Dian Zhong

Kuo Zeng

Jun Li

Xinyi Yang

Yang Song

Youjian Zhu

Gilles Flamant

Ange Nzihou

Haiping Yang

Hanping Chen

3E analysis of a biomass-to-liquids production system based on solar gasification

Keywords: Biomass-to-liquid, Gasification, Solar energy, 3E analysis

The solar gasification system (SGS) and traditional system are modeled by Aspen Plus. And their energetic, economic as well as ecologic (3E) performance are compared. The effects of different feedstocks and Direct Normal Irradiance (DNI) to the productivity and efficiency of SGS are also carried out. The results show that a biomass-based, solar-assisted liquid fuel production system offers a productivity increasing potential of 49.44% more refined syngas and 65.74% more liquid fuels due to its higher utilization of feedstock. And for the same reason, the energetic performance of SGS increases from 40.22% to 40.66% for thermal efficiency and from 38.35% to 41.35% for exergy efficiency compared with those of reference system. The final price of products in SGS could only be equal to that of reference system when the carbon tax is under considering, while both of them shows no superiority to that of petroleum products. SGS has a better ecology performance contributed by less total carbon and water footprints which are only 55.27% and 61.34% of those of the reference system.

Introduction

The demand for liquid fuel is increasing rapidly for long-distance transport, with fuel consumption of about 580,000 barrels per day in 2019, and it is excepted to grow continually [1]. The consumed fuel derived from the petroleum products released a lot of greenhouse gas and negative gas like CO 2 and NO X when combusted, which is harmful to environment. Therefore, it is urgent and necessary to find a method to obtain liquid fuel with more ecologic benefits while achieving higher efficiency and better economic benefit competitive with traditional techniques. To achieve this purpose, biomass is proposed to be a promising carbon feedstock for liquid fuel production.

Biomass gasification has been proved to be an attractive approach for liquid fuel production [START_REF] Ruiz | Biomass gasification for electricity generation: Review of current technology barriers[END_REF][START_REF] Service | Biomass Fuel Starts to See the Light[END_REF][START_REF] Parthasarathy | Hydrogen production from steam gasification of biomass: Influence of process parameters on hydrogen yield -A review[END_REF]. Large quantities of syngas are produced in this gasification reaction, and the syngas can be further synthesized to liquid fuel through suitable catalytic processes like Fischer-Tropsch (F-T) process [START_REF] Dry | The Fischer-Tropsch process: 1950-2000[END_REF]. However, traditional autothermal gasification systems require additional heat to drive the endothermic reactions by burning about 20-30% of the feedstock [START_REF] Nickerson | Economic assessment of solar and conventional biomass gasification technologies: Financial and policy implications under feedstock and product gas price uncertainty[END_REF]. It results in the syngas contamination with combustion products and the low utilization rate of feedstock that further decreases the gasification efficiency (the ratio of total low heating value of syngas products to that of feedstock) [START_REF] Iliuta | Allothermal steam gasification of biomass in cyclic multi-compartment bubbling fluidized-bed gasifier/combustor -New reactor concept[END_REF]. To overcome these drawbacks, solar energy has been explored as an alternatives of traditional heat source driving the gasification process [START_REF] Piatkowski | Solar-driven gasification of carbonaceous feedstock -A review[END_REF][START_REF] Taylor | Solar gasification of carbonaceous materials[END_REF][START_REF] Lédé | Solar thermochemical conversion of biomass[END_REF][START_REF] Zedtwitz | The solar thermal gasification of coal -energy conversion efficiency and CO2 mitigation potential[END_REF].

The productivity of syngas as well as liquid fuel usually increases with the assistance of solar energy. Kaniyal et al [START_REF] Kaniyal | Polygeneration of liquid fuels and electricity by the atmospheric pressure hybrid solar gasification of coal[END_REF] obtained a higher total annually averaged energetic productivity of 21% for a coal-to-liquid system with solar gasification comparing with tradition system. Hathaway et al. established a biomass gasification system with concentrated solar power of 100 MW, the annual average thermal efficiency reached up to 82% superior to that of the traditional gasification system [START_REF] Nickerson | Economic assessment of solar and conventional biomass gasification technologies: Financial and policy implications under feedstock and product gas price uncertainty[END_REF][START_REF] Hathaway | Steam gasification of plant biomass using molten carbonate salts[END_REF][START_REF] Hathaway | Integration of Solar Gasification With Conventional Fuel Production: The Roles of Storage and Hybridization[END_REF]]. Though the system using biomass as feedstock is found to have better ecologic potential [START_REF] Yang | Biomass-to-Methanol by dual-stage entrained flow gasification: Design and techno-economic analysis based on system modeling[END_REF], its total cost and price are still not competitive enough with that of conventional refinery [START_REF] Dimitriou | Techno-economic and uncertainty analysis of Biomass to Liquid (BTL) systems for transport fuel production[END_REF]. Recent researches have reported that solar system is expected to become economically competitive in the near future based on the larger scale of production and expected reduction in the cost of subsystems [START_REF] Rahbari | A solar fuel plant via supercritical water gasification integrated with Fischer-Tropsch synthesis: Steady-state modelling and techno-economic assessment[END_REF].

Considering that the fuel prices will fluctuate with its investment and overall cost of a certain system, the economic performance of a solar gasification system (SGS) remains unknown. Consequently, the economic performance of SGS in different situations should be further investigated [START_REF] Loutzenhiser | A review of the state-of-the-art in solar-driven gasification processes with carbonaceous materials[END_REF][START_REF] Bai | A polygeneration system for the methanol production and the power generation with the solar-biomass thermal gasification[END_REF]. As for the ecological impact, the participation of solar energy significantly reduces the CO 2 emission in gasification process without burning the feedstock. But there are still additional indirect emission and consumption accompany with the extra facilities of solar system, which causes the ecologic performance of solar driven system unclear.

Therefore, the 3E analysis of a biomass-to-liquids production system based on solar gasification was carried out in this paper. Aspen Plus is used to model the SGS and the reference system to analyze their total net efficiency of thermal and exergy as well as their productivity. Besides, the performance of SGS under different feedstocks and DNI is estimated. And the economic performance was discussed by estimating the system cost and products' price as well the sensitivity. Finally, the ecological footprint was analyzed to indicate the ecological influences on the environment.

System

Flow chart and boundary

The transience and intermittent of solar energy are harmful to the liquid hydrocarbon fuel synthesis process because the FT reactor is very sensitive to the variations during system operation. So, the solar gasification system is designed to be consisted by three subsystems named solar gasification, fuel synthesis system and syngas storage system. Syngas storage system can not only smooth the fluctuations in upstream, e.g., fluctuation caused by the transience of solar energy, but also reserve enough syngas in case of a long period without sunlight like rainy days or dark nights. A traditional gasification system that has the same structure with SGS except using less storage tanks and replacing solar collection section with air separation is

Reaction conditions

Biomass gasification with steam includes complex chemical reactions. The main reactions that are related to gasification process are listed in Table 1.

+ = + ∆ = - ℃ , (5)
The ideal overall reaction of steam gasification of biomass can be described by Eq [START_REF] Nickerson | Economic assessment of solar and conventional biomass gasification technologies: Financial and policy implications under feedstock and product gas price uncertainty[END_REF].

( )

1 x y 2 2 x C H O + 1-y H O=CO+ 1-y+ H 2       (6)
where x and y respectively represent the H/C and O/C of biomass materials. This gasification reaction tends to increase in volume, which is not conducive to gas production. Thus, the pressure of gasification reaction is set at 1 bar in this paper.

Xinjiang, China has abundant solar resource and is widely planted with cotton, which is suitable for solar gasification. Therefore, the cotton stock was selected as feedstock. And the proximate analysis of the air-dried cotton stock was 80.785% [START_REF] Bai | Integration Mechanism for Thermochemical Hybrid Utilization for Solar Energy and Biomass[END_REF]. Based on the characteristics of cotton straw samples and Eq [START_REF] Nickerson | Economic assessment of solar and conventional biomass gasification technologies: Financial and policy implications under feedstock and product gas price uncertainty[END_REF], the theoretical value of the ratio of steam to biomass (S/B) for gasification reaction is 0.25. however, the ratio needs to be adjusted to a specific range which is generally higher than 2, resulting extra water input. Therefore, the S/B changes with different feedstock and reaction conditions.

Methodology and data

System modeling

The solar gasification sub-system, fuel synthesis sub-system and other important devices had been modeled. Those other important devices include syngas storage facilities, power generation equipment and auxiliary equipment used in both systems.

Solar gasification sub-system

In the gasification reactor, the biomass feedstock and steam were heated by concentrated solar energy to produce crude syngas.

Q η = Q +m LHV & & & (9)
Where the bio LHV is the low heat value of biomass feedstock.

The actual heat absorption of the biomass gasification with steam gasification,

T Q & is: gasification,T bio gasification,T Q =m Δh & & (10)
Where

Δh = n h -n h -n h °°∑ (11)
Where i , T h represents the formation enthalpy of syngas components i at the reaction temperature.

The actual heat absorption of the biomass gasification with steam can also be calculated as: gasification,T reactor absorption

Q =Q η & & (12)
where the reactor Q & represents the energy radiated to the reactor, kW; absorption η represents the absorption efficiency of reactor, which can be expressed as [START_REF] Zedtwitz | The solar thermal gasification of coal -energy conversion efficiency and CO2 mitigation potential[END_REF]:

absorption σT η =1- IC         (13)
Where σ represents Steff-Boltzmann constant, W/(m 2 K 4 ); I represents the standard solar intensity, W/m 2 ; C represents the average concentrating ratio of the concentrated solar energy entering the reactor.

Then the heat loss caused by the reactor is:

( ) reactor,loss reactor absorption

Q =Q 1-η & & (14)
The solar energy from the heliostat field to the gasification reactor can be illustrated as:

reactor solar opt Q =Q η & & (15)
where the solar Q & represents the solar radiation received by the heliostats field, kW; opt η represents the average optical efficiency of the heat collecting system, which can be assumed as 68.6% based on the Hu's study [START_REF] Müller | A pressurized high-flux solar reactor for the efficient thermochemical gasification of carbonaceous feedstock[END_REF]. Then the heat loss caused by the optical characteristics of the heliostat field is:

( ) solar,loss solar opt Q =Q 1-η & & (16)
Exergy of solar energy is calculated according to the following formula [START_REF] Ng | Thermodynamic analyses of solar thermal gasification of coal for hybrid solar-fossil power and fuel production[END_REF]:

ambient solar solar sun T Ex = 1- Q T       & & (17)
where ambient T represents the ambient temperature, which was set as 25°C; sun T is the temperature on the surface of sun, which is about 5500°C.

Exergy of biomass can be calculated as follows [START_REF] Ng | Thermodynamic analyses of solar thermal gasification of coal for hybrid solar-fossil power and fuel production[END_REF]:

bio bio bio bio Ex =β m LHV & & (18)
where bio β represents the ratio of biomass chemical exergy to lower calorific value, and is calculated as follows [START_REF] Ng | Thermodynamic analyses of solar thermal gasification of coal for hybrid solar-fossil power and fuel production[END_REF]:

O N H bio C C C m m m β =1.0437+0.1882 +0.0661 +0.0404 m m m                   (19)
where C m , H m , O m and N m represent the elemental mass ratio of C, H, O and N in the biosmass materials.

The ratio of 2 H to CO in the crude syngas obtained from gasification reaction needs to be adjusted by water-gas shift reaction described as Eq [START_REF] Dry | The Fischer-Tropsch process: 1950-2000[END_REF]. The reaction releases heat of 42kJ per mole of CO , and the heat released by water gas conversion reaction is:

WGS CO Q =42 n × & ( 20
)
where The recovery rate of PSA is about 90% [START_REF] Mclean | Energy efficiency of gas separation by pressure swing adsorption[END_REF], thus some 2 H and CO will be released into the exhaust gas.

                        ∑ ∑ (21)

Fuel synthesis sub-system

The syngas produced from solar gasification is processed through a series of processes. Some of syngas is injected into the F-T reactor, while the rest is stored in the gas storage tank. Before entering the F-T reactor, the syngas needs to be pressurized by a compressor to the reaction pressure required by the F-T reaction, which is expressed as follow:

( ) 2 n 2n+2 2 2n+1 H +nCO=C H +nH O ( 22
)
The yields of hydrocarbon products with different carbon atom numbers satisfied the Anderson-Schulz-Flory distribution [START_REF] Rahbari | A solar fuel plant via supercritical water gasification integrated with Fischer-Tropsch synthesis: Steady-state modelling and techno-economic assessment[END_REF], and the formula is as follows:

( )

2 n-1 n M =na 1-a ( 23
)
where n is the number of carbon atoms in hydrocarbon products; n M is the mass fraction of hydrocarbons with n carbon atoms in hydrocarbon products; α is the growth probability of carbon chain, whose value is related to the operating conditions of F-T reaction and the composition of fed syngas.

The F-T reaction is reported to produce more hydrocarbons that contain more than five carbon atoms (especially wax) at a lower reaction temperature. And the cobalt-based catalyst will also have a better performance for F-T reaction in this condition [START_REF] Selvatico | Low Temperature Fischer-Tropsch fuels from syngas: Kinetic modeling and process simulation of different plant configurations[END_REF]. Therefore, the F-T synthesis in these systems was conducted at a temperature of 220°C and pressure of 20 bar, producing 8.15% light gas, 29.72% gasoline, 28.21% diesel and 33.92% wax. The α is 0.9 [START_REF] Swanson | Techno-economic analysis of biomass-to-liquids production based on gasification[END_REF] and the CO conversion rate reaches 90% [START_REF] Guo | Performance assessment of Fischer-Tropsch liquid fuels production by solar hybridized dual fluidized bed gasification of lignite[END_REF] in this case.

Waxes can be further hydrocracked to produce hydrocarbons with shorter carbon chains like gasoline and diesel. The yields of hydrocarbons derived from hydrocracking process with platinum-based catalyst were 3.77wt% for light gas, 61.19wt% for gasoline, 27.04% for diesel, 8.00% for wax remained when the temperature is 330°C and the pressure is 35 bar while the mass ratio of 2 H to waxes is 0.1 [START_REF] París | Hydroconversion of paraffinic wax over platinum and palladium catalysts supported on silica-alumina[END_REF].

2

H required for hydrocracking is produced by electrolysis of water. In this paper, an improved acid/alkaline amphoteric water electrolysis (AAEC) technology [START_REF] Lei | Hydrogen generation with acid/alkaline amphoteric water electrolysis[END_REF] is used to provide 2 H for hydrocracking to obtain higher system efficiency.

The electric power consumed during water electrolysis is:

2 AAEC H AAEC W =V E & (24) where 2 H
V & is the volume flow rate of 2 H , m 3 /s; AAEC E is the energy comsumption producing 2 H per unit volume, which is reported to be 2.85 kWh/m 3 [START_REF] Lei | Hydrogen generation with acid/alkaline amphoteric water electrolysis[END_REF].

Other devices

A compressor is needed to compress the refined syngas for storage. The gas storage pressure is set at 5 bar. The energy consumption of compressor will be calculated with the isentropic compressor model in Aspen Plus as the isentropic efficiency and the mechanical efficiency set at 0.88 [START_REF] Chen | Design efficiency optimization of one-dimensional multi-stage axial-flow compressor[END_REF][START_REF] Danish | Effect of tip clearance and rotor-stator axial gap on the efficiency of a multistage compressor[END_REF] and 0.9 [START_REF] Zhang | Study on Catalysts and Technology of Methanol Synthesis from Biomass Syngas[END_REF], respectively.

The light gas from the fuel synthesis process will be used to drive the gas-steam combined cycle for electricity generation to meet the system's electrical load, with syngas making up the shortfall. Since the power generation is not the main point, the thermal efficiency of the combined cycle based on the LHV of fuel can be set at 55%

according to the results in other researches [START_REF] Chen | Analyses on supercritical water gasification of coal and integration of novel ower generation systems[END_REF][START_REF] Li | The Energy Efficiency Optimization and Feedwater Control Analysis of Integrated Solar Combined Cycle[END_REF] and the power generation and heat release of the combined cycle are calculated by follows respectively:

CC CC fuel fuel W =η n LHV & (25) ( ) CC CC fuel fuel Q = 1-η n LHV & & (26)
where fuel n &

is the mole flow rate of fuel, mol/s; fuel LHV is the low heat value of fuel, kJ/kg; CC η is the efficiency of the combined system.

Thermodynamic analysis 3.2.1 Gasification efficiency

The efficiency of solar gasification gasification η can be defined as [START_REF] Bellouard | Solar thermochemical gasification of wood biomass for syngas production in a high-temperature continuously-fed tubular reactor[END_REF]:

syngas gasification reactor bio bio LHV η = Q +m LHV (27)
The molar fraction of gasification products under different temperatures are shown in

Material flow

As descripted by Eq(7)-Eq [START_REF] Guo | Performance assessment of Fischer-Tropsch liquid fuels production by solar hybridized dual fluidized bed gasification of lignite[END_REF], these two systems were modeled and simulated with Aspen Plus software, in which the input of biomass feedstock was set at 1 kg/s, and operation parameters such as fuel yield and system power consumption were calculated. Particularly, the material flow of two systems were listed in Table 2, and the differences of products yield between two systems intuitively represent their characteristic of productivity.

Validation

As long as the H 2 /CO ratio in syngas remaining unchanged, the mass fraction of the products derived from FT process won't change according to Eq 22 and Eq 23.

Thus it is reasonable to mainly focus on the syngas production from gasification process. In order to check the accuracy of gasification system in predicting the productivity of syngas compositions, the dry gas compositions obtained from the Aspen Plus model is compared against experimental findings by [START_REF] Chuayboon | Insights into the influence of biomass feedstock type, particle size and feeding rate on thermochemical performances of a continuous solar gasification reactor[END_REF]

Cost of each parts 3.3.1 Cost of heliostat field

Xinjiang in China is rich in solar energy resource; whose solar radiation intensity exceeds 700 W/m 2 in both typical days of summer and winter at noon. In this paper, a solar radiation intensity of 700 W/m 2 was selected as the benchmark to design the heliostat field. The designed power of gasification reactor in both systems is set at 50 MW, on which all subsequent designs of the rest parts of two systems are based.

The System Advisor Model [START_REF] Zedtwitz | The solar thermal gasification of coal -energy conversion efficiency and CO2 mitigation potential[END_REF] (SAM) platform developed by the Renewable Energy Laboratory of the United States was used for modeling and calculation in the design of heliostat field. According to the solar radiation conditions, the preliminary design of the heliostat field is carried out. The whole heliostat field consists of 886 heliostats, and each single one has an area of 144 m 2 , whose total area is 127,584 m 2 .

The equipment cost of heliostat field is calculated based on the data given by SAM platform, and the results showed that the reactor with a designed power of 50MW needs 886 heliostats whose single area is 144 m 2 , making up the whole heliostat field with an area of 127584 m 2 . And the total cost of this part reached 2.

The annual biomass consumption of reference system was about 4 9.36 10 × t/y.

Cost of gas storage tank and heat exchanger

The operation time can be estimated as 6 hours a day. A solar multiple of 3 is adopted, which means that more storage tanks are necessary to support the downstream processes keeping running for at least 16 hours when the syngas production is offline. The cost of storage tanks is related to their material, which is usually carbon steel [START_REF] Muroyama | Modeling of a Dynamically-Controlled Hybrid Solar/Autothermal Steam Gasification Reactor[END_REF], and their thickness determined by national standard of pressure vessels [START_REF] He | Economic analysis of gas storage devices for compressed air energy storage system based on life cycle cost[END_REF] as 5 bar. According to the container's thickness and capacity, the metal consumption and the cost of a single gas tank is estimated as shown in Appendix Table A1.

The shell and tube heat exchanger can meet the heat exchange requirement of two systems. The heat transfer area of heat exchanger can be calculated as follows:

Q S= ΔTK (28)
where: Q represents the heat load of exchanger, kJ; ΔT represents the logarithmic mean temperature difference, °C; K is heat transfer coefficient.

The cost of heat exchanger, as well as the cooler that is the same with the heat exchanger in structure, is related to the heat exchange surface area. And their correlation can be expressed as the following function [START_REF] Xiang | Shell-and-tube heat exchanger network total cost optimization using improved particle swarm algorithm[END_REF]:

3 a heat exchanger 1 2 C =a +a S ( 29
)
where the 1 a = 8000, 2 a = 259.2, 3 a = 0.91, as stainless steel was used. The costs of heat exchanger and cooler are calculated as shown in Table 3.

Cost of other devices

The main equipment of fuel synthesis system of SGS includes solar heat collection equipment, gasification reactor, water-gas shift reactor, F-T synthesis reactor, water electrolyser, hydrocracking reactor and fractionator, CO 2 removal devices and gas-steam combined cycle power station. Reference systems also require air separation equipment due to the use of oxygen as the main gasifier. The cost of the main equipment can be estimated by relevant literature [START_REF] Rahbari | A solar fuel plant via supercritical water gasification integrated with Fischer-Tropsch synthesis: Steady-state modelling and techno-economic assessment[END_REF][START_REF] Feng | Simulation and economic analysis of IGCC power plant[END_REF][START_REF] Wu | System development of integrated high temperature and low temperature Fischer-Tropsch synthesis for high value chemicals[END_REF][START_REF] Haarlemmer | Investment and production costs of synthetic fuels -A literature survey[END_REF][START_REF] Larson | Large-scale gasification-based coproduction of fuels and electricity from switchgrass[END_REF][START_REF] Baliban | Toward Novel Hybrid Biomass, Coal, and Natural Gas Processes for Satisfying Current Transportation Fuel Demands, 1: Process Alternatives, Gasification Modeling, Process Simulation, and Economic Analysis[END_REF]. Since the size of the equipment used in the literature is different from what is used in this paper, the cost of these devices can be converted exponentially as follows [START_REF] Swanson | Techno-economic analysis of biomass-to-liquids production based on gasification[END_REF]:

sf r 0 0 S C=C S       (30)
where 0 C is the cost of the reference equipment; r S is the capacity of the new equipment; 0 S is the capacity of the reference equipment; sf is the scale factor.

Compressors are needed during the compression of syngas. According to the requirements of the mass flow rate and the import pressure, the four-stage compressor (m-155/55) made by Sichuan Huaxi General Machinery Company was selected, whose cost is 2×10 6 CNY each [START_REF] Zhang | Study on Catalysts and Technology of Methanol Synthesis from Biomass Syngas[END_REF]. A total cost of four compressors was 8×10 6 CNY.

Hydrogen required by hydrocracking reaction is provided by water electrolyser.

According to the current technical level, the cost of electrolytic water reactor is 7,800 ~ 9,500 CNY/kW [START_REF] Schmidt | Future cost and performance of water electrolysis: An expert elicitation study[END_REF]. The cost of the water electrolyser is 34.09×10 6 CNY as the load of the electrolyser in the system is 3588.79kW.

Total investment of system

The costs of each parts of the system are shown in Table 4 based on the data given previously and the methods presented in Appendix, Table A2. The operating cost of the whole SGS is consisted of variable cost and fixed cost. Variable costs include biomass raw materials (pretreatment), industrial water, catalysts, etc., and fixed costs include workers' wages, benefits, and system maintenance costs. Error! Reference source not found. summarizes the main assumptions used to assess operating costs. The data mainly derived from relevant researches [START_REF] Rahbari | A solar fuel plant via supercritical water gasification integrated with Fischer-Tropsch synthesis: Steady-state modelling and techno-economic assessment[END_REF][START_REF] Swanson | Techno-economic analysis of biomass-to-liquids production based on gasification[END_REF] and the National Bureau of Statistics [START_REF]China Statistical Yearbook-2019[END_REF]. Where a is calculated as 2% TFI C which represents the total fixed investment introduced in Appendix Table A2.

Cost of liquid fuel products

The fuel cost is one of the primary indicators for technical economic evaluation of the system, which was calculated as follows. Under the condition that the net present value (NPV) is not less than 0 and the internal rate of return (IRR) is not less than the discount rate, the minimum price of the fuel products is taken as the fuel cost.

The NPV and IRR will be calculated based on the annual net cash flow n C as follows [START_REF] Yang | Hybrid life-cycle assessment for energy consumption and greenhouse gas emissions of a typical biomass gasification power plant in China[END_REF]:

( ) N n n n=0 0 C NPV= 1+i ∑ (31)
( )

N n n n=0 C =0 1+IRR ∑ (32)
Where the n C is the annual net cash flow of n th year; 0 i is discount rate; N represents the system designed life. The economic assumptions used in the NPV calculation are shown in Table 6. Carbon emission and water consumption data are converted into carbon footprint and water footprint for further analysis of its impacts on environment. The LHV of gasoline and diesel was used as a unified evaluation standard to calculate the carbon footprint and water footprint of the two systems at different processes.

CO 2 Emission and water consume of faming and transportation

The method introduced above are not suitable for calculating those footprints of faming and transportation sections of raw materials, so another method is applied. The distribution coefficient of stalk i is the ratio of the market value of stalk per unit cultivated area to the sum of the market value of both cotton and stalk per unit cultivated area. According to the investigation, the average market price of cotton in Xinjiang China is 12736 CNY/t, while the price of cotton stalk is 290 CNY/t [START_REF] Bai | Integration Mechanism for Thermochemical Hybrid Utilization for Solar Energy and Biomass[END_REF].

Together with the cotton yield data, the yield of cotton stalk per unit cultivated area is about 4.5 times of that of cotton, and the distribution coefficient i is 0.093 in this case. The data of price and yield are attached in the Appendix, Table A3 and A4 [START_REF]Statistic Bureau of Xinjiang Uygur Autonomous Region. Xinjiang Yearbook 2017[END_REF].

The carbon emission and the water consumption of cotton stalk were 0.28 kg CO 2 eq /kg and 0.45 m 3 /kg respectively. They were calculated by multiplying the distribution coefficient of stalk i and the carbon emission or the water consumption of the whole cotton plant including its stalk in Xinjiang China, which were 2.98 kg CO 2 eq /kg [START_REF] Zhao | Study on Carbon Footprint of Cotton/Peanut Intercropping in Xinjiang[END_REF] and 4.8 m 3 /kg [START_REF] Zhong | Water footprints of primary crop production in Xinjiang[END_REF] respectively.

The distribution density of cotton straws in Xinjiang is 9.84t /km 2 [START_REF] Zhang | Estimation and utilization of the cotton straw resource in Xinjiang[END_REF]. According to the annual biomass consumption of SGS and reference system, the collection radius of cotton straws is 43km and 54km respectively. Due to the lack of relevant data support, the transport process of raw materials was simplified as carrying biomass from the collection area to the factory. Assuming the fuel used by agricultural transport vehicles is diesel, the consumption coefficient of diesel during transport is 0.05 L/(t km) ⋅ [START_REF] Yang | Greenhouse gas emissions of corn-ethanol production in China[END_REF]. According to the material flow calculated previously and the density of diesel taken as 0.83kg/L, it was calculated that the diesel consumed by SGS and the reference system in the transportation process is 102t and 203t respectively, which results in the direct CO 2 emission of two systems accounting for 7.

Result and discussion

Energy performance

Table 8 shows the energy and the exergy efficiency of two systems. It presents almost the same energy efficiency of 40.66% for SGS and 40.22% for reference system. While the exergy efficiency of SGS is higher than that of reference system, accounting for 41.35% and 38.35%, respectively. The replacement of the solar energy and relative devices made little promotion for the energy efficiency of SGS. But solar gasification could still be regarded as a more appropriate utilization of bio-energy for its better exergy efficiency.

According to the material flow calculated by Aspen Plus, each parts' thermal loss and exergy loss of SGS have been presented in Fig 7 . The attenuation of solar energy failed to be received by the mirrors may be responsible for the biggest energy and exergy loss of solar collector, which accounting for 31.81% and 29.46% respectively.

Though the optical loss is unable to be eliminated, it can be alleviated by redesigning the heliostat field with a higher efficiency. Besides, we can reduce the fuel demand for the power generation and improve the thermal efficiency of the system by using the heat from the FT reaction to preheat the working fluid in the power generation section.

What's more, after analyzing the power consumption inside the system, it is found water electrolyser takes the largest power consumption proportion, accounting for 54.74%, which indicates that increasing the efficient of the hydrogen production process is the most effective way to reduce the power consumption inside the system and thus improve the energy efficiency. The efficiency and the productivity of SGS changes with different biomass feedstock input. Table 9 shows the compositions of six different biomasses as well as the material flow and efficiency of SGS fed with these feedstocks. The fuel productivity changes along with the total input of water, which corresponds with the theoretical results calculated by Eq 6. As shown in Fig 8, both the thermal and exergy efficiency present a strong correlation with the standard molar enthalpy of formation (h, kJ/mol) of each feedstock and their volatiles content (V, wt%). The Bio-1 has a higher h and V, resulting its highest efficiency. While in the Bio-3, the lowest h and V corresponded to the lowest efficiency. The Bio-6 have the highest V, but its efficiency of thermal and exergy were less than those of bio-1 because of its lower h. According to Eq 11, the total heat absorption of the gasification reaction ( gasification,T

Δh

) is negatively correlated with the h. And the decrease of the total heat absorption caused by the lower h can reduce the demand of solar energy input, which eventually leads to an efficiency increment. Higher volatile fraction is reported to have a potential of higher syngas productivity and higher H 2 fraction [START_REF] Li | The Energy Efficiency Optimization and Feedwater Control Analysis of Integrated Solar Combined Cycle[END_REF][START_REF] Wieckert | Syngas Production by Thermochemical Gasification of Carbonaceous Waste Materials in a 150 kW th Packed-Bed Solar Reactor[END_REF]. What's more, the volatile fraction generally predicts the heating value of feedstock [START_REF] Thipkhunthod | Predicting the heating value of sewage sludges in Thailand from proximate and ultimate analyses[END_REF], which would affect the h. Thus, to some extends, the h and V shows the same influence on the efficiency of the SGS. The Fig 9 shows the effect of DNI to the SGS system. Both the thermal and exergy efficiency have a peak when DNI reaches 600 W/m 2 . However, the syngas productivity continually increases along with the DNI and tends to be stable as DNI >700 W/m 2 , which is set as the nominal operation point of SGS for a higher yield of syngas. According to the data in Table 2, the SGS produced 49.44% more refined syngas and 65.74% more liquid fuels than the reference system, indicating that the SGS has huge advantage in productivity because the feedstock can be highly utilized instead of being consumed to provide reaction heat. However, this advantage could be narrowed when the DNI is lower than the nominal point, and will be eliminated as DNI decreasing to 335 W/m

Economic analysis

As shown in Table 4, fuel synthesis takes the largest part of equipment expenditure both in SGS and reference systems, reaching 36.37% and 54.11%

respectively. The SGS and reference system have their own unique equipment such as solar collector and air separator. The cost of syngas storage tanks in SGS is 22.5 times of that in reference system. Because SGS needs bigger and more tanks to store the syngas to deal with the transience of solar energy and avoid the system instability that would make the downstream syngas supply discontinued. In this case, more syngas compressors are needed in SGS, so the cost of auxiliary equipment of the SGS is 52.64% higher than that of the reference system. With the same output of refined syngas, SGS consumes less biomass feedstock and requires less crude syngas to be refined. Therefore, the solar energy system has a smaller size of equipment used for syngas production, and the cost is 59.98% of the reference system. The results of the investment schedule show that the equipment cost of fuel synthesis, syngas storage and solar collector takes the highest proportion in the cost of fundamental equipment.

Further optimization improvement of these three parts could effectively control and reduce the investment of the system. For example, a lower solar multiply could increase the utilization rate of this part of equipment and cut down the cost of storage tanks due to the less demand of syngas stored for fuel synthesis at night, which contributes to reducing the production cost and improving the production capacity of the system.

The main economic performance of each system is shown in Table 4. The total investment of solar energy system is 48.78% higher than that of the reference system with the same production capacity. In the case of similar NPV and IRR, the production costs of SGS for gasoline and diesel are 1.507×10 4 CNY/t and 1.242×10 4 CNY/t respectively, which is 24.32% higher than the production costs of the reference system. According to Summary of gasoline and diesel retail prices in 36 large and medium-sized cities in China in October 2018 [START_REF]gasoline prices in 36 large and medium-sized cities in China in October 2018[END_REF][START_REF]Diesel prices in 36 large and medium-sized cities in China in October 2018[END_REF], the price of gasoline (#92) was 4 1.045 10 × CNY/t, while the price of diesel (#0) was 4 0.880 10 × CNY/t. Taking these as the reference prices, the cost of producing liquid fuel from biomass in both systems is much higher than that producing from oil (costing 44.21% more for SGS, and 16.30% for reference systems). However, in the perspective of energy sustainability, the continuous depletion of fossil resource will inevitably lead to the rise of oil price, and the cost of solar energy system can be further reduced through technological progress and optimized design of system process. All of these indicate that SGS has potential for a long-term competition.

As a party for the United Nations Framework Convention on Climate Change, the carbon tax is inevitable in order to meet the goal of controlling greenhouse gas emissions. Since a reference system releases more greenhouse gas per unit LHV of products than SGS, the carbon tax would have a bigger impact on the reference system. Take the cost of producing gasoline as an example. To further analyze and determine the factors that have the great impact on system cost, the variation of cost under 13 scenarios set in a range of ±20% has been estimated, and the results are presented in Fig 10. It shows that the production capacity and the proportion of loans has the biggest influence on the system cost.

With the production capacity increasing by 20%, the total cost of SGS is reduced by 15.4%. It proves that technological progress or process optimization can cut down the cost by improving system capacity with little investment increase. In scenario 9, the proportion of loans in the total investment of the system is reduced to 80%, and the system cost is reduced by 12.241%, making it the second biggest influence factor to system cost. The total system cost seems to be less sensitive to the changes of equipment cost, interest rate of loan and the fixed cost, which cause the variation of total cost less than 7%. The changes of revenue tax rate and price of biomass have nearly no influence (less than 1.6%) on the total cost.

Ecological analysis

The carbon and the water footprint of two systems are given in Table 10 and 0.

Overall, the carbon footprint of SGS and the reference system is 0.1561 t/GJ and 0.2825 t/GJ respectively. And their water footprint is 39.514 m 3 /GJ and 64.416 m 3 /GJ respectively. The carbon and water footprints of SGS were only 55.27% and 61.34% of those of the reference system, indicating that SGS has a better ecology performance. In the building and equipment section, the carbon footprint of SGS is 0.0379t /GJ, 53.76% higher than that of reference system; and the water footprint is 0.502m3 /GJ, 59.96% higher than that of reference system. This is because the SGS needs to build solar collectors and larger-scale gas storage devices, which brings additional indirect carbon and water footprint.

The operation and maintenance process contribute the largest proportion of whole carbon footprint in both systems, which is shown in Table 10. The carbon footprint of SGS in this process is 43.2% of that of reference system, because the reference system has additional carbon emission derived from burning part of feedstock. The distribution of carbon emission in this process (Fig 11 ) shows the CO 2 removal process is the major source of carbon emission. Moreover, SGS produced liquid fuels with less electricity and catalyst consumption per LHV than reference systems. The CO 2 removal process of reference system release 166% more CO 2 than that of SGS because it needs more biomass input as the liquid fuel products are set to be the same for two system, which would obviously increase the amount of CO 2 . At the meantime, part of the feedstock in reference system is combusted to provide the heat, which makes a further increase of the amount of CO2 in the crude syngas. The air separator that only exists in reference system is the major reason for the higher electricity consumption afforded by power generation sector. And the higher CO 2 concentration in the syngas results in the more electricity consumption of CO 2 removal devices.

These together lead to the higher CO 2 emission from power generation by combustion.

As for the catalysts used in water-gas-shift reaction, FT synthesis and hydrocracking process, the amount of the catalysts is determined by the flow rate of the syngas. So with the same fuel productivity, the SGS needs less syngas and thus has a lower indirect CO 2 emission from catalysts. As for the water footprint, although the direct water footprint of SGS is higher than that of reference system due to the additional water used in gasification process to increase the H 2 /CO ratio, the indirect water footprint caused by using catalyst and other materials is much lower than that of the reference system. This leads to the overall water footprint of SGS during operation and maintenance process is still smaller than a reference system.

Conclusion

Solar gasification system (SGS) produced 49.44% more refined syngas and 65.74% more liquid fuels than the reference system. The thermal efficiency of the two systems was about the same, while the exergy efficiency of the SGS was slightly higher than that of the reference system. The volatile matter fraction and standard mole enthalpy of feedstock formation are positively related to the thermal and exergy efficiency of SGS. The efficiencies reach their maximum value at the DNI of 600W/m 2 , and the productivity continually increases and finally remain unchanged as DNI>700 W/m 2 . Though the SGS are not economic-competitive in short term, it still has potential when the carbon tax reaches 551.42 CNY/t. It's proven that the change of production capacity has a great influence on system cost, whose changes of ±20% could lead to a system cost change rate ranging from -15.406% to 23.109%. The total carbon and water footprints of the solar system were only 55.27% and 61.34% of those of the reference system, showing that SGS has a better ecology performance.

Acknowledgement

Authors acknowledge funding from the National Natural Science Foundation of . Table A2. System total investment estimation method [START_REF] Swanson | Techno-economic analysis of biomass-to-liquids production based on gasification[END_REF].

Parameter Method

Fig 1 .Fig 2 .

 12 Fig 1. Flow chart of SGS and reference system

∑

  represents the proportion of one component in the mixture of gases; the subscripts F, P and E represent feedstock, product and exhaust respectively.

Fig 3 .Fig 3 .Fig 4 .Fig 5 .

 3345 Fig 3. It indicates that the molar ratio of H 2 and CO increases rapidly with the

6 96.22 10 ×

 610 CNY. Based on the designed solar radiation intensity of 700 W/m 2 , the annual biomass consumption of SGS is about 4 5.65 10 × t/y. The operational conditions of reference system were converted proportionally under the assumption that its liquid fuel output was the same as SGS based on the data shown in Table

  respectively. The farming and transportation data of CO 2 emission and water consumption of two systems are presented in Table

Fig 7 .

 7 Fig 7. The thermal loss and exergy loss proportion of SGS each part:

Fig 8 .

 8 Fig 8. The standard molar enthalpy of formation and the volatiles content of six

Fig 10 .

 10 Fig 10. Variation rate of total system cost under 13 scenarios.

Fig 11 .

 11 Fig 11. Distribution of carbon emission in operation and maintenance process

  , Natural Science Foundation of Shenzhen (JCYJ20170818164006890) and the Key Laboratory of Coal Science and Technology, Taiyuan University of Technology (MKX201905).

Table 1 .

 1 Reactions in gasification process[START_REF] Piatkowski | Solar-driven gasification of carbonaceous feedstock -A review[END_REF][START_REF] Loutzenhiser | A review of the state-of-the-art in solar-driven gasification processes with carbonaceous materials[END_REF][START_REF] Pala | Steam gasification of biomass with subsequent syngas adjustment using shift reaction for syngas production: An Aspen Plus model[END_REF]

	Name	Reactions	number
	Steam gas	2 C H O CO H 2 + = + , ∆ H 25 ℃	=	131 kJ/mol	(1)
	shift reaction
	Boudouard	2 C CO 2CO H + = ∆ ,	25 ℃	=	172 kJ/mol	(2)
	reaction
	Methanation	2 C 2H CH + =	4 , ∆ H	25 ℃	75 kJ/mol = -	(3)
	Reaction
	Methane	4 CH H O CO 3H 2 + = +	2 , ∆ H	25 ℃	=	206 kJ/mol	(4)
	refined
	Water-gas
		2 CO H O CO H 2	2		H	25	42 kJ/mol
	shift

  volatile, 2.686 wt% ash, 11.004 wt% fixed carbon, and 5.525 wt% moisture. The elemental composition of the dried feedstock was 45.011 wt% carbon, 6.094 wt%

	hydrogen, 40.040 wt% oxygen, and 0.601 wt% nitrogen. Its low heating value
	reached 17564.80 kJ/kg

Table 2 .

 2 Material flow of each system.

	Material	Solar system (kg/s) Normal system (kg/s)
	Biomass	1.000	1.000
	Steam	0.525	0.196
	Oxygen	0.000	0.466

Table 3 .

 3 The costs of heat exchanger and cooler[START_REF] Xiang | Shell-and-tube heat exchanger network total cost optimization using improved particle swarm algorithm[END_REF].

			Material type	Heat/cold load (kW)	Heat exchange area (m 2 )	Cost (10 6 CNY)
	SGS	Heat exchanger		15511.93	485.88	0.39
		Cooler	S31020	8421.43	2338.72
	Reference system	Heat exchanger		5570.95	143.67	0.39
		Cooler		7539.21	2792.58

Table 4 .

 4 Details of investments in two systems

	SGS	Reference system

Table 5 .

 5 Variable and fixed costs of SGS[START_REF] Rahbari | A solar fuel plant via supercritical water gasification integrated with Fischer-Tropsch synthesis: Steady-state modelling and techno-economic assessment[END_REF][START_REF] Swanson | Techno-economic analysis of biomass-to-liquids production based on gasification[END_REF][START_REF]China Statistical Yearbook-2019[END_REF].

	Items	Cost
	Variable cost
	Biomass (CNY/t)	289.05
	Industrial water (CNY/t)	5.00
	Catalysts in F-T reaction (CNY/kg)	215.74
	Catalysts in gas-water shift reaction (CNY/kg) 124.36
	Catalysts in hydrocracking (CNY/kg)	350.32
	PSA padding (CNY/kg)	31.09

Table 6 .

 6 Economic assumptions

	Economic assumptions	Contents
	System designed life (year)	30
	Loan interest rate	8.00%

Table 7 .

 7 The CO 2 emission and water consumption of two systems

		SGS		Reference system
		Diesel	Straw	Diesel	Straw
	Section number	37		37
	Direct CO 2 emission (t/y)	0.31E+03		0.62 E+03
	Indirect CO 2 emission
	Intensity (t/10 4 CNY)	1.09E+01		1.09E+01
	Water consumption intensity
	(m 3 /10 4 CNY)	7.08E+01		7.08E+01
	Value (10 4 CNY/y)	7.73E+01		1.65E+02

Table 8 .

 8 The thermal efficiency and exergy efficiency of two systems.

			SGS	Reference system
	System
		Energy	Exergy	Energy	Exergy
	Input (kW)
	Biomass (kW)	17565.00	19822.17	17565.00 19822.17
	Solar energy (kW)	11235.24	10647.56
	Output (kW)
	Gasoline (kW)	6837.44	7350.65	4125.36 4435.00
	Diesel (kW)	4872.85	5247.69	2940.03 3166.19
	Efficiency (%)	40.66	41.35	40.22	38.35
	Electricity
	Air separation (kW)			469.75
	CO 2 removal (kW)		273.04	253.71
	Compressor (kW)		861.72	533.62
	Water electrolyser (kW)		1372.26	827.95

Table 9 .

 9 Characterization of six feedstocks[START_REF] Hathaway | Steam gasification of plant biomass using molten carbonate salts[END_REF][START_REF] Li | Biomass gasification in molten salt for syngas production[END_REF][START_REF] Li | Gasification characteristics of biomass at a high-temperature steam atmosphere[END_REF][START_REF] Hu | Integrated gasification and catalytic reforming syngas production from corn straw with mitigated greenhouse gas emission potential[END_REF][START_REF] Edreis | Kinetics, thermodynamics and synergistic effects analyses of petroleum coke and biomass wastes during H2O co-gasification[END_REF] and the material flow as well as efficiency of SGS fed with these feedstocks

		Number	Bio-1	Bio-2	Bio-3	Bio-4	Bio-5	Bio-6
	Biom
			Cotton	Cotton	Rice	Corn	Corn	Corn
	ass	Material
			stock-1	stock-2	husk	stover-1	stover-2	stover-3
	C (wt%)	45.01	46.56	50.03	45.70	43.60	46.09
	H (wt%)	6.09	6.04	6.07	5.70	6.30	5.60
	O (wt%)	40.04	41.82	42.54	42.36	48.30	38.22
	V (wt%)	80.79	77.49	68.32	75.03	75.70	80.92
	Bio (kg/s)	1	1	1	1	1	1
	H 2 O (kg/s)	0.525	0.530	0.577	0.522	0.390	0.590
	Fuel (kg/s)	1.536	1.541	1.588	1.533	1.399	1.601

  When the carbon tax reached 551.42 CNY/t, the production cost of SGS increased by 14.62%, reaching 2204.38 CNY/t, while the production cost of the reference system increased by 42.49%, reaching 5152.44 CNY/t. The production cost of the two systems come to the same level in this case. A further increase of the carbon tax would bring SGS economic advantage immediately.

Table 10 .

 10 Carbon footprint of two systems

	System	Processes	CO 2 emission (t/y)	Direct carbon footprint (t/GJ)	Indirect carbon footprint (t/GJ)	Life-cycle carbon footprint (t/GJ)

Table 11 .

 11 Water footprint of two systems

			Water	Direct	Indirect
						Life-cycle
			consumpt	water	water
	System	Processes				water footprint
			ion (m 3 /y)	footprint (m 3 /GJ)	footprint (m 3 /GJ)	(m 3 /GJ)
		Farming	2.52E+07	35.723	2.373	38.097
		Transportation
			5.47E+03	0.000	0.008	0.008
		of biomass
	SGS	Building and
			3.32E+05	0.000	0.502	0.502
		equipment
		Operation and
			6.00E+05	0.801	0.106	0.907
		maintenance

Table A3 .

 A3 Cotton market price in Xinjiang China.

	Region	City	Cotton price (CNY/t)
	Kashi	Payzawat
		Makit
		Yopurga
		Marabishi
	Bayingol	Korla
	Total fundamental equipment cost Yuli	TFC C
	Venues preparation ( site C ) Bugur	15% TFC C
	Service facility ( serv C ) Tiemenguan	20% TFC C
	Direct fixed investment ( DFI C ) Turpan Toksun	TFC C + site C + serv C
	Unexpected expenditure and contractors' Ili Kuytun
				18% DFI C
	fees ( cont C ) Akesu Kuqa
	Total depreciated capital ( TDC C ) Xayar	DFI C + cont C
	Land cost ( land C ) Average price		2% TDC C
	Start-up capital ( startup C	)	10% TDC C
	Total fixed investment ( TFI C )	TDC C + land C + startup C
	Working cost ( WC C )		15% TFI C
	Total capital investment ( TCI C )	TFI C + WC C

Table A4 .

 A4 Planting area, yield and straw collection of cotton in Xinjiang China[START_REF]Statistic Bureau of Xinjiang Uygur Autonomous Region. Xinjiang Yearbook 2017[END_REF].

	Year Cotton plantation area (10 4 hm 2 ) Cotton yield (10 4 t) Stalk yield (10 4 t)
	215.491	430.00	1890.00
	227.311	409.36	1842.12

Appendix

Highlights:

► 3E analysis was used to evaluate the solar gasification biofuel production system. ► Solar gasification system (SGS) exhibited higher productivity and exergy efficiency.

► The efficiency performance of SGS under different conditions were estimated.

► Carbon and water footprint of SGS were 44.73% and 38.66% lower.

► SGS will be competitive when carbon tax reaches 551.42 CNY/t.


G Amoyal

V Schoepff

F Carrel

N Blanc De Lanaute

M Michel

J C Angélique

A prototype of hybrid gamma imager has been developed, based on a single Timpex3 readout chip hybridized with a 1 mm thick cadmium telluride semiconductor. This prototype combines coded-aperture imaging spectrometry and Compton imaging techniques to perform hybrid gamma imaging. It associates and takes advantage of both techniques to locate gamma emitters. The prototype is designed to be portable and compact in order to ease its field use. In this work, we present experimental results obtained with this prototype in coded-aperture imaging spectrometry mode, Compton imaging mode, and hybrid gamma imaging.

I. INTRODUCTION

Gamma imaging is a technique well adapted for the remote localization of radioactive sources. It presents a real interest in several application fields: decommissioning of nuclear facilities, nuclear waste management, and radiation protection in Nuclear Power Plants (NPP) or Homeland Security. This technique can simultaneously provide qualitative (spatial localization of radioactive sources) and quantitative information (radioactive hot spot intensities). Using gamma camera reduces the dose received by operators and consequently achieves the ALARA principle ("As Low As Reasonably Achievable"). There are two gamma imaging techniques for the localization of gamma emitters: coded-aperture imaging and Compton imaging [START_REF] Cieślak | Coded-aperture imaging systems: Past, present and future development -A review[END_REF] [START_REF] Frandes | Image Reconstruction Techniques for Compton Scattering Based Imaging: An Overview[END_REF]. Most of the gamma cameras are based on these approaches, requiring a pixelated detector. Gamma camera with coded-aperture relies on a spatial modulation technique. The coded-aperture consists of a matrix made of transparent and non-transparent elements with a specific pattern, and is placed between the radioactive source and the detector. A source object projects the pattern of the coded-aperture on the detector; this projection is called a shadowgram. The reconstruction of the radioactive source is achieved by applying the knowledge of the coded-aperture pattern to the shadowgram [START_REF] Cieślak | Coded-aperture imaging systems: Past, present and future development -A review[END_REF]. A spectrometric criterion can be used to discriminate radioactive hotspots according to their energies, this criterion is used to carry out coded-aperture spectro-imaging. This imaging technique performs well in terms of sensitivity and spatial resolution, especially for photons with energy lower than 100 keV. However, its field-of-view is limited by the coded-aperture geometry, and its performances decrease as the energy of the incoming photons increase (due to sensing volume measuring efficiency). Compton cameras rely on the Compton scattering kinematics. If an incident photon interacts two or more times in the detector, it is possible to locate a radioactive source. Indeed, the energy deposited during the first interaction allows calculating the first scatter angle, while the interaction position allows estimating the direction of the incident photons. The first scatter angle and the direction infer a cone, the radioactive source is on the surface of said cone. The intersection of several cones thus corresponds to the position of the radioactive source. The Compton imaging technique has the advantage of covering a theoretical field-of-view of 4π sr. However, because of the Compton kinematics, Compton camera performances are strongly degraded for incident energies lower than 100 keV. Moreover, the incident photon energy must be known a priori and on top of that, the quality of the localization is directly correlated to the spectrometric performances of the Compton gamma camera. In addition, it is also required to be able to identify coincidences within the sensitive area. The purpose of this study is to develop a hybrid gamma camera prototype combining coded-aperture imaging with Compton imaging techniques. One of the interests of such an imager is to combine, in a single system, the benefits of both techniques and to mitigate at the same time associated limitations. A second interest concerns the multiplication of information sources for the localization of radioactive sources, because it opens interesting possibilities for the algorithmic reconstruction step. The developments carried out in this study consisted in combining the two imaging techniques mentioned above around the Timepix3 chip, hybridized with a 1 mm cadmium telluride semiconductor. This article gives an overview of the experimental results obtained with Timepix3 with coded-aperture spectro-imaging, Compton imaging, and with hybrid gamma imaging. First, the main characteristics of Timepix3 are described, then descriptions of codedaperture spectro-imaging and Compton imaging are detailed, and the specifications of the radioactive sources used for this study are described. Following, the experimental results obtained with both imaging techniques are presented. An example emphasizing the interest of hybrid gamma imaging is also given. Finally, future developments related with this topic are underlined at the end of the article.

Development of a hybrid gamma camera based on

Timepix3 for nuclear industry applications

II. MATERIAL AND METHODS

A. Timepix3

In 2013, CERN developed Timepix3 [START_REF] Poikela | Timepix3: a 65K channel hybrid pixel readout chip with simultaneous ToA/ToT and sparse readout[END_REF], that works as an event-based readout chip. The Timepix3 hybrid-pixel readout chip is a matrix made of 256 × 256 square-shaped pixels with 55 µm pitch. Timepix3 can be hybridized to several types of semiconductor, such as Si or CdTe with thicknesses up to 5 mm. In each pixel, it simultaneously records the Time-over-Threshold (ToT) that gives access to deposited energy [START_REF] Jakubek | Energy-sensitive X-ray radiography and charge sharing effect in pixelated detector[END_REF], and the time-of-arrival (ToA) with a time resolution of 1.5 ns. Therefore, the Timepix3 chip has the necessary requirements to perform coded-aperture spectro-imaging and Compton imaging, which are: energy measurement, fast time sampling, and fine pixelisation pitch to precisely locate interaction position. For this study, we used a Timepix3 hybridized with a 1 mm thick N-on-P cadmium telluride semi-conductor equipped with Schottky contacts, operating in electron collection mode under -300 V bias. The power supply of the chip, the semiconductor bias, and the communication with the acquisition computer are carried out by the Katherine readout system developed in cooperation between Faculty of Electrical Engineering, University of West Bohemia and IEAP, CTU [START_REF] Burian | Katherine: Ethernet Embedded Readout Interface for Timepix3[END_REF]. In order to simplify the terminology in our paper, the term "Timepix3" will refer to the Timepix3 readout chip hybridized to the cadmium telluride semiconductor. The energy calibration was set following the method described in [START_REF] Jakubek | Precise energy calibration of pixel detector working in time-over-threshold mode[END_REF], and was performed in the energy range from 15 keV to 1.3 MeV. The energy calibration allows for spectrometric performances such that for photons with an energy > 80 keV, energy resolution is < 10 %, and the relative error on measured energy is < 0.5 % for photons with an energy > 25 keV [START_REF] Amoyal | Evaluation of Timepix3 Si and CdTe hybrid pixel detectors spectrometric performances on X-and gamma rays[END_REF].

B. Coded-aperture spectro-imaging

For several years, CEA List has been designing coded aperture systems, such as GAMPIX [START_REF] Carrel | GAMPIX: a new generation of gamma camera for hot spot localisation[END_REF]- [START_REF] Amoyal | Metrological characterization of the GAMPIX gamma camera[END_REF], that has been industrialized by MIRION Technologies under the commercial name of iPIX [START_REF] Amgarou | iPIX: A New Generation Gamma Imager for Rapid and Accurate Localization of Radioactive Hotspots[END_REF], [START_REF] Amgarou | A comprehensive experimental characterization of the iPIX gamma imager[END_REF]; and lately Nanopix, the smallest gamma imager based on coded-aperture in the world. Both of those technologies rely on a pixellated detector, associated with a MURA coded-aperture [START_REF] Gottesman | New family of binary arrays for coded aperture imaging[END_REF]. For our prototype, we selected a 4 mm-thick tungsten alloy, rank 7, MURA coded-aperture. This choice is based on our expertise in the GAMPIX system, this coded-aperture is the best compromise between angular resolution and measurement sensitivity (here defined as the minimum time to locate a radioactive source) [START_REF] Carrel | GAMPIX: A new gamma imaging system for radiological safety and homeland security purposes[END_REF]. The distance between the coded mask and the detector is 1.6 cm, which corresponds to a squared field-of-view of 50°×50°. Figure 1 is a photography of Timepix3 equipped with its MURA coded-aperture. The so-called "mask/anti-mask" procedure (MAM procedure) is used, and consists in carrying out a second measurement after rotating the mask by 90°. The MAM procedure enables a suppression of the gamma background generated by radioactive sources located out of the field-of-view of the gamma camera [START_REF] Gottesman | New family of binary arrays for coded aperture imaging[END_REF]. The decoded image is obtained using the algorithm described in [START_REF] Gottesman | New family of binary arrays for coded aperture imaging[END_REF]. This method consists in an autocorrelation between the decoding function described by the coded-aperture pattern, and the measured shadowgram. In our case, the sensitive area is the Timepix3 detector, and is made of 256×256 pixels; therefore, the decoded image has the same size and is made of 256×256 pixels. During the decoding process, the spectrometric information is also taken into account in order to deploy coded-aperture spectro-imaging. This feature enables to obtain a decoded image corresponding to a specific energy region of interest, which is defined by the end-user. To do so, during the decoding process, a criterion on the energy deposited by each event is applied.

C. Single detector Compton imaging

The most popular configuration for Compton imaging is based on a two detectors structure: a first detector, "the scatterer", in which the Compton scattering process will occur, associated to a second detector, the "absorber", in which the scattered photon will be absorbed [START_REF] Frandes | Image Reconstruction Techniques for Compton Scattering Based Imaging: An Overview[END_REF]. Compton imaging takes advantage of scattering kinematics, as illustrated in Figure 2 (a). The energy deposited during the scattering process determines the scattering angle (see Figure 2 (a)), then the interaction position determine the direction of the incident gamma-ray. The position of the radioactive source is set on the surface of a cone, which apex corresponds to the scattering event position, as illustrated in Figure 2 (b). Considering several interactions from a unique source, multiple Compton cones are determined and their overlap coincide is the source location, as shown in Figure 3 (a). Results shown in Figure 3 and Figure 4 are obtained with Monte-Carlo simulations of a Cs-137 radioactive source, with a two detectors structure (300 µm-thick Si material, associated with a 1 mm-thick CdTe material, 1 cm apart from each other). The Cs-137 radioactive source is set at 1 m in the upper-right part of the system's field-of-view. Those results are obtained considering a "perfect" system, in which there is no uncertainty, either on positions or on energies measurements. In this work, the Compton cones are projected on a pixelated half-sphere, which corresponds to a 2π sr field-of-view. The algorithm used to calculate the projection of Compton cones consists in a simple back projection (SBP) algorithm, as described in [START_REF] Frandes | Image Reconstruction Techniques for Compton Scattering Based Imaging: An Overview[END_REF]. Once the Compton cones are projected on the pixelated half-sphere, the position of the radioactive source is highlighted by applying a threshold at 50% of the maximal number of counts in the image, associated with a two-dimensional Gaussian filtering at 1 sigma, as illustrated in Figure 3 (b). The Gaussian filtering is done so as to apply mathematical regularization. We also have implemented the possibility of modifying the pixel grid of the half-sphere on which the Compton cones are projected. This allows for a trade-off between the angular resolution and the sensitivity, as illustrated in Figure 4. This kind of trade-off makes sense in the case of on-field measurements, for which the measurement times may be limited, making it impossible to obtain sufficient statistics for fine pixelisation. Projections shown in Figure 4 result from Monte-Carlo simulations with the same configuration as the one shown in Figure 3 (a). The Cs-137 radioactive source is located 1 m from the system, in the middle of the system's field-of-view. In this study, we used a "single detector configuration", in which, said detector is thick enough for Compton scattering and absorption to occur in the same detection volume. We decided to develop such a configuration because it offers benefits in terms of compactness and price. Moreover, using a single detector configuration also avoids the need to synchronize two detectors. The single detector configuration is illustrated in Figure 5FIGURE 5. In such a configuration, there is no direct information on the nature of the identified Compton events, i.e. which interaction corresponds to Compton scattering and which corresponds to absorption. In the case of the single detector configuration, the temporal resolution of Timepix3 (1.5 ns) is higher than the photon time-of-flight between two interactions. Therefore, there is no direct a priori on the interactions. The sequence of interactions shall be reconstructed from the information on the positions and energies of both interactions. In the case where one of the two energies has an energy greater than the energy of the Compton edge, this interaction will necessarily correspond to the absorption. For all other cases, it is not possible to know directly which interaction corresponds to which event. A deterministic algorithm, based on the Klein-Nishina formula was developed in [START_REF] Xu | 4-pi Compton imaging with single 3D position-sensitive CdZnTe detector[END_REF]. This algorithm consists in probabilistically determining which event is associated to each of the two interactions (Compton scattering or absorption). The function describing the probability density of a photon to be scattered at a certain an angle, is calculated taking the solid angle fraction into account, and is given by Equation (II-1) [START_REF] Xu | 4-pi Compton imaging with single 3D position-sensitive CdZnTe detector[END_REF]. In Equation (II-1), 𝛽 is the Compton scattering angle; and 𝐾(𝛽, 𝐸) (called the Klein-Nishina coefficient [START_REF] Klein | Über die Streuung von Strahlung durch freie Elektronen nach der neuen relativistischen Quantendynamik von Dirac[END_REF]) is the probability that a photon with an energy 𝐸 scatters at an angle 𝛽.

𝑃(𝛽) ∝

𝐾(𝛽, 𝐸) sin 𝛽 𝑑𝜑 ∝ 2𝜋 • 𝐾(𝛽, 𝐸) sin 𝛽 (II-1) The construction of the Compton cones, enabling for the localization of radioactive sources, requires both energy measurements and information on the interaction positions. In the case of a single detector configuration, there is no direct information on the depth of interaction. In order to minimize the uncertainty on the Compton cone axes, a practical solution consists in considering only the pairs of events separated by at least a certain distance. A study has been carried out by Monte-Carlo simulation with MCNP6 2.0 [START_REF] Goorley | Initial MCNP6 Release Overview -MCNP6 version 1[END_REF] to determine this optimal distance. This study consisted in simulating a CdTe volume, with dimensions similar to those of Timepix3 described in paragraph II.A. The CdTe volume is irradiated by a source emitting photons with an energy of 662 keV (Cs-137), located at 1 m in front of the detection volume. For those Monte-Carlo simulations, energy resolutions of Timepix3 [START_REF] Amoyal | Evaluation of Timepix3 Si and CdTe hybrid pixel detectors spectrometric performances on X-and gamma rays[END_REF]; and its 55 µm pixelisation are taken into account. Figure 6 shows the evolution of the number of Compton cones, as a function of the distance between the position of Compton scattering and absorption. As expected, an increase in the distance between the two interactions implies a decrease in the number of Compton cones. However, an increase in the distance between the two interactions lowers the angular resolution associated with the reconstructed source. Figure 7 shows three reconstructed images using the SBP algorithm for different distances between the Compton scattering position and the absorption position. Figure 8 is a plot of azimuthal FWHM at the reconstructed position of the source, as a function of the distance between the Compton scattering position and the absorption position. In order to compare the FWHM values, the same number of Compton cones (100) is used for the reconstruction for each position. This value was chosen because it corresponds to the number of Compton cones obtained for the maximum distance between the interaction positions. For a distance of 1 cm between two interactions, 100 Compton cones are obtained for a Cs-137 having emitted 1.2×10 13 photons (equivalent to an exposure time of 33 hours using a 100 MBq source). A greater number of Compton cones would imply an even greater time of exposure, which would be incompatible with end-user constraints. An increase in the minimum distance between interactions implies a decrease in FWHM at the reconstructed source position. Since FWHM at the reconstructed source position corresponds to the angular resolution in degree, it equates to a lower angular resolution. Therefore, a compromise must be found between the minimum distance between interactions positions and the sensitivity of the Compton gamma camera. The value corresponding to the best compromise between the number of Compton cones and the angular resolution was found to be 5 mm.

D. Radionuclide

In order to assess the possibility of achieving coded-aperture spectro-imaging and Compton imaging using Timepix3, several measurements have been carried out using different radionuclides chosen for they are the most commonly encountered in the nuclear industry. Activities and experimental equivalent dose rates at 1 m are summarized in table 1. The different energies used to identify/locate those radionuclides are also specified.

III. EXPERIMENTAL MEASUREMENTS

A. Coded-aperture spectro-imaging using Timepix3 Several studies have been carried out to evaluate the coded-aperture imaging performances of the GAMPIX gamma camera [START_REF] Carrel | GAMPIX: a new generation of gamma camera for hot spot localisation[END_REF], [START_REF] Gmar | GAMPIX: A new generation of gamma camera[END_REF], [START_REF] Amoyal | Metrological characterization of the GAMPIX gamma camera[END_REF], [START_REF] Carrel | GAMPIX: A new gamma imaging system for radiological safety and homeland security purposes[END_REF]. The GAMPIX gamma camera is a prototype of coded-aperture imaging system. It is industrialized by MIRION Technologies under the name of iPIX [START_REF] Amgarou | iPIX: A New Generation Gamma Imager for Rapid and Accurate Localization of Radioactive Hotspots[END_REF]. The detector of the GAMPIX camera is a Timepix detector hybridized to a 1 mm thick CdTe semiconductor. The dimensions of the semiconductor, as well as the pixelisation of the detector, are identical between the GAMPIX gamma camera detector and the here discussed prototype gamma camera based on Timepix3. In addition, the operating modes of the two detectors are almost identical. Therefore, the experimental evaluation of the localization capabilities with Timepix3 proposed in this study will not be exhaustive. For in-depth studies on this matter, see [START_REF] Carrel | GAMPIX: a new generation of gamma camera for hot spot localisation[END_REF], [START_REF] Amgarou | A comprehensive experimental characterization of the iPIX gamma imager[END_REF]- [START_REF] Amgarou | iPIX: A New Generation Gamma Imager for Rapid and Accurate Localization of Radioactive Hotspots[END_REF]. In order to evaluate Timepix3 ability for coded-aperture spectro-imaging, the following measurement has been carried out: two radioactive sources (Am-241 and Ba-133) have been simultaneously positioned at 1 m within the field-of-view of our prototype. The Am-241 source is positioned in the upper-part of the field-of-view, whereas the Ba-133 source is positioned in the lower-part. The measurement is carried out following the MAM procedure (see paragraph II.B): 30 min in mask mode, and 30 min in anti-mask mode. Figure 9 shows the decoded images without any energy discrimination (a), and when Ba-133 characteristic energies are selected (b), and when the Am-241 characteristic energy is selected (c). Without energy selection, only the Ba-133 radioactive source is reconstructed. With energy selection applied, both sources can be separately identified. Sources are positioned at 1 m from the Timepix3 detector, with an exposure time of 1 h (30 min in mask mode, and 30 min in anti-mask mode).

A limit of coded-aperture imaging concerns the reconstruction of artefacts when a radioactive source is located at the periphery of the fully coded field-of-view of the coded-aperture [START_REF] Charalambous | Aberrations in gamma-ray coded aperture imaging[END_REF]. Figure 10 (a) illustrates the field-of-view and the coding fraction of a coded-aperture gamma camera. Figure 10 (b) shows the reconstruction of a Cs-137 source positioned in said position. In this case, there is an uncertainty about the true position of the Cs-137 source (hot spot split into two diametrically opposite parts). A knotty case may be encountered while performing in-situ measurements, if the radioactive source is located in the partially coded field-of-view, then it will be not located in the decoded image. In the case of an unknown environment, it is not possible to know what the «true» position. The solution to counter this effect is to perform an additional Compton measurement that allows the identification of the "real" radioactive source position.

B. Compton imaging with Timepix3

Experimental validation of the Timepix 3's ability to locate radioactive hot spots in Compton mode have been carried out with the following radionuclides: Am-241, Ba-133, Na-22, Cs-137, and Co-60. Characteristics in terms of activity and equivalent dose rate are summarized in table 1.

1) Single source localization and sensitivity evaluation

In this paragraph, we present experimental results obtained for a single radionuclide source positioned in the 2π Timepix 3 field-of-view. First, we evaluated the ability to locate a single radionuclide and the associated sensitivity. The source/detector distance is 1 m and exposure time 1 h. This protocol was applied for each radionuclide. Experimental results demonstrate that Timepix3 is able to locate Ba-133, Na-22, Cs-137, and Co-60 for the investigated positions as illustrated in Figure 11. However, it was not possible to locate Am-241: this is mainly due to the energy resolution of the detector (5.65 keV at 59.5 keV) combined with the Doppler broadening effect [START_REF] Zoglauer | Doppler broadening as a lower limit to the angular resolution of next-generation Compton telescopes[END_REF]. The combination of these two parameters increases the uncertainty on the calculation of the Compton scattering angle. After validating the experimental feasibility of Compton imaging with Timepix 3, we focused on the sensitivity in this specific acquisition mode. For this evaluation, the radioactive source is positioned at the center of the field-of-view. Sensitivity is qualitatively evaluated according to a visual criterion on the reconstructed image. The sensitivity indicator is defined as the minimum exposure time necessary to correctly locate a single radioactive source. Sensitivity evaluation is obtained by observing the reconstructed images for acquisition time bins of 60 seconds. Sensitivity depends on the pixel grid of the reconstructed image. Therefore, we evaluated sensitivity for three different pixelisations of the reconstructed image: 20×20, 90×90 and 180×180 pixels. Figure 12 shows the reconstructed images with the 20×20, 90×90, and 180×180 pixelisations of the half-sphere, for which the best sensitivity value was assessed reached. For these experiments, we used a Cs-137 source positioned at the center of the Compton field-of-view. Sensitivity values for Ba-133, Cs-137, and Co-60 sources, and for all three pixelisations of the half-sphere of, are presented in table 2. Timepix3 here experimentally demonstrates is capability to locate the Ba-133, Cs-137, and Co-60 sources at 1 m, considering acquisition time between 240 and 1560 seconds depending on the pixelisation of the reconstructed space and the nature of the source. These results confirms that it is possible to achieve shorter measurement times by reducing the number of pixels (e.g. with a 20×20 pixelisation). while the Cs-137 source on the top side. Figure 13 (a) shows the measured energy spectrum corresponding to this experimental configuration: the peaks used for radionuclides identification/location are highlighted. Figure 13 shows the reconstructed images when the energies of Ba-133 (b) and Cs-137(c) are selected. A second measurement was carried out by placing a Cs-137 source and Co-60 source simultaneously within the Timepix3 field-of-view. The distance from the radioactive sources to the detector is 1 m, and the acquisition time is 2 h. The Cs-137 source is positioned on the left side of the detector's field-of-view. The Co-60 source is positioned in the right part of the field-of-view. Figure 14 (a) shows the energy spectrum and the peaks of interest with a specific colour code. Figure 14 shows the reconstructed images when the energies of Cs-137 (b) and Co-60 (c) are selected.

C. Hybrid gamma imaging with Timepix3

In order to evaluate hybrid imaging with Timepix3, an experimental measurement was performed by simultaneously positioning an Am-241 source within the field-of-view of the coded-aperture prototype, and a Cs-137 source within its partially coded field-of-view. This measurement aims to illustrate the interest of a hybrid gamma imager, and to illustrate how to take advantage of each gamma imaging technique.

The measurement setup of this experiment is described hereinafter.The distance between the sources and the detector is 1 m. For practical reasons, measurements are performed separately: first in "Compton imaging" mode and then in "coded-aperture imaging" mode. Acquisition time for the Compton imaging measurement is 1 hour. The acquisition time for coded-aperture imaging measurement is 30 minutes in mask position, and 30 minutes in anti-mask position. The exposure time for coded-aperture could be reduced to one minute, but in order to have enough counting statistics it was decided to carry out a one-hour measurement. Figure 15 (a) and (b) show the decoded images obtained by selecting, respectively, the energy lines associated to Am-241 (59.5 keV) and Cs-137 (662 keV) using coded-aperture spectro-imaging. The decoded images are projected on the pixelated half sphere also used for Compton imaging. The Am-241 source is measured at the correct position; however, there is an uncertainty related to the position of the Cs-137 source (two hotspots are recontructed). The actual position of the Cs-137 source is in the lower-left side of the field-of-view, as shown by the Compton image in Figure 15 (c). In this measurement, coded-aperture imaging is used for the localization of an Am-241 source, and Compton imaging is used for the localization of a Cs-137 source. First, the Am-241 can not be localized with our system and Compton imaging (see paragraph III.B.1), highlighting one interest of the coded-aperture imaging information. Regarding the Cs-137 source, it is positionned within the partially coded field-of-view of the coded aperture, therefore an uncertainty on its position remains with coded-aperture imaging (see paragraph III.A and Figure 15 Once the positions of the radioactive sources have been identified, the decoded images associated with each of the two imaging modes can be superposed on a visible image. The main interest of this aspect is the visualization of the imaging results. The visible image is a photograph taken with a fisheye camera, or wide-angle camera (i.e. 2π sr field-of-view), well adapted to Compton acquisition modes. Figure 16 shows the superposition of the visible image, the coded-aperture image, associated with the Am-241 (Figure 15 (a)), and the Compton image, associated with the Cs-137 source (Figure 15 (c)). In order to improve visibility, a grid pattern has been added, corresponding to a reconstructed space pixelisation of 20×20 pixels.

IV. CONCLUSION AND FUTURE DEVELOPMENTS

The objective of this work was to develop a prototype hybrid gamma imager, combining coded-aperture and Compton imaging techniques, dedicated to applications in the nuclear industry. The different localization measurements in coded-aperture imaging and Compton imaging with the developed prototype demonstrated the feasibility to build a hybrid gamma imager based on Timepix3. An experimental validation of the prototype is detailed. In this test, an Am-241 source was positioned in the fully-coded field-of-view of the coded-aperture, and a Cs-137 source was placed in the partially-coded field-of-view of the coded-aperture. The experimental results demonstrate the prototype performances and thus emphasis the benefits of a hybrid gamma imager. The various developments carried out in this work open up several prospects for the further development of a hybrid imager based on Timepix3 technology. First, the sensitivity and angular resolution capabilities of the prototype in Compton imaging mode need to be evaluated. Indeed, only its localization capabilities have hereby been demonstrated. Another perspective concern hybrid imaging. At this stage, information from Compton and coded-aperture imaging is only normalized and added-up A study must be conducted to make the best use of both sources of information. On the other hand, it has been shown by Lynde [START_REF] Lynde | Demonstration of coded-aperture fast-neutron imaging based on Timepix detector[END_REF], that the combination of a neutron-sensitive conversion layer with a tungsten coded-mask around the Timepix detector allows neutron imaging. The developments led by Lynde, thus paved the way for a double-particle hybrid imaging system, sensitive to both X and gamma rays and neutrons.

Figure 1 :

 1 Figure 1: Timepix3 and its MURA coded-aperture. Photo credit: P. Stroppa/CEA.

Figure 2 :

 2 Figure 2: (a) Compton scattering diagram and equation; (b) determination of a Compton cone through interactions locations in scatterer and absorber detectors.

Figure 3 :

 3 Figure 3: Representations of the location of a radioactive source using the simple back projection algorithm, (a) without filtering, (b) with a 50% threshold and 1 sigma Gaussian filtering.

Figure 4 :

 4 Figure 4: Impact of the half-sphere pixel grid on which are projected the Compton cones: (a) 20×20 pixels; (b) 90×90 pixels; (c) 180×180 pixels; (d) 360×360 pixels.

Figure 5 :

 5 Figure 5: Illustration of the single detector configuration for Compton imaging.

Figure 6 :

 6 Figure 6: Evolution of the number of Compton cones as a function of the minimal distance between Compton scattering position and absorption position. Error bars are given at three sigmas.

Figure 7 :

 7 Figure 7: Reconstructed image with the SBP algorithm of a Cs-137 source positioned in front of a single detector configuration, for different distances between the Compton scattering position and the absorption position ((a) 1 mm, (b) 5 mm, (c) 9.5 mm). The images are reconstructed using 100 Compton cones, without any filtering. The colour scale corresponds to the number of Compton cones intersection.

Figure 8 :

 8 Figure 8: Plot of the azimuthal FWHM (i.e the angular resolution in degree) of the reconstructed hotspot against the distance between the positions of Compton scattering and absorption. For each distance, 100 Compton cones are used to reconstruct the position of the source.

Figure 9 :

 9 Figure 9: Coded-aperture imaging decoded images) when: (a) no energy criterion is used (a); (b) Ba-133 characteristic lines are selected (81 keV, 303 keV, 356 keV); (c) Am-241 characteristic line is selected (59.5 keV). The measurement is carried out with MAM procedure.

Figure 10 :

 10 Figure 10: (a) Field-of-view and coding fraction illustration of a coded-aperture gamma camera showing the Fully Coded Field-Of-View (FCFOV), and the Partially Coded Field-Of-View (PCFOV). (b) Localization of a Cs-137 source, using coded-aperture imaging, positioned at the border of the fully coded field-of-view. The source is positioned in the upper part of the coded-aperture field-of-view. The distance between the source and the detector is 1 m. The measurement is carried out with the MAM procedure with a total exposure time of 1 h (30 min in mask mode, and 30 min in anti-mask mode).

Figure 11 :

 11 Figure 11: Compton imaging results obtained with the Timepix3 detector for different radionuclides positioned in a 2π sr field-of-view: (a) Ba-133, (b) Na-22, (c) Cs-137, (d) Co-60. The energy lines used to reconstruct the images are given for each radionuclide. For each measurement, the distance between the Timepix3 detector and the radioactive source is 1 m, total exposure time is 1 h.

Figure 12 :

 12 Figure 12: Example of reconstructed images corresponding to the qualitatively evaluated sensitivity limit. Pictures are obtained with a Cs-137 source positioned at the center of the field-of-view, at a distance of 1 m. Values are given as pixelisation and exposure time: (a) 20×20 pixels, 180 s; (b) 90×90 pixel, 300 s; (c) 180×180 pixels, 360 s. Table 2: Sensitivity evaluation for different radionuclides at a distance of 1 m, for pixel grids of the reconstructed space of 20×20, 90×90 and 180×180 pixels.

Figure 13 :

 13 Figure 13: Multiple source localization with Timepix3 working in Compton mode (Ba-133 and Cs-137 simultaneously positioned within the field-of-view): (a) the measured energy spectrum, the peaks used for a considered radionuclide are highlighted. For a given energy peak "mu" corresponds to the mean energy; (b) reconstructed image when energy lines of Ba-133 are selected; (c) reconstructed image when energy line of Cs-137 is selected.

Figure 14 :

 14 Figure 14: Multiple sources localization with Timepix3 and Compton mode (Cs-137 and Co-60 simultaneously positioned within the field-of-view): (a) measured energy spectrum, with peaks used for radionuclide identification are coloured; (b) reconstructed image when energy line of Cs-137 is selected; (c) reconstructed image when energy lines of Co-60 are selected.

  (b)), highlighting one interest of the Compton imaging information. This measurement is an example of the contribution of coded-aperture imaging for the localization of the Am-241 source, and of Compton imaging for the localization of the Cs-137 source.

Figure 15 :

 15 Figure 15: (a) and (b), Localization using coded-aperture spectro-imaging of an Am-241 source positioned in the fully coded field-of-view and a Cs-137 source positioned at the border of the fully coded field-of-view of the coded-aperture. Energy windows are set at the characteristic energy gamma emissions of the radionuclides (59.5 keV for Am-241 and 662 keV for Cs-137). A 50% threshold is applied on the decoded images. (c) Compton imaging location of the Cs-137 source with Timepix3. A Gaussian filtering and 50% threshold are applied.

Figure 16 :

 16 Figure 16: Example of the use of the hybrid gamma imaging with Timepix3. Superposing the wide-angle visible image, the decoded image in the coded-aperture mode with a 50% threshold and an energy window corresponding to Am-241, and the decoded image in the Compton mode with a 70% threshold and an energy window corresponding to Cs-137 (yellow).

Table 1 :

 1 List of activities and measured equivalent dose rates of the different radionuclides used to evaluate the localization performances of the Timepix 3 gamma camera prototype. The characteristic energy lines used for gamma imaging associated with each radionuclide are listed.

	Radionuclide	Activity [MBq]	Experimental equivalent dose rate at 1 m [µSv.h -1 ]	Characteristic energies used for gamma imaging [keV]
	Am-241	73.8	0.95	59.5
	Ba-133	23.3	1.64	303; 356
	Na-22	1.5	0.57	511; 1022
	Cs-137	34.5	2.92	662
	Co-60	20.0	6.11	1173; 1332