Ildar Rakhmatulin

Mathieu Lihoreau

Jose Pueyo

Selective neutralisation and deterring of cockroaches with laser automated by machine vision

Keywords: Laser, pest control, German cockroaches, Blattella germanica, laser insect control

Controlling insect pests still relies on the extensive usage of generic and established methods, such as pesticides, which utilise broad spectrum chemicals or toxins persisting in the environment and targeting non-pest insect species. Therefore, more effective and environmental friendly approaches are needed to counteract these damaging effects. Since a laser can be remotely directed to neutralise undesirable targets, this approach could be highly promising for controlling insect pests in a selective and ecofriendly fashion. In this study, we present a laser system automated by machine vision for neutralising and influencing the behaviour of insect pests. By performing experiments on domiciliary cockroaches, Blattella germanica, we demonstrate that our approach enables the immediate and selective neutralisation of individual insects at a distance up to 1.2 m. We further show the possibility to deter cockroaches by training them not to hide under a dark shelter through aversive heat conditioning with a low power-laser. Parameters of our prototype system can readily be tuned for applications in various situations and on different pest species like mosquitoes, locusts, and caterpillars. The prospect of this study is to pursue the creation of a standalone, safe for the environment, compact, low-cost, and energy-efficient device system for pest control.

Introduction

Pest control is a major issue for the food industry and public health. Current agrochemical practices for controlling harmful insects are generally problematic because they lead to resistance and often impact non-targeted species. This is the case of the massive utilisation of non-specific insecticides for crop protection that largely contributes to pollinator declines [START_REF] Colin | Pesticide dosing must be guided by ecological principles[END_REF]. To overcome these problems, biocontrol solutions have been developed using natural predators or chemical traps releasing molecules involved in the CONTACT Ildar Rakhmatulin i.rakhmatulin@hw.ac.uk School of Engineering and Physical Sciences, Heriot-Watt University, Edinburgh, UK communication of targeted pests. However, even when these practices are possible, not only a detailed knowledge of the biology of species is required but also their impact has to be taken in into consideration prior any efficient implementation. Thus, a more generic approach that can be targeted to specific animal pests without damaging the environment should be developed.

Laser (amplification of light by means of stimulated emission) may provide an alternative approach for the selective neutralisation of unwanted targets, such as animal pests and weeds. For instance, [START_REF] Brown | Robotic laser scarecrows: a tool for controlling bird damage in sweet corn[END_REF] discussed the possibility of using a laser for birds to protect sweet corn fields. Furthermore, [START_REF] Xiong | An autonomous strawberry-harvesting robot: design, development, integration, and field evaluation[END_REF] tested a robot with a static laser for weeding during strawberry harvesting. However, a major drawback of this approach for large-scale deployment is that it requires specific types of equipments that are costly and complex to implement. Recently, we successfully tested the possibility of using a laser to kill mosquitoes (Rakhmatulin 2021), weeds [START_REF] Rakhmatulin | A concept of a compact and inexpensive device for controlling weeds with laser beams[END_REF]) and created a simulation program for the destruction of locusts and caterpillars (Rakhmatulin 2021). Despite in these previous studies an economical and energy-efficient laser prototype was developed, we envisioned major health and safety risks that could be triggered by the use of high laser power, such as eye damage and fire ignition, which prevented the large-scale expansion of our prototype. Therefore, further laser theory considerations were needed in order to develop robust and safe biocontrol approaches.

The idea of using a galvanometer (i.e., an electromechanical instrument for measuring electric current) was previously used for directing the laser in other applications. For instance, [START_REF] Hegna | Inexpensive 3-D laser scanner system based on a galvanometer scan head[END_REF] used a laser galvanometer to tilt the beam from a laser range finder along an object of interest to determine its geometric properties and therefore developing a more effective 3-D scanning system. In addition, [START_REF] Huang | Angle measurement technology based on magnetization vector for narrow space applications[END_REF] considered the magnetic properties of the rotor and concluded that the energy consumption of the motor can be reduced by reducing the total number of changes in the position of the mirrors per second. In this paper, we have tested the efficiency of our improved automated vision driven Laser prototype to with the German cockroach Blattella germanica (Linnaeus 1767), which is one of the major urban pest species worldwide [START_REF] Lihoreau | The social biology of domiciliary cockroaches: colony structure, kin recognition and collective decisions[END_REF]). These domiciliary cockroaches can live in populations of millions of individuals, potentially spoiling food, household, and electrical appliances [START_REF] Nasirian | Infestation of cockroaches (Insecta: Blattaria) in the human dwelling environments. A systematic review and meta-analysis[END_REF], but also being a serious health hazard triggering allergic reactions and the development of asthma. Despite various methods are used to control cockroaches, there is still no perfect solution [START_REF] Pan | Advances in biological control of the German cockroach, Blattella germanica (L.)[END_REF]. The most efficient approaches so far are mechanical (e.g., sticky traps) and chemicals (insecticidal gels and pastes). These methods have the disadvantage of having a limited catching range and therefore many individuals may not visit the trap areas. In addition, long-term chemical treatments may lead to problematic resistances.

We have improved our previous prototype by using galvanometer mirrors driven by neural networks algorithms to control the laser beam direction to efficiently target moving cockroaches in a controlled environment. This work demonstrates that our prototype is able to neutralise and deter cockroaches efficiently at specific distances depending on the laser power utilised. Thus, our approach (laser-targeted) could offer an effective, ecofriendly, and low-cost alternative to control the number of cockroaches and possibly other insects in different environments (i.e., domestic households, fields).

Methods

We have improved our previous approach (Rakhmatulin 2021) by developing the laser system automated by machine vision for neutralising and deterring moving insect pests. Guidance of the laser by machine vision allows for faster and more selective usage of the laser to locate objects more precisely, therefore decreasing associated risks of off-target laser exposure. In this device, the laser beam is controlled by galvanometer mirrors driven by a Jetson Nano single-board computer which uses deep learning algorithms (neural networks) for detecting moving objects and training.

Setup overview

We developed a laser device automated by machine vision (Fig. 1).

The single-board computer Jetson nano -1 (CPU Quad-core ARM Cortex-A57 MPCore processor, NVIDIA, USA) processes the digital signal from two cameras (IMX219, Sony, Japan) -2 and determines the position of the target insect -3 in the 3-D space. After calculations, the Jetson nano transmits the analog signal in the 0-5 V range to the board with an operational amplifier. This board converts the signal into a bipolar voltage (± 5 V), which powers the boards with a motor driver for the galvanometer -4 (Unbranded/Generic, style DMX Stage Ligh type: DHR814494, the protocol for laser control: ILDA DB25, AUCD, China). The galvanometer, with the help of mirrors, changes the direction of the laser -6 to shoot the target (see details in Supplementary materials). We used generally available equipment at a low-price range (all devices cost not more than 250 $US). Programming was made in python 3.7. The device algorithm is presented in Fig. 2.

Machine vision

Machine vision is the limiting element of the entire system since its accuracy depends on many factors: hardware, neural network model, dataset, etc. To reach high tracking accuracy, we used external focusing systems [START_REF] Rakhmatuliun | Machine vision for low-cost remote control of mosquitoes by power laser[END_REF]. We used camera IMX219 with an 8-megapixel matrix to allow for optimal detection of objects. To implement the neural network, we used Yolov4-tiny to search for 1 object in real-time video with a resolution of 416 × 416 pixels. We chose Yolo because it has high speed and accuracy of declaration [START_REF] Kuznetsova | YOLOv5 versus YOLOv3 for apple detection[END_REF]. Images for training the neural network were labelled manually using https://github.com/tzutalin/ labelImg. The resulting dataset is publicly available at https://www.kaggle. com/ildaron/tracking-a-cockroach-at-home. We used 1000 images that were prepared with different lighting to make the research more effective at any time of the day. We made 1000 images with cockroaches in our test box that we then manually labelled by marking the position of each cockroach with a red rectangle on each image (Fig. 3A). The detection of cockroaches in the red rectangles was made by YoloV4-tiny realised in the Darknet framework (https://pjreddie.com/darknet/) on Jetson nano (Fig. 3B). The speed of the neural network can be greatly improved. We tested our model on various frameworks and obtained the following results (Table 1). Laser operation [START_REF] Liu | Extension of continuous scanning laser Doppler vibrometry measurement for complex structures with curved surfaces[END_REF] described in detail the physics of the galvanometer operation process. The galvanometer scanner system consists of two orthogonal mirrors (X mirror and Y mirror) driven by two motors. Considering the voltages applied to the X and Y mirrors, the mirrors create certain angles of rotation. Both rotation angles are proportional to the input voltages. It is important to note that the position of the mirrors only needs to be changed 100 times instead of 20,000 times. The accuracy of the galvanometer is controlled by the use of iterative learning as proposed by [START_REF] Dai | Investigation of micron-sized fish-scale surface structures on tool steel surfaces using laser galvanometer scanning[END_REF], which achieves high speed, linear, and accurate bi-directional scanning for laser microscopy. In addition, the galvanometer is able to operate at different temperatures.

The positions of the mirrors were calculated as follows. For the tasks of stereo vision, we developed a stereo camera, and followed a detailed calibration as described in Rakhmatulin (2021b). Stereo vision permits the determination of the distance to the object along the z-axis. Then, the angle of the mirror rotation is calculated using the laws of optics (Fig. 5A). Once the object coordinates are determined then, the required angle of rotation for the mirror is calculated through the tangent of the angle α, which is the ratio of the opposite leg to the adjacent leg. The used galvanometer had a step width of 30°, but as it turned out we have only 20° (Fig. 4A-D).

The principle of the determination of the distance to the object and the dimensions of the device is shown in Fig. 5. The laser beam obeys all the optical laws of physics. Therefore, depending on the design of the galvanometer, the required angle of inclination of the mirror -α, can be calculated through the geometrical formulas. In our case, through the tangent of the angle α, where it is equal to the ratio of the opposing side -X(Y) (position calculated by deep learning) to the adjacent side -Z (calculated by stereo vision). The galvanometer is a fairly accurate device and can direct the laser to tens of metres with an accuracy of several centimetres (Belosludtsev 2021). In the general case, we experimentally established that the mechanical part of the device allows directing the laser to 10 m with an accuracy of up to 1 cm. To calibrate the system, we set the coordinates programmatically through the OpenCV library and checked whether the galvanometer directs the laser beam to the given point. Eight points were arbitrarily chosen for 1000 mm, 2000 mm, and 3000 mm (Ruler -Accuracy: 0.2 mm; Line Expansion, Tritec, Japan).

Cockroaches husbandry

We used German cockroaches Blattela germanica for testing the viability of our laser device for pest control. A population of 150 individuals composed of nymphs and adults (sex ratio 1:1) was obtained from a pet store (https://herasato-s.business.site/). We indiscriminately used nymphs and adults (♂ and ♀) during the experiments. Cockroaches were placed in the clear plastic box (height 8 cm × length 24 cm × depth 6 cm) without food or water for 24 hours before the experiments. We carried out the experiments in a room maintained at 24°C, under 65% humidity (temperature sensor with an accuracy 0.1 C and humidity sensor with accuracy of 1%, TDJstudio, Japan) and with the lighting of 150 lux (Digital Lux Metre BT-881D Illumination Metre, BTMETER, China). Depending on the experiment, the transparent box containing the cockroaches was placed on a table at a distance of either 600 mm or 1200 mm from the laser.

Laser neutralisation approach

We used three types of lasers:

-Power laser, 300 mW, 450 nm -Oxlasers, China; -Power laser, 1600 mW, 808 nm -Oxlasers, China; -Power laser, 100 mW, 660 nm -Oxlasers, China. To test the accuracy of our laser prototype in neutralising freely moving cockroaches in the box, we used a group of four cockroaches per box, as it is the limiting number of objects that can efficiently been tracked at high speed with the neural network algorithm. Five groups of cockroaches were used as controls (N = 20 cockroaches). In these control groups, cockroaches could move freely and interact in the box for 10 min. In the experimental groups (N = 15 groups, 60 cockroaches) cockroaches were exposed to the laser. We compared two laser power (300 mV and 1600 mW) and two distances between the laser and the box containing cockroaches (600 mm and 1200 mm). Different laser spot sizes (2 mm, 3 mm, 5 mm) for the 1600 mW were also tested to ascertain the efficacy of the laser intensity. We compared the area of action in the box of the cockroaches in the control and laser groups over time. We measured cockroach movements (travelled distance) using a library OpenCV cv2.TrackerCSRT_create, the laser detection accuracy, and efficiency of neutralisation.

Laser deterring approach

For deterring cockroaches from aggregating in a dark shelter upon light exposure, we used a laser with a lower power of 100 mW that triggers fleeing. The shelter was an opaque plastic plate (dimensions 500 × 300 × 10 mm) (see images in Appendix 2). The box containing cockroaches was placed at a distance of 300 mm from the laser. We ran experiments with five control groups (N = 20) that could move freely for 12 h. We also observed five experimental groups (N = 20), in which we shot cockroaches with a low-power laser every time they were detected hiding under the shelter. For measuring the deterring effect of the laser, a virtual region of interest (ROI) in the test box with the OpenCV library was created (see Fig. 6) and then we counted the number of times cockroaches entered the ROI area using the OpenCV function and compared data at the beginning of the experiments and after 12 h of laser exposure.

Results

Neutralising cockroaches

To test the efficacy of our laser system in neutralising freely moving cockroaches in an enclosed chamber (box), we used two different laser power settings, each targeting specimens at two different distances and measured cockroach movements, and neutralisation efficacy (Table 2; see methods).

On average, the cockroaches ran at a speed of 1.3 metres per second (4.8 km/h) with an error of no more than 10% (speed error is average error found in the movements of cockroaches, N = 20). Overall, cockroaches in the laser groups covered much more distance than cockroaches in the control groups as the latter were undisturbed from the thermal effect induced by the laser.

There was an increase in the movement speed of cockroaches targeted with the 300 mW laser in comparison with those shot with the 1.6 W laser. This speed increment in the lower laser group is because to neutralise the individuals generally the laser needs to shoot the target continuously for about 2-3 seconds (Stopwatch -8RDA55-002 Digital Stopwatch 055 Water Resistant Rainproof Black, Accuracy 0.01 s, Citizen CITIZEN, Japan) and at this lower laser power, cockroaches do not die instantly, but instead moved quickly outside the laser beam.

Examples of the thermal effects of the laser on cockroaches can be found in Fig. 7. Overall, the laser 1.6 W was more efficient for neutralising cockroaches than the laser 300 mW. Laser neutralisation was also significantly faster with 1.6 W than with 300 mW.

Next, we searched for the relationship between the laser distance and the laser spot diameters with the neutralisation efficacy. First, we found out that the higher the distance between the laser and the box, the longer it took for the lasers to neutralise the cockroaches. Detection and shot accuracy were also greatly reduced with distance from laser. Second, we tested the different diameters of laser spots for high 1.6 W laser at 300 mm to target. As it is shown in Fig. 8, the dose-effect curve for laser neutralisation of cockroaches for different laser spots indicates that the optimal laser spot size is 3 mm. Theoretically, reducing the size spot of the laser to 1 mm should be more efficient in neurtralisation, especially if the laser hits the cockroach's abdomen. However, the spot 1 mm is extremely difficult to implement experimentally. In addition, it is important to note that when a laser spot touches the most distal part of the leg (arolium an pulvilli) containing heat receptors, it triggers the activation of the escape response thus provoking only slight damage and sparing the individual from lethal exposure. Thus, although the spot size concentration directly affects the efficiency of the laser, our experiments show that for effective neutralisation a laser power of 1600 mW and a spot size of 3 mm must hit its body area, otherwise hitting the appendages triggers the escape response, increases speed and reduces neutralisation. Since we cannot control which part of the body is hit by the laser in each neutralisation attempt, and technical gaps preclude us for targeting the laser in a specific area, then further improvements are needed in our targeted laser prototype for effective neutralisation.

Cockroaches are most active at night whereas during daytime they rest in secluded places, such as shelters [START_REF] Lihoreau | The social biology of domiciliary cockroaches: colony structure, kin recognition and collective decisions[END_REF]. Therefore, in the presence of light, cockroaches have a strong tendency to aggregate under these dark shelters [START_REF] Halloy | Cockroaches to control self-organized choices[END_REF]. Having demonstrated the ability of the high-power laser to neutralise cockroaches, we tested whether our system could successfully deter cockroaches, by training them not to aggregate under a preferred dark shelter based on negative reinforcement with lowpower laser. The laser was located 300 mm to the experimental box containing cockroaches. The results are shown in the Table 3.

Cockroaches in the control group spent more time under the dark shelter than in other areas in the box throughout the experiments, whereas in the experimental laser group cockroaches showed a strikingly different trend. In the latter, cockroaches tended to aggregate under the shelter at the beginning of the experiment similar to the control ones. After 12 hours of laser treatment, these specimens were no longer in the shelter. Instead, they were resting in initially non-preferred areas under the light. Similar changes in behaviour (shelter avoidance) were observed when measuring first the number of times cockroaches entered under the shelters, with the experimental group showing a lower number of entries than the control one (Table 3), and second by measuring the time spent in the different areas of the box, in which the experimental group showed a cumulative time increase in non-preferred areas and a subsequent time reduction in shelter area (Fig. 9).

Interestingly, the laser-induced shelter avoidance seems to be effective from 8 hr onwards when cockroaches in the laser groups showed a steeply reduced ability to enter the shelter (Fig. 10). Such decline in ability was not observed in control groups. These differences cannot be explained by differences in the automated tracking accuracy, which was similar in control and laser groups throughout the experiments (Table 3). However, it is important to note that even do the data presented is an average of the results obtained, we have not controlled for the number of laser shots being received by each cockroach during the experiments. Despite this, these results indicate that our laser set-up is able to deter sheltering of cockroaches and therefore could be implemented for conditioning insect pest behaviours.

Discussion

In this paper, we have described the development of a safe, compact, lowcost, and energy-efficient laser device automated by machine vision, which is able to neutralise and influence the behaviour behaviour of insect pests in an environmentally friendly fashion. We have included a GitHub database with all technical details in open-source with GPL-3.0 licence. It is very important to note that the usage of this device must be restricted to areas where the possibility of the laser beam hitting another non-targeted living specimen is minimised. The aim of this work is to demonstrate the feasibility of using a laser to control insects pest, but we also understand that there exist safety issues of using lasers in insect control processes and they would require further study.

Here, we have improved a previous prototype by leveraging deep neural networks through the use of the Jetson nano, an on-pay computer-office suite, and its CUDA, a hardware-software architecture for parallel computing. We studied the effect of laser size and capability on the performance of a laser. We also significantly increased the working distance of the galvanometer. This device is a high-quality effective, with low energy consumption, destruction of one pest will cost a few joules.

By using B. germanica as a pest model, our work has shown that at higher laser power settings this device can selectively neutralise freely moving cockroaches at a distance beyond 1 m. In addition, in a low power setting, this laser device is able to precisely and persistently deploy heat at 300 mm distance inducing cockroach heat escape response and therefore influencing their shelter behaviour. Despite these findings, our program which numbered cockroaches periodically failed and did not allow us to calculate how many times each individual cockroach needed to be hit with the laser to avoid hiding. To resolve this issue, we could either use only one single cockroach per experiment or improve the tracker program. Further improvements in increasing the tracking range can be achieved by replacing the camera with a higher width and focus. At first with simple means, like the Haar cascade by OpenCV library, we can find an area with an object and then focus on this area using a telephoto lens and get an image for a neural network. Thus, our approach provides a plausible alternative solution to mechanical traps and chemicals (pesticides) for the selective neutralisation and deterring of not only cockroach populations but other insect pests as this system is readily tunable and could be applied for tracking and controlling other targets for instance to protect against mosquitoes, bees from predatory hornets, bees from ectoparasites.

Although this prototype is suitable for academic research, several factors must be considered before exploring the large-scale deployment of this technology. One of the main limiting factors is the danger of the laser beam hitting the eyes. The laser can enter a blood vessel and clog it, get into a blind spot where nerves from all over the eye go to the brain, burn out a line of 'pixels' and then the damaged retina can begin to flake off, and this is the path to complete and irreversible loss of vision [START_REF] Schirmacher | Eye protection for short and ultra-short pulsed laser systems Augenschutz für Kurz-und Ultrakurzpulslasereinrichtungen[END_REF]. The danger of lasers is considered based on whether it can cause damage before the eye reflexively blinks -and it is considered not too dangerous a power of 5 mW for visible radiation. As we have shown with cockroaches, 5 mW is not enough to control pests. To overcome this problem, we can develop additional security systems, such as human detection and audio sensors. But in any case, we are not able to make the installation 100% safe, since even a laser can be reflected and damage the eye of a person who is not in the field of view of the device and at a distant distance. Therefore, this technology should not be used at home (for a review of eye safety of laser see [START_REF] Sliney | Chapter 24 -eye safety of laser and light-based devices[END_REF].

However, this technology could still be useful in non-human-driven applications (robot-driven) or when high laser speed is not required, for example, for weed control. Our prototype can be tuned for this purpose by using a microcontroller instead of a computer, which will make the system more reliable and energy-efficient. We can also utilise the remote control of IP camera for stereo vision task and neural networks can be used to determine the distance [START_REF] Zhang | Dense-CNN: dense convolutional neural network for stereo matching using multiscale feature connection[END_REF]). As a processor, any low-cost singleboard computer such as RaspberryPI, BananaPI, Google Coral Edge TPU and ASUS Tinker Board can be incorporated. However, in all these board computers there is no possibility of using the GPU due to the hardware and software architecture of parallel computing -CUDA.

These devices can be used for other possible applications, such as real-time detection of objects with a bright background with OpenCV; or transfer images over the network and carry out calculations remotely. For either application out-of-the-box solutions, such as AWS IoT Greengrass Platform, which extends Amazon Web Services AWS capabilities to edge devices can be used to allow them to work locally with the data they create. Furthermore, Google Colab is also a service like Jupyter-Notebook that has been offering free access for a long time to GPU instances. Colab GPUs have been updated to the new NVIDIA T4 GPUs. This update unlocks new software packages, which means we can now experiment with RAPIDS for free on Colab. Based on CUDA-X AI, the RAPIDS suite of software libraries gives the freedom to run end-to-end data processing and analysis pipelines entirely on GPUs. In addition, despite the Jetson Nano has been used in our prototype, another more expensive devices such as Jetson TX2, Jetson Xavier NX, and Jetson AGX Xavier can also be considered. Other considerations to take into account are power supply, size, and periphery, which users can vary depending on the specifics of the project. Finally, while we used YoloV4 in this work through Keras, it is advisable to switch to YOLOv5 in PyTorch. YOLOv5-7, which conceptually gives a much better percentage of recognition on the COCO dataset than previous versions.

One of the advantages of our laser prototypes is the cost of installation which does not exceed several hundred dollars, and can even be reduced to $30 when using a stm32 series microcontroller instead of Jetsonnano with a CDMI protocol with an OpenCV library and also by replacing the fitted motor driver for less powerful ones with a mirror rotation angle of no more than 100 times per second. These improvements will allow us to create a 'pocket version' of the device, which could be easily fitted with other apparatus for the using this laser technology in the study of complex processes at the cellular and tissue levels. Finally, it has been proposed that ARM and FPGA processors for embedded laser marking controllers can operate outdoors even in harsh environmental conditions [START_REF] Wang | An embedded laser marking controller based on ARM and FPGA processors[END_REF]). In our prototype, a standard galvanometer was installed, but it can be upgraded for various specific purposes such as operating in outdoor settings.

Thus, this study is a proof of principle that our automated laser targeting prototype is an effective, and low-cost approach for controlling freely moving insects. Further improvements will allow the development of a more efficient device for targeting insect pests, weeds, and other desirable specimens in different environments.

Disclosure statement

No potential conflict of interest was reported by the authors.

Figure 1 .

 1 Figure 1. Summary diagram of the laser setup: 1 -transparent box containing cockroaches, 2 -Pi cameras, 3 -Jetson nano, 4 -laser, 5 -galvanometer, 6 -laser beam, L -distance between laser device and target.

Figure 2 .

 2 Figure 2. Algorithm of the laser operation for the neutralisation of cockroaches.

Figure 3 .

 3 Figure 3. Machine vision for cockroach detection: A, labelling process of cockroaches; B, an example of a neural network YoloV4 for detecting a cockroach.

Figure 4 .

 4 Figure 4. Maximum and minimum positions of galvanometer mirrors: A, lower position -35° for x mirror; B, upper position -55° for x mirror; C, lower position -0° for y mirror; D, upper position -25° for y mirror.

Figure 5 .

 5 Figure 5. The developed device (dimensions in mm): A, determination of the distance to the object, z and z coordinates when the mirror is located at an angle of 35°; B, side view: 1 -PI cameras, 2 -galvanometer, 3 -Jetson nano, 4 -adjusting the position to the object, 5 -laser device, 6 -power supply, 7 -galvanometer driver boards, 8 -analog conversion boards.

Figure 6 .

 6 Figure 6. The process of experiments for Cockroach training: A, ROI for neutralising laser and control group; B, laser group; C, demonstration of the operation of a powerful laser -100 mW.

Figure 8 .

 8 Figure 8. Dose-effect curve for laser 1600 mW control of cockroaches where 1 -laser spot 3 mm, 2 -laser spot 2 mm, 3 -laser spot 5 mm. Cockroaches were placed 300 mm to the laser device.

Figure 7 .

 7 Figure 7. Result of laser exposure during 0.5 sec: A, detected cockroaches; B, neutralised cockroaches by laser 300 mv; C, neutralised cockroaches by laser 1.6 W; D, cockroach box for the control and laser group.

Figure 9 .

 9 Figure 9. Heatmap of movement of cockroaches (average of 5 groups over 12 h). X-axisdistance in millimetres. Y-axis -time in seconds. A, laser groups; B, control groups. The black rectangle is region of interest.

Figure 10 .

 10 Figure 10. Number of times cockroaches entered the shelter (i.e., the region of interest: ROI).The X-axis is the time in hours. On the y-axis of attempted entries. Green line -laser group, blue line -control group.

Table 1 .

 1 Frames per second (FPS) for the Yolov4-tiny model when running on the Jetson Nano.

	Methods	FPS	Source
	Keras	4-5

https://github.com/jkjung-avt/tensorrt_demos Darknet 12-15 https://github.com/AlexeyAB/darknet Tensor RT 24-27 https://github.com/jkjung-avt/tensorrt_demos DeepStream 23-26 https://github.com/marcoslucianops/DeepStream-Yolo tkDNN 30-35 https://github.com/ceccocats/tkDNN

Table 2 .

 2 Technical parameters during neutralising cockroaches process with sample size -5.

Table 3 .

 3 Technical parameters during deterring cockroaches process.

						Tracking	Laser
		Sample	Time in shelter,	Cockroaches	Laser operation,	accuracy, %	precision, %
		size	min (Accuracy	entered the shelter	times (Accuracy	(by Yolov4-	(error -
	Group	(groups)	0.5 sec)	(Accuracy 5%)	0.5 sec)	tiny)	visually)
	Control	5	45	96	-	88	-
	group
	Laser	5	2	45	80	89	85
	group


Valerii Myndrul

Emerson Coy

Mikhael Bechelany

Igor Iatsunskyi
email: yatsunskiy@gmail.com

Photoluminescence label-free Immunosensor for the Detection of Aflatoxin B1 using 1D ZnO/polyacrylonitrile Nanofibers

Keywords: ZnO, immunosensor, detection, Aflatoxin B1, photoluminescence

The precise and rapid detection of hazardous molecules, microorganisms, pollutants, and toxins currently remains a global challenge. Aflatoxin B1 (AFB1) is a toxic and dangerous product of fungi that considered as cancerogenic, mutagenic, and immunosuppressive for humans and animals.

Therefore, the screening of AFB1 in food and beverages plays an important role in preventing foodborne illnesses. In this study, AFB1 molecules were detected in a microfluidic device with integrated polyacrylonitrile/zinc oxide (PAN/ZnO) nanofibers fabricated via a combination of the electrospinning, and atomic layer deposition (ALD) techniques. The structural and optical analyses of PAN/ZnO nanofibers were performed and samples with the most suitable properties were utilized for AFB1 detection. In order to obtain the biorecognition layer toward AFB1, PAN/ZnO samples were modified by (3-Aminopropyl)triethoxysilane (APTES), and glutaraldehyde (GA), bovine serum albumin (BSA) and monoclonal antibodies (Anti-AFB1). Subsequently, photoluminescence (PL)-based immunosensor was integrated into a microfluidic cell and tested for AFB1 detection. The mechanism of PL changes caused by AFB1 & Anti-AFB1 complex formation was analyzed and developed. The proposed approach enables the detection of AFB1 with a lowest concentration (LOD) of about 39 pg/ml, while the sensitivity range was evaluated as 0.1-20 ng/ml. The obtained values of LOD and sensitivity, as well as the simplicity of the detection method, make this approach a prospect for the further application.

Introduction

Mycotoxins are dangerous secondary metabolites produced by some organisms from the kingdom fungi. Generally, they can be released to the foodstuff during the fungi growth, especially in humid and warm conditions [START_REF] Chauhan | Recent advances in mycotoxins detection[END_REF][START_REF]Fungi and mycotoxins in grains: Implication for stored roducts research[END_REF]. Moreover, they have been classified as possible carcinogens and immunosuppressive agents [START_REF] Rieswijk | Aflatoxin B1 induces persistent epigenomic effects in primary human hepatocytes associated with hepatocellular carcinoma[END_REF][START_REF] Marchese | Aflatoxin B1 and M1: Biological Properties and Their Involvement in Cancer Development[END_REF]. Therefore, precise control and detection of mycotoxins in human and animal rations can help to avoid their negative influence on the general health.

Despite the thorough monitoring of mycotoxin levels in food and beverages within the European Union, contaminated foodstuffs still have been delivered to the customers. Adegbeye et al. have reported on the current situation of foodstuff contamination by mycotoxins, and indeed it takes place worldwide, especially in the developing countries [START_REF] Adegbeye | Mycotoxin toxicity and residue in animal products: Prevalence, consumer exposure and reduction strategies -A review[END_REF]. Furthermore, Global Climate Change could promote the spread of mycotoxins in Europe [START_REF] Adegbeye | Mycotoxin toxicity and residue in animal products: Prevalence, consumer exposure and reduction strategies -A review[END_REF].

Among different mycotoxins, Aflatoxin B1 (AFB1) has been found to be one of the most foodcontaminating toxins [START_REF] Battilani | Aflatoxin B 1 contamination in maize in Europe increases due to climate change[END_REF]. Being in the human liver, AFB1 stimulates cellular metabolism to generate high levels of reactive oxygen species (ROS) and free radicals. Such conditions lead to cell death, hepatotoxicity and initiate human hepatocellular carcinoma [START_REF] Xu | Critical role of caveolin-1 in aflatoxin B1-induced hepatotoxicity via the regulation of oxidation and autophagy[END_REF]. Based on the mentioned above, it is important to develop a high-sensitive and simple approach for AFB1 detection.

Traditional approaches for AFB1 detection, such as chromatography methods, have a high sensitivity and specificity, but they require an expensive equipment and specially trained staff, which increase the costs of analysis [START_REF] Lee | A Rapid Aflatoxin B1 ELISA: Development and Validation with Reduced Matrix Effects for Peanuts, Corn, Pistachio, and Soybeans[END_REF][START_REF] Ammida | Detection of Aflatoxin B 1 in Barley: Comparative Study of Immunosensor and HPLC[END_REF]. Moreover, AFB1 detection usually requires additional secondary labeled antibodies that makes this approach more complicated and expensive [START_REF] Chauhan | Recent advances in mycotoxins detection[END_REF]. Due to the small size of AFB1 molecules, it can be even undetectable by the Surface Plasmon Resonance based approach (SPR), which is considered to be the most sensitive label-free techniques. In order to solve this problem the "weighting agents" such as bovine serum albumin (BSA) has been used [START_REF] Puiu | Significance testing and multivariate analysis of datasets from surface plasmon resonance and surface acoustic wave biosensors: Prediction and assay validation for surface binding of large analytes[END_REF]. However, BSA weighting agents can adversely affect detection selectivity; therefore, the use of highly selective receptors (for example, nanobodies against AFB1) is preferred over the AFB1-BSA using [START_REF] Pan | Direct Immunoassay for Facile and Sensitive Detection of Small Molecule Aflatoxin B 1 based on Nanobody[END_REF]. Besides, a very limited number of studies represented a general mechanism for AFB1 detection that may clarify the behavior and response during the AFB1 binding. The wellstudied mechanism of detection will clarify the nature of the "detection platform-AFB1" interaction. Therefore, the major challenge is to develop a high-sensitive biosensing platform and/or a detection approach with a significantly reduced cost, when compared to traditional methods, and with a relative simplicity for application.

Among different types of biosensor transducers, the optical ones are small size, portable, and high precision devices. Currently, optical transducers have been successfully used in SPR, surfaceenhanced Raman spectroscopy (SERS), reflectance, and photoluminescence (PL) biosensors [START_REF] Myndrul | Nanosilicon-Based Composites for (Bio)sensing Applications: Current Status, Advantages, and Perspectives[END_REF].

Among optical transducers, PL -based biosensors are considered to be one of the most promising approaches, but stable, efficient and environment-friendly transducers are still required [START_REF] Han | Harnessing Photoluminescent Properties of Carbon Nitride Nanosheets in a Hierarchical Matrix[END_REF]. The change in the PL signal (e.g. relative PL intensity, the shape of PL curve) of semiconductors, as a function of the analyte concentration, can be used as an indicator for the detection of target molecules by the probe. The PL of semiconductors is very sensitive to small modifications of their surface (e.g. absorption of molecules on the surface) that enables to distinguish analyte concentration changes [START_REF] Myndrul | Porous silicon based photoluminescence immunosensor for rapid and highly-sensitive detection of Ochratoxin A[END_REF][START_REF] Myndrul | Gold coated porous silicon nanocomposite as a substrate for photoluminescence-based immunosensor suitable for the determination of Aflatoxin B1[END_REF][START_REF] Tereshchenko | ZnO films formed by atomic layer deposition as an optical biosensor platform for the detection of Grapevine virus A-type proteins[END_REF][START_REF] Viter | Analytical, thermodynamical and kinetic characteristics of photoluminescence immunosensor for the determination of Ochratoxin A[END_REF][START_REF] Hariharan | Band bending effect induced non-enzymatic highly sensitive glucose sensing in ZnO nanoparticles[END_REF][START_REF] Politi | Versatile synthesis of ZnO nanowires for quantitative optical sensing of molecular biorecognition[END_REF][START_REF] Tamashevski | Zinc oxide nanorod based immunosensing platform for the determination of human leukemic cells[END_REF].

Nanostructured zinc oxide (ZnO) is the one of most attractive materials for PL biosensors due to high active surface area, strong room-temperature (RT) PL in the UV/VIS range [START_REF] Tereshchenko | Optical biosensors based on ZnO nanostructures: advantages and perspectives[END_REF], and high isoelectric point/IEP (pH=9) suitable for the direct immobilization of low IEP acidic proteins or DNA via electrostatic interaction [START_REF] Zhang | Synthesis, Characterization, and Applications of ZnO Nanowires[END_REF]. ZnObased PL biosensors have been successfully applied for the detection of Salmonella [START_REF] Viter | Application of Room Temperature Photoluminescence From ZnO Nanorods for Salmonella Detection[END_REF], Ochratoxin A [START_REF] Viter | Analytical, thermodynamical and kinetic characteristics of photoluminescence immunosensor for the determination of Ochratoxin A[END_REF], and for the protein-protein biorecognition, etc. [START_REF] Politi | Versatile synthesis of ZnO nanowires for quantitative optical sensing of molecular biorecognition[END_REF][START_REF] Tereshchenko | Optical biosensors based on ZnO nanostructures: advantages and perspectives[END_REF]. Recent discoveries show that the morphology and structural properties of ZnO are crucial for the efficient biosensor performance [START_REF] Liu | Effects of nanoparticle size and cell type on high sensitivity cell detection using a localized surface plasmon resonance biosensor[END_REF][START_REF] Sang | Fluorescence enhancement and multiple protein detection in ZnO nanostructure microfluidic devices[END_REF]. The comparison analysis of the ZnO surface topography (nanoparticles (NPs), nanorods (NRs), nanosheets (NSs) and nanobeams (NBs)) on the protein adsorption process showed that 1D ZnO nanostructures provided a higher number of surface adsorption sites [START_REF] Liu | Effects of nanoparticle size and cell type on high sensitivity cell detection using a localized surface plasmon resonance biosensor[END_REF][START_REF] Sang | Fluorescence enhancement and multiple protein detection in ZnO nanostructure microfluidic devices[END_REF]. Thus, to enhance the sensitivity of ZnO based biosensors, a high surfaceto-volume ratio, such as the one present in a 1D structure, is needed.

Recently, it was proposed a novel approach to produce 1D ZnO nanostructures with a high surface architecture. This approach is based on the combination of two experimental techniques:

electrospinning and atomic layer deposition (ALD) [START_REF] Iatsunskyi | Tailoring of the electronic properties of ZnO-polyacrylonitrile nanofibers: Experiment and theory[END_REF][START_REF] Viter | Tuning of ZnO 1D nanostructures by atomic layer deposition and electrospinning for optical gas sensor applications[END_REF]. Electrospinning is a low-cost powerful technique, which can produce 1D organic or polymer nanofibers [START_REF] Barhoum | Nanofibers as newgeneration materials: From spinning and nano-spinning fabrication techniques to emerging applications[END_REF]. Electrospinning deposited 1D organic nanofibers, such as collagen, polyacrylonitrile (PAN), polylactic acid (PLA), gelatin, collagen, hyaluronic acid (HA) are widely used in tissue engineering and medicine as 3D scaffolds for cell growing [START_REF] Nagarajan | Design of Boron Nitride/Gelatin Electrospun Nanofibers for Bone Tissue Engineering[END_REF]. At the same time, these nanofibers can be a template for PL biosensors via ALD coatings with a photonic material (e.g. ZnO based coatings). It is known that, ALD is one of the most versatile methods for fabrication of ZnO nanostructures [START_REF] Graniel | Atomic layer deposition for biosensing applications[END_REF]. It does not depend on the substrate geometry and can be applied for both planar samples, and porous media at relatively low temperatures [START_REF] Pavlenko | Enhancement of optical and mechanical properties of Si nanopillars by ALD TiO 2 coating[END_REF][START_REF] Weber | Atomic Layer Deposition for Membranes: Basics, Challenges, and Opportunities[END_REF]. This method provides a conformal coating of the substrate and allows the control of thickness and chemical composition of the deposited layers. In recent works, it was also demonstrated that 1D PAN/ZnO nanofibers produced by this approach can be used as an effective PL biosensor for volatile organic compounds (VOC) [START_REF] Viter | Tuning of ZnO 1D nanostructures by atomic layer deposition and electrospinning for optical gas sensor applications[END_REF]. However, there are still several questions need to be solved The quartz microfluidic cell (useable optic range: 170 -2700 nm, v = 600 microliters, w = 8 mm, d = 2 mm, h = 40 mm) was purchased from Starna Cells. The diameter of the inlet and outlet tubes was 0.9 mm (inner diameter: 0.36 mm).

PAN fiber fabrication

Polyacrylonitrile (10 wt% PAN) was dissolved in DMF. The polymer solution was kept under stirring for 1 h with the following heating in an oil bath at 80 °C for 10 min. A home-made electrospinning machine with HPx 600 605 generator (physical instruments) and a KDS 100 syringe pump was used for the electrospinning deposition process. The solution was electrospun under an applied voltage of 25 kV with a flow rate of 3 mLh -1 using a 0.7 mm diameter syringe (connected to the positive output of the generator) in ambient air atmosphere. The collector, made of aluminum foil was fixed at the distance of 25 cm from the tip of the syringe and was connected to the negative output of the generator. The liquid was extruded from the spinneret to produce a pendant droplet that followed the Taylor cone formation due to the electrostatic repulsion among the surface charges upon electrification. The charged jet underwent stretching and thinning under the whipping instability and solidifies quickly into a fiber with tailored diameter.

ALD of ZnO

ZnO thin layers were deposited over the PAN nanofibers by a home-made ALD set-up at 100 °C and sequential exposures to diethyl zinc (DEZ) and deionized water, separated by a purge with dry Argon (flow rate of 100 sccm). The deposition protocol included the following steps: i) 0. Cu lamp (λ= 1.5418 Å). The Fourier-transform infrared (FTIR) spectra were obtained with the Jasco FT/IR 4700 -Fourier Transform Infrared Spectrometer. Photoluminescence was generated by a He-Cd laser (325 nm) and the emission spectra were recorded in the range from 360 to 800 nm by Ocean Optics Spectrometer USB4000. Two-photon laser fluorescence confocal microscopy (Zeiss LSM 780, the Coherent Chameleon laser with an excitation wavelength of 700 nm) was used to study the real-time PL during AFB1 adsorption.

The evaluation of PL signal of immunosensor

To prepare the biorecognition layer, the immobilization of antibodies toward AFB1 (anti-AFB1) was accomplished by the protocol described in the reference [START_REF] Myndrul | Porous silicon based photoluminescence immunosensor for rapid and highly-sensitive detection of Ochratoxin A[END_REF]. Briefly, the PAN/ZnO20nm samples were functionalized by APTES, and then, after GA activation, anti-AFB1were conjugated to the surface. Finally, the Bovine BSA PBS solution was added to block the remaining active sites and to improve the selectivity of the biosensor. As a result, PAN/ZnO20nm/APTES/GA/Anti-AFB1 structure was formed.

It also was supposed to add the Protein A (Prot.A) during the functionalization process to achieve oriented Anti-AFB1 immobilization, however, this step does not lead to the correct PAN/ZnO20nm/APTES/GA/Prot.A/Anti-AFB1 assembly. The possible reason for the incorrect assembly can be associated with the weak binding affinity of Prot.A to anti-AFB1 antibodies [START_REF] Hober | Protein A chromatography for antibody purification[END_REF].

Analytical characterization of the biosensor based on PAN/ZnO20nm/APTES/GA/Anti-AFB1 structures was performed in a microfluidic cell (Fig. 1 a,b) with the analyte flow rate about 37 ml/min. The cell was equipped with an inlet and outlet for analyte infusion. PL was excited with He-Cd (λ = 325 nm) and collected by optical fiber spectrometer using multimode optical fibers equipped with semispherical lenses. An output laser power was around 1-2 mW. Before measurements, 600 microliters of buffer solution were pumped through the cell by using a peristaltic pump. The PL spectra of the sample were collected every 10 s. The sample was stored in a buffer solution until the PL signal reached equilibrium. Then, 600 microliters of various AFB1 concentrations were subsequently infused to the cell via pumping.

Results and discussion

Structural and optical properties

In order to investigate the structure, surface morphology and optical properties of fabricated PAN/ZnO nanofibers with different ZnO thicknesses, SEM, TEM, XRD, EDX, and PL analysis were performed. Figure 2 shows SEM images of PAN/ZnO nanocomposites with different numbers of ALD cycles (25 to 250) corresponding to different layer thicknesses. It was confirmed that applying both techniques one was able to produce PAN/ZnO nanofibers with tuned structural parameters and optical properties [START_REF] Iatsunskyi | Tailoring of the electronic properties of ZnO-polyacrylonitrile nanofibers: Experiment and theory[END_REF]. Figures 2 (a-c) indicate the solid "spaghetti-like" morphology with an average fiber diameter of 500 nm. Figures 2 (d-f) show the crystalline structure of ZnO layers with the visually evaluated crystallites with the size around 15-30 nm. Moreover, In order to confirm the ZnO conformal layer TEM experiments were conducted. Figure 3 To confirm the crystalline phase of the obtained PAN/ZnO nanofibers, XRD analysis has been also performed (Fig. 4 a). The peaks at 2θ = 31.74° (001), 2θ = 34.42° (002), 2θ = 36.22° (101), and 2θ = 47.53° (102) confirm ZnO wurtzite structure [START_REF] Viter | Tuning of ZnO 1D nanostructures by atomic layer deposition and electrospinning for optical gas sensor applications[END_REF]. The XRD peak at 2θ = 17° directly corresponds to PAN fiber [START_REF] Viter | Tuning of ZnO 1D nanostructures by atomic layer deposition and electrospinning for optical gas sensor applications[END_REF]. It is clearly seen that the crystallinity of the PAN/ZnO5nm structure is weak and the ZnO coverage which is attributed to the small amount of material, the miss orientation of the fibers towards the bragg-brentano condition and the polycrystallinity of the films. [START_REF] Libera | Conformal ZnO coatings on high surface area silica gel using atomic layer deposition[END_REF]. With the growth of the ZnO layer from 10 to 50 nm, the crystallinity of the structure is increasing, which allows to estimate the average size of ZnO nanocrystallites the Debye-Scherrer's equation [START_REF] Patterson | The Scherrer Formula for X-Ray Particle Size Determination[END_REF]

𝐷 = 0,9•𝜆 𝛽•cos (𝜃) , (1)
where β, θ, and λ are full width of half maximum, diffraction angle, and x-ray wavelength (λ = 0.154 nm), respectively. The calculated average size of ZnO nanocrystallites was about 9 ± 2 nm for all samples what in agreement with the TEM measurements. The PL spectra of PAN/ZnO nanofibers are shown in Figure 5 a. The narrow peak in the ultraviolet (UV) region (3755 nm) corresponds to the near band emission (NBE) [START_REF] Viter | Tuning of ZnO 1D nanostructures by atomic layer deposition and electrospinning for optical gas sensor applications[END_REF][START_REF] Damberga | Photoluminescence Study of Defects in ZnO-Coated Polyacrylonitrile Nanofibers[END_REF]. This band can also be interpreted by the emission (3.34 eV) of free excitons (FE) in the bandgap of ZnO nanocrystallites [START_REF] Viter | Application of Room Temperature Photoluminescence From ZnO Nanorods for Salmonella Detection[END_REF]. The broad peak in the visible range around 565 nm corresponds to the deep defect levels (DLE) such as zinc vacancies (Zni ++ ), single (Vo + ) and double (Vo ++ ) ionized oxygen vacancies, neutral oxygen vacancies (Vo), and oxygen interstitials (Oi) [START_REF] Baitimirova | Tuning of Structural and Optical Properties of Graphene/ZnO Nanolaminates[END_REF]. The deconvolution of DLE emission (Fig. Taking into account the findings from PL analysis, and to achieve a stable, reliable, and repeatable results for the developed PL biosensing platform, it was decided to use PAN/ZnO nanofibers with an oxide layer of 20 nm that is capable of providing the conformal coverage over the PAN, relatively high PL emission and the stable biorecognition layer.

The evaluation of PAN/ZnO PL-based immunosensor

Biofunctionalization

It is important for biosensors to detect selectively the target molecules while the remaining molecules must not affect the sensor's response. In order to achieve the selective adsorption of AFB1 to the PAN/ZnO surface, the bioselective (biorecognition) layer containing Anti-AFB1 was formed along the step-by-step biofunctionalization process (Fig. 6 To confirm the biofunctionalization of PAN/ZnO20nm nanofibers by APTES, GA, and Anti-AFB1 a series of FTIR measurements were performed (Fig. 6 b). The peak at 480 cm -1 is attributed to an electronic transition to deep surface states that originated from defects (oxygen vacancies) in the ZnO layer [START_REF] Lee | Visible light-sensitive APTESbound ZnO nanowire toward a potent nanoinjector sensing biomolecules in a living cell[END_REF].The significant changes have appeared in the FTIR spectrum when the silanization process is done. Peaks from the Si-O-C (777 cm -1 ), Si-O-Si (1078 cm -1 ), NH2 (1529 cm -1 ), NH3

(1596 cm -1 ), O-Si-H (2341 cm -1 ), and, CH2 (2878 -2931 cm -1 ) and CH3 (2977 cm -1 ) groups indicate the formation of APTES layer. The GA-activation of APTES modified nanofibers results in appearing of peaks at 1635 -1690 cm -1 which can be attributed to the C=O or/and C=C stretchings of GA molecule [START_REF] Gunda | Optimization and characterization of biomolecule immobilization on silicon substrates using (3-aminopropyl)triethoxysilane (APTES) and glutaraldehyde linker[END_REF]. Afterward, Anti-AFB1 were added to form layer selective to AFB1

molecules. The aldehyde groups on the surface react with amino groups of antibodies and proteins for covalent immobilization by an amide bond formation. The peaks in the range of 1226 -1666 cm - 1 can be associated with the amide I (1642-1660 cm -1 ), amide II (1450-1535 cm -1 ) and amide III (1226-1233 cm -1 ) bonds. Additionally, one can assume that peaks in the range of 3005-3730 cm -1 correspond to the amide A and amide B bonds, on the other hand, such a broad peak can appear due to the O-H stretching.

Aflatoxin B1 PL detection

Quantitative analysis of the interactions between PAN/ZnO20nm/APTES/GA/Anti-AFB1 structure and AFB1 molecules was performed in the concentration range of 0.1-100 ng/ml (target AFB1). To simplify the calculation of the main biosensors parameters (LOD, sensitivity range, etc.), PL signals of PAN/ZnO20nm nanocomposite were normalized as follows:

𝐼 𝐶𝑛 = 𝐼 𝐶 𝐼 𝐶𝑚𝑎𝑥 , (2)
where 𝐼 𝐶𝑛 is the normalized PL signal for each concentration as shown in the Figure 7, 𝐼 𝐶 is the non-normalized PL signal for each AFB1 concentration, and 𝐼 𝐶𝑚𝑎𝑥maximum PL signal (CAFB1 = 118.1 ng/ml).

where C is the AFB1 concentration.

Considering the equation (3), the LOD was calculated using the formula:

𝐿𝑂𝐷 = 3.3 • √𝑛 • 𝜎/𝑏 , ( 4
)
where σ is the standard deviation of the negative control at small concentrations, nnumber of tests, b is the slope of the curve, extracted from equation (3

The mechanism of PL biosensing

To gain further insights regarding the mechanisms of PL detection, we decided to develop a model that could explain the PL changes in semiconductors during the adsorption of molecules. According to the theory of PL in semiconductors, the changes of PL signal can be associated with the bandgap modification (e.g. band bending) under additional external forces that could be caused by the adsorption of the proteins which will affect the surface band bending. Those forces mostly initiate the surface potential 𝜓 𝑠 changes resulting in expanding or constriction of the space charge region (SCR) and/or energy band bending. The existence of a surface potential barrier that needs to be overcome by the photogenerated carriers and the value of SCR strongly affects the recombination processes, and as a consequence, the PL in semiconductors.

Being in liquids/electrolytes, semiconductor experience a significant influence of ions and the surface potential 𝜓 𝑠 depends on the total charge of all ions at the defined distance from the surface (Debye length) [START_REF] Tereshchenko | Interaction mechanism between TiO 2 nanostructures and bovine leukemia virus proteins in photoluminescence-based immunosensors[END_REF]. Besides, if the liquid contains macromolecules, such as proteins (antibodies, antigens, etc.), they will induce an additional effect on 𝜑 𝐷 . It means that the PL signal is defined by the 𝜓 𝑠 , which is determined by the total electrostatic potential of both ions in the liquid and protein charges near the semiconductor surface.

There are two hypotheses of the electrostatic influence of protein charges which penetrate the diffuse layer (Helmholtz layer) to the semiconductor interface [START_REF] Schasfoort | Possibilities and limitations of direct detection of protein charges by means of an immunological field-effect transistor[END_REF]. The first hypothesis is based on the Debye model, which defines the thickness of diffuse-charged layers by the distance (Debye length) where the electrostatic field has dropped to 1/𝑒 of its initial value. However, the Debye length in a physiological salt solution is limited to be around 0.8 nm [START_REF] Schasfoort | Possibilities and limitations of direct detection of protein charges by means of an immunological field-effect transistor[END_REF]. It means only that the charge density changes comparable to the value of a Debye length can be detected. As we deal with proteins, such as antibodies and antigens, with an average size (> 10𝑛𝑚) much bigger than the Debye length, one may conclude that their charges will be "not seen" for the detection platform [START_REF] Schasfoort | Possibilities and limitations of direct detection of protein charges by means of an immunological field-effect transistor[END_REF].

The second hypothesis can be described by the so-called Donnan model [START_REF] Bergveld | A critical evaluation of direct electrical protein detection methods[END_REF]. This model enables to consider the influence of charge density changes caused by antibodies and antigens at the distances comparable to the Debye length. The main idea of this model based on the assumption that there are two phases (s and m) at the interface semiconductor/electrolyte, in which ions can freely diffuse to the surface until the electrostatic equilibrium state is achieved. Phases m and s represent the protein layer on the semiconductor surface and the volume of the electrolyte, respectively. The total electrostatic potential of the surface 𝜑 𝐷 caused by ions and proteins in the Helmholtz layer (phase m) can be described by the equation [START_REF] Haustein | Analytical Model To Describe the Effect of Polyethylene Glycol on Ionic Screening of Analyte Charges in Transistor-Based Immunosensing[END_REF]:

𝜑 𝐷 = 𝑅𝑇 𝐹 ln ( 𝐶 𝑝+ +√4𝐶 𝑠 2 +𝐶 𝑝+ 2 2𝐶 𝑠 ), (5)
where 𝑅, 𝑇, 𝐹 are the universal gas constant, temperature, and Faraday constant respectively, while 𝐶 𝑝+ and 𝐶 𝑠 are the concentration of protein-fixed positive charges and the ion concentrations in phase m [START_REF] Schasfoort | Possibilities and limitations of direct detection of protein charges by means of an immunological field-effect transistor[END_REF]. As seen from the equation ( 5), the Donnan potential (potential arises between two phases) mostly depends on the ion equilibrium concentrations in phase m. It worth to mention that there is a smooth transition between the 𝜑 𝐷 and the surface potential (𝜓 𝑠 ) of semiconductor [START_REF] Ohshima | Donnan potential and surface potential of a charged membrane[END_REF],

which means that the changes of 𝜑 𝐷 caused by ions transfer between m and s phases will influence on the surface potential 𝜓 𝑠 (𝜑 𝐷 ). Taking into account that the value of SCR is proportional to the square root of 𝜓 𝑠 , it becomes obvious that the changes of 𝜑 𝐷 will affect the SCR as well [START_REF] Zhang | Band bending in semiconductors: Chemical and physical consequences at surfaces and interfaces[END_REF].

One may consider two different cases: (i) the surface potential of 𝜓 𝑠1 (𝜑 𝐷1 ) for the surface functionalized by antibodies, and (ii) the surface potential of 𝜓 𝑠2 (𝜑 𝐷2 ) for the surface with antibody-antigen complexes. While the n-type semiconductor (e.g. ZnO) possesses the positive 𝜓 𝑠 (bending up), the binding of the positively-charged proteins (e.g. AFB1) induces a downward bandbending and decreasing of 𝜓 𝑠 (𝜓 𝑠1 (𝜑 𝐷1 ) > 𝜓 𝑠2 (𝜑 𝐷2 )) due to the ion concentrations change in the phase m [START_REF] Yang | Direct electrical detection of antigenantibody binding on diamond and silicon substrates using electrical impedance spectroscopy[END_REF]. Such antibody-antigen interaction will promote decreasing of the semiconductor 𝜓 𝑠 and the value of SCR. This will promote an increase of charge carrier concentration and, as a consequence, it will enhance the radiative recombination from the bulk defect states. However, the radiative recombination of photogenerated holes and electrons will take place only when the defect level energy lies below the Fermi level (EF) of ZnO. This condition will only be met for the bulk region called here the PL active region (Fig. 8). It is clearly seen that the width of the PL active region is modulated by the value of SCR and the𝜓 𝑠 , which values strongly depend on the concentration of adsorbed AFB1 molecules and the ion concentrations in the Helmholtz layer. for PAN/ZnO20nm/APTES/GA/Anti-AFB1. The PL intensity is determined by radiative transitions 1→2→3 (Fig. 8). The expanding of SCR (increasing of 𝜓 𝑠 ) will subsequently lead to the constriction of the PL active region and it will decrease the probability of radiative transitions 1→2→3. On the other hand, the reducing of SCR will have an opposite effect and, as a result, increasing PL intensity. After positively charged AFB1 molecules interact with antibodies (Anti-AFB1), it should downward the band bending (Fig 8 b). This downward band bending is associated with the lower value of ZnO surface potential 𝜓 𝑠2 (𝜑 𝐷2 ) and it promotes constriction of the SCR to the value 𝑑 2 . Thus, the probability of radiative transitions 1→2→3 in the PL active region increases, while the probability of non-radiative transitions (transition 4) and the charge carriers separation (transition 5'-5'') becomes lower. This condition promotes increasing of PL intensity for PAN/ZnO20nm/APTES/GA/Anti-AFB1/BSA&AFB1 nanostructures after the adsorption of positively charged AFB1 molecules on the surface.

Kinetic and thermodynamic aspects

Kinetic and thermodynamic analysis may provide important information on biomolecular interactions between antibody and antigen. Moreover, kinetic analysis offers insights concerning the relationships between structure and biochemical activities. The basis of kinetic and thermodynamic analysis is adsorption isotherm interpretation, which allows to calculate some important biosensor parameters, such as adsorption affinity constant, Gibbs free energy change, and power coefficient. Biosensor responses vs various ABF1 concentrations were calculated using the formula [START_REF] Myndrul | Gold coated porous silicon nanocomposite as a substrate for photoluminescence-based immunosensor suitable for the determination of Aflatoxin B1[END_REF]:

𝑆(𝐶) = 𝐼 𝑒𝑞 (𝐶) -1, (6)
where 𝐼 𝑒𝑞 and C are the normalized PL signal value of the PAN/ZnO20nm/APTES/GA/Anti-AFB1 sample in steady state conditions and the value of AFB1 concentration, respectively.

Adsorption isotherm indicates a pseudo-first-order interaction between AFB1 and PAN/ZnO20nm/APTES/GA/Anti-AFB1 structure as shown in Figure 9 b. This type of interaction can be described by the first order kinetic equation (Langmuir equation) obtained from the fitting (dark blue curve) [START_REF] Azizian | Re-evaluation of the century-old Langmuir isotherm for modeling adsorption phenomena in solution[END_REF]:

𝑑𝑁 𝑑𝑡 = 𝑘 𝑎 • 𝐶 • (𝑁 𝑠 -𝑁) -𝑘 𝑑 • 𝑁, (7)
where 𝑁, 𝑘 𝑎 , 𝑘 𝑑 , 𝑁 𝑠 and 𝐶 are a number of adsorbed molecules, an association constant, a dissociation constant, a number of adsorption sites and the concentration, respectively. In this particular case, the number of adsorbed molecules has maximum value, while the sensitivity is highest. It means that those parameters are proportional 𝑁 𝑠 ~𝑆𝑚𝑎𝑥 , and 𝑁 is proportional to the biosensor sensitivity (𝑁~𝑆, where𝑆 < 𝑆 𝑚𝑎𝑥 ).

It should be noted, that after adding of AFB1 into the microfluidic cell, the PL intensity increases until its saturation, which indicates the steady-state conditions between PAN/ZnO20nm/APTES/GA/Anti-AFB1 and AFB1. Thus, the rate of AFB1 adsorption is equal to zero ( 𝑑𝑁 𝑑𝑡 = 0),and the equation ( 7) can be rewritten as follows:

𝑘 𝑎 • 𝐶 • (𝑆 𝑚𝑎𝑥 -𝑆) -𝑘 𝑑 • 𝑆 = 0. (8)
After some additional calculations, the Langmuir equation ( 8) is transformed to the equation ( 9), while fitting parameters are taken from the equation (10) (inset, Fig. 9 b):

𝑆 𝑆 𝑚𝑎𝑥 = 𝐾 𝐴 •𝐶 1+𝐾 𝐴 •𝐶 , (9)
𝑦 𝑎 = 𝑏•𝑥 𝑛 1+𝑏•𝑥 𝑛 , (10)
where

𝑏 = 𝐾 𝐴 = 𝑘 𝑎 𝑘 𝑑
, is the affinity constant, 𝑥 = 𝐶concentration, 𝑛 = 1 -𝑐 is the power coefficient (c-fitting parameter from the inset table of Fig. 9 b), 𝑦, 𝑎 are 𝑆 and 𝑆 𝑚𝑎𝑥 respectively.

The affinity dissociation constant 𝐾 𝐷 = 0.96 ± 0.11𝑛𝑔/𝑚𝑙 was calculated as the reversed value of 𝐾 𝐴 and allows one to estimate the change in Gibbs free energy (∆𝐺) of PAN/ZnO20nm/APTES/GA/Anti-AFB1 & AFB1 complex formation:

∆𝐺 = 𝑅𝑇 • 𝐿𝑛𝐾 𝐷 0 , (11)
where 𝑅and𝑇 are the universal gas constant and the absolute temperature, respectively. The value𝐾 𝐷 0 = 𝐾 𝐷 /𝐶, in this case, 𝐶 is the standard reference concentration of 1 M.

The obtained value of the change in Gibbs free energy ∆𝐺 = -44.6 ± 1.4𝑘𝐽/𝑚𝑜𝑙 indicates the thermodynamically favorable reaction of the chemical adsorption [START_REF] Baleviciute | Evaluation of theophylline imprinted polypyrrole film[END_REF] for the PAN/ZnO20nm/APTES/GA/Anti-AFB1&AFB1 complex formation [START_REF] Saadi | Promotion of clinoptilolite adsorption for azithromycin antibiotic by Tween 80 and Triton X-100 surface modifiers under batch and fixed-bed processes[END_REF]. One can conclude that a strong electrostatic chemical bonding occurs between the PAN/ZnO20nm/APTES/GA/Anti-AFB1 and AFB1 molecules. The calculated ∆G is in good agreement with the value obtained in our previous research [START_REF] Myndrul | Gold coated porous silicon nanocomposite as a substrate for photoluminescence-based immunosensor suitable for the determination of Aflatoxin B1[END_REF] and higher than recently reported for the AFB1 physisorbed onto the detection platform [START_REF] Haidukowski | Aflatoxin B1-Adsorbing Capability of Pleurotus eryngii Mycelium: Efficiency and Modeling of the Process[END_REF].

The calculated power coefficient 𝑛 = 0.95 ± 0.01 indicates a favorable sorption process (𝑛 < 1) of the analyte onto the PAN/ZnO20nm/APTES/GA/Anti-AFB1 structure [START_REF] Lim | Performance of composite mineral adsorbents for removing Cu, Cd, and Pb ions from polluted water[END_REF] and the fast diffusion of AFB1 molecules to the developed nanofibers structure [START_REF] Viter | Analytical, thermodynamical and kinetic characteristics of photoluminescence immunosensor for the determination of Ochratoxin A[END_REF]. Besides, such value of the power coefficient(0.5 < 𝑛 < 1) can be additionally explained by the partially negative cooperative adsorption [START_REF] Luo | Cooperative Adsorption of Proteins onto Hydroxyapatite[END_REF]. The negative cooperative adsorption indicates the decreasing of affinity while the molecule covalently binds with the binding site. Taking into account that the structure of antibodies assumed to be bivalent [START_REF] Eisen | Immune Tolerance and an Extracellular Regulatory Role for Bivalent Antibody[END_REF], because of V regions of the two heavy and light chains, it offers two identical antigen-binding sites [START_REF] Wang | Antibody Structure, Instability, and Formulation[END_REF]. Therefore, it can be supposed that binding affinity (capability)

of Anti-AFB1 toward AFB1 becomes lower after the first Anti-AFB1&AFB1 binding and tends to the zero value after the second Anti-AFB1&AFB1 binding.

Finally, the sensitivity of PAN/ZnO20nm/APTES/GA/Anti-AFB1 was calculated as the derivative of the sensor signal response 𝑆 to the natural logarithm of AFB1 concentration 𝐶 (Fig. 10 c). Analysis of the sensitivity indicates, that the PAN/ZnO20nm/APTES/GA/Anti-AFB1 biosensor shows the sensitivity towards AFB1 molecules in the range of 0.1 -20 ng/ml. However, the upper limit can achieve higher values than 20 ng/ml of AFB1 concentration, if more Anti-AFB1 would be immobilized on the PAN/ZnO20nm/APTES/GA structure.

All analytical parameters and kinetic constants of the PAN/ZnO20nm/APTES/GA/Anti-AFB1&AFB1 complex are presented in Table 2.

Microscopy visualization

In the final stage of the research, the two-photon PL microscopy was used to visualize immunosensor response during PAN/ZnO20nm/APTES/GA/Anti-AFB1&AFB1 complex formation.

Figures 10 (a,b) demonstrate the PL emission from PAN/ZnO20nm and PAN/ZnO20nm/APTES/GA/Anti-AFB1, respectively. It is clearly seen the more intense PL emission for the sample with immobilized antibodies that proves the mechanism provided in section 3.2.2.

This means that after immobilization of Anti-AFB1 to the surface of the PAN/ZnO20nm sample, the downward band-bending and decreasing of 𝜓 𝑠 lead to increasing of PL intensity. Besides, the uniform PL emission from PAN/ZnO20nm/APTES/GA/Anti-AFB1 nanofibers proves the conformal functionalization of the ZnO surface. Then, the probe of AFB1 with a concentration of 10 ng/ml was injected into the cell with the PAN/ZnO20nm/APTES/GA/Anti-AFB1 and the control sample.

The PL images/frames have been recorded every 5 min until signal saturation.

Conclusions

In conclusion, PAN/ZnO nanofibers prepared by electrospinning and ALD was successfully examined as a PL-based platform for AFB1 detection. The intensity of the PL emission of PAN/ZnO20nm modified by APTES/GA/Anti-AFB1 is seen to be dependent on the AFB1 concentration, evidencing an increase of PL with increasing concentration of the analyte.

PAN/ZnO20nm/APTES/GA/Anti-AFB1 samples were integrated into the microfluidic cell, which showed high sensitivity towards AFB1 molecules in the range of 0.1 -20 ng/ml, and the LOD was evaluated as 39 pg/ml. The immunosensor response time to the different AFB1 concentrations was in the range of 15-20 min. The calculated values of kinetic constants and thermodynamic parameters indicate favorable AFB1 adsorption to the PAN/ZnO20nm/APTES/GA/Anti-AFB1 immunosensor as well as high electrochemical interaction between immunosensor and AFB1 due to the Anti-AFB1&AFB1 complex formation. The results obtained by the two-photon PL microscopy confirm that the developed immunosensor is capable to detect AFB1 with a high signal-to-noise ratio and diminished non-specific adsorption. Besides, the model of semiconductoranalyte interaction and its effect on emission was proposed and analyzed. The obtained results indicate the suitability of our materials and detection approach to be employed in the fabrication of biosensing devices for probing other relevant analytes.

Figure 1 .

 1 Figure 1. (a) Photography of the experimental set-up, where (1) -microfluidic cell with tubes; (2) -AFB1 sample; (3) -peristaltic pump; (4) -AFB1 waste; (5) -laser; (6), (7) and (8) -system of mirrors and lens, (9) -light collector. (b) Scheme of the experimental set-up for the PLbased AFB1 detection on PAN/ZnO20nm/APTES/GA/Anti-AFB1 structure.

Figure 2 d

 2 Figure 2 d indicates the core-shell structure with a clear border between the core (PAN polymer) and the shell (ZnO crystalline layer).

Figure 2 .

 2 Figure 2. SEM images of PAN/ZnO nanofibers: (a-c) PAN/ZnO50 nm top-view with different magnifications; the core-shall structure of single nanofibers (thickness ~50 nm) (d); the crystalline structure of PAN/ZnO20 nm nanofibers (e-f).

  shows the TEM images of PAN/ZnO nanofibers: PAN/ZnO50nm (Fig.3a, b, d) and PAN/ZnO20 nm (Fig.3c, e, f). The TEM image (Fig.3 a) shows a uniform fiber with the conformal ZnO layer. TEM images (Fig.3 a-c) show the single fibers with an approximate diameter of 400-500 nm. Figures3 d-fshows the crystalline structure of the ZnO layer over PAN fiber with an average crystallites size of about 10-15 nm. Besides, Figure3f represents (101) lattice plane with the interplanar distance of 0.24 nm suggest the stabilization of the wurtzite phase of ZnO. High-resolution TEM proves the polycrystalline nature of produced ALD ZnO layers for all samples.

Figure 3 .

 3 Figure 3. TEM images of PAN/ZnO nanofibers: ZnO layer 20 nm (c, e, f); ZnO layer 50 nm (a, b, d).

  Furthermore, EDX mapping of a single PAN/ZnO nanofiber (Fig. 4 b) indicate the oxygen and zinc content and distribution on the ZnO shell, while the carbon content attributed the PAN fiber, remains at the fiber's core. Besides, this mapping confirms that Zn and O are homogeneously dispersed.

Figure 4 .

 4 Figure 4. XRD spectra of the obtained PAN/ZnO nanofibers (a) and EDX mapping of the single nanofiber with ZnO layer thickness 20 nm (b).

  5 b) reveals three general types of defects involved in the green-blue PL process: Vo + (2,45 eV), Vo ++ (2,23 eV), Oi (2 eV) (inset Fig. 5 b)[START_REF] Damberga | Photoluminescence Study of Defects in ZnO-Coated Polyacrylonitrile Nanofibers[END_REF][START_REF] Garimella | One-Step Synthesized ZnO np-Based Optical Sensors for Detection of Aldicarb via a Photoinduced Electron Transfer Route[END_REF]. The peak around 785 nm attributes to the residual PL emission of PAN nanofibers. The decrease of PL in the visible region upon increasing the thickness of the ZnO layer can be explained by the improvement of the crystallinity of semiconductor and thus, the reduction of defect concentration[START_REF] Moore | Affect of film thickness on the blue photoluminescence from ZnO[END_REF]. However, the low UV emission and high DLE to NBE ratio indicate the high defects concentration within the ZnO structure[START_REF] Viter | Application of Room Temperature Photoluminescence From ZnO Nanorods for Salmonella Detection[END_REF][START_REF] Damberga | Photoluminescence Study of Defects in ZnO-Coated Polyacrylonitrile Nanofibers[END_REF].

Figure 5 .

 5 Figure 5. PL spectra of PAN/ZnO nanofibers with different thicknesses of ZnO layer (a) and (b) PL deconvolution with Gaussian function; inset -possible optical transitions and their energies in ZnO nanostructures, where free excitons (FE), single ionized oxygen vacancies (Vo + ), double ionized oxygen vacancies (Vo ++ ), and oxygen interstitials (Oi).

  a). The blank PAN/ZnO20nm nanofibers during the silanization (APTES treatment) process and GA activation were prepared for conjugation with the Anti-AFB1. The detailed biofunctionalization protocol was as follows: i) to achieve the thin APTES layer which acts as a coupling agent between the PAN/ZnO20nm and Anti-AFB1, nanofibers were treated by 10 μl of 2% APTES solution in Ethanol (99.9%) at room temperature (RT) for 10 min. Then the sample was gently washed with Ethanol (99.9%) with the following drying on a hot plate at 85 °C for 1 hour. ii) At the next step, PAN/ZnO20nm/APTES samples were immersed in a 1% GA water solution (at RT for 1 h) to activate APTES modified surface. Subsequently, the PAN/ZnO/APTES/GA was rinsed with DI water to avoid non-specific adsorption of the Anti-AFB1. iii) The GA-activated surface was then reacted with 10 μl of 50 μg/ml Anti-AFB1 solution in PBS buffer (pH 7.4) at RT for 30 min to form a bioselective layer of anti-AFB1. Then, PAN/ZnO/APTES/GA/Anti-AFB1 was rinsed with PBS to wash out nonconjugated antibodies. iv) 10 μl of 5μg/ml of BSA was added to block the remaining active sites that enable adsorb proteins. v) As a result, PAN/ZnO20nm/APTES/GA/Anti-AFB1 was formed.

Figure 6 .

 6 Figure 6. Step by step biofunctionalization process (a) and (b) FTIR spectra of the following biofunctionalization stages: dark bluebulk PAN/ZnO20nm sample; bright blue line -PAN/ZnO20 nm/APTES; green -PAN/ZnO20nm/APTES/GA; red line -PAN/ZnO20nm/APTES/GA/Anti-AFB1.

Figure 7 .

 7 Figure 7. Photoluminescence spectra of PAN/ZnO20nm/APTES/GA/Anti-AFB1 biosensor after incubation in different AFB1 concentrations (from bottom to top) containing samples after the reaching of steady state conditions; (b) the response curve, measured at PL peak position (λ = 565 nm).

Figure 7 a

 7 Figure 7 a shows that the PL signal increases while the AFB1 molecules bind to the PAN/ZnO20nm/APTES/GA/Anti-AFB1 surface. One may observe the 25 % increasing of the PL intensity for the concentration of AFB1 around 100 ng/ml. The saturation of the analytical PL signal is observed in the range of 20-100 ng/ml what imposes an upper limit for the AFB1 detection (Fig.7 a). The saturation can be explained considering that the great majority of antibodies (anti-AFB1) are bonded to the AFB1 molecules. Besides, no significant changes in the PL were identified for control samples. Figure 7 b shows the sensor signal (response curve) of PAN/ZnO20nm/APTES/GA/Anti-AFB1 structure vs the concentration of AFB1. The linear fitting (dark blue line) of the experimental data (bright blue spots) can be expressed by the formula: 𝐼 𝑃𝐿565,2 = 0.489 -0.385 • 𝐿𝑜𝑔(𝐶),(3)

Figure 8 .

 8 Figure 8. Sketch of the energy band diagram of the ZnO nanolayer with two types of surface modifications: PAN/ZnO20nm/APTES/GA/Anti-AFB1/BSA (a) and PAN/ZnO20nm/APTES/GA/Anti-AFB1/BSA&AFB1 (b). The transition 1 is the excitation of the electron-hole pair under UV light irradiation, 2non-radiative transition of the electron to the defect level, 3 is the radiative transition, which is the PL in the visible region, 4non-radiative transition in the space charge region (SCR), 5' indicates the electron migration from the surface to the volume of ZnO, 5'' indicates the holes migration from volume to the ZnO interface.

Figure 8 a

 8 Figure 8 a shows the upward band bending with the surface potential 𝜓 𝑠1 (𝜑 𝐷1 ) and the SCR (𝑑 1 ),

Figure 9a presents the

  Figure 9a presents the time-resolved PL intensity changes of the PAN/ZnO20nm/APTES/GA/Anti-AFB1 sample vs different AFB1 concentrations. The immunosensor response time to the different AFB1 concentrations was in the range of 15-20 min. The dashed lines indicate the steady-state conditions for each concentration. The total AFB1 concentration interacted with the PAN/ZnO20nm/APTES/GA/Anti-AFB1 surface was calculated as the sum of all infused

Figure 9 .

 9 Figure 9. Dependence of PL peak maximum (at λ = 565 nm) vs AFB1 concentration; (b) the isotherm of analyte (AFB1) interaction with PAN/ZnO20nm/APTES/GA/Anti-AFB1 structure; and (c) calculated sensitivity of PAN/ZnO20nm/APTES/GA/Anti-AFB1 structure towards AFB1.

  Figure 10 c shows the time-dependent average intensity of PL for the PAN/ZnO20nm/APTES/GA/Anti-AFB1&AFB1.It is seen that the PL intensity progressively increases over time. The PL images were analyzed using ImageJ software. The inset image indicates the change in average PL intensity during the APTES/GA/Anti-AFB1&AFB1 complex formation. The average PL intensity was about (~ 26%), and has a good agreement with the value (~ 25%) from PL-based real-time measurement for AFB1 10 ng/ml concentration (Fig.9 b). A control experiment was also conducted on the PAN/ZnO20nm sample. No significant non-specific adsorption of AFB1 was observed. The results confirm that the produced immunosensor provides a sensing capability with a high signal-to-noise ratio and diminished non-specific adsorption.

Figure 10 .

 10 Figure 10. The images obtained via fluorescent confocal microcopy: (a) bulk PAN/ZnO20nm nanofibers (b) and PAN/ZnO20nm/APTES/GA/Anti-AFB1 structures. (c) the time-resolved PL intensity of PAN/ZnO20nm/APTES/GA/Anti-AFB1, concentration of AFB1 -10 ng/ml.

  In the present study, we report on the development of 1D PAN/ZnO nanocomposites that can be applied for a low-cost, label-free and sensitive PL biosensor (immunosensor) towards AFB1 as a model molecule. As a biorecognition layer, the antibody towards AFB1 (anti-AFB1) has been chosen. Structural and optical properties of the fabricated PAN/ZnO nanocomposites have been

	investigated by scanning electron spectroscopy (SEM), transmission electron microscopy (TEM),
	X-Ray diffraction analysis (XRD), Fourier-transform infrared spectroscopy (FTIR) and confocal
	microscopy. The PL of PAN/ZnO nanocomposites functionalized with the anti-AFB1, as well as the
	control samples (without anti-AFB1), was measured for different concentrations of AFB1. It was
	found that high surface to volume ratio of PAN/ZnO nanocomposites and high affinity of
	immobilized anti-AFB1 to AFB1 give the possibility of detecting AFB1 in a wide sensitivity range
	0.1 -20 ng/ml and with detection limit (LOD) of 39 pg/ml. Furthermore, estimated values of power
	coefficient, and change of Gibbs free energy indicate strong electrostatic interaction between
	biosensor and the analyte (AFB1). The general mechanism of the PL biosensor response change
	during the PAN/ZnO/APTES/GA/Anti-AFB1&AFB1 complex formation was proposed. Hereby,
	we propose a novel PL-based approach for AFB1 detection on PAN/ZnO/APTES/GA/Anti-AFB1
	structure.
	2. Experimental section
	2.1. Materials
	Polyacrylonitrile PAN (Mw = 150 000), and dimethylformamide (DMF) (ACS reagent, ≥99.8%)
	were purchased from Sigma Aldrich. Diethyl zinc (DEZ) (Zn(CH2CH3)2, 95% purity, CAS: 557-20-
	0), was purchased from Sterm Chemical. Anti-AFB1 monoclonal antibodies (1 mg/ml, mouse IgG1
	isotype, № A9555), AFB1 (2 μg/ml in acetonitrile, analytical standard, №34029), Protein A (№
	P3838), BSA, (purity ≥98.0%, № 05470), (3-Aminopropyl)triethoxysilane (APTES, purity ≥98%),
	and glutaraldehyde (GA, 50 wt. % in H2O) were purchased from Sigma Aldrich. Phosphate-
	buffered saline (PBS, pH 7.4) was used as the diluent for AFB1 dissolution. Al biological
	components were diluted on the day of the experiment (without additional storage in dissolvent).

: (i)

what are the mechanisms for PL detection in ZnO; and (ii) is it possible to use this nanocomposite for mycotoxin (AFB1) detection.

2.4. Characterization techniques

	3 s pulse
	of DEZ, 30 s exposure and 50 s purge with dry Ar; ii) 2 s pulse of H2O, 40 s of exposure, and 60 s
	purge with dry Ar. The growth rate was generally 2.1 Å/cycle for ZnO. The ZnO thickness growth
	per cycle was controlled by measuring the ZnO film's thickness on planar Si substrates placed in the
	reactor and proved by transmission electron microscopy on PAN nanofibers. After the ALD of ZnO
	over the PAN nanofibers were obtained, samples with different ZnO thicknesses were obtained:
	PAN/ZnO5nm, PAN/ZnO10nm, PAN/ZnO20nm, PAN/ZnO50nm.
	Morphology of the PAN/ZnO nanocomposite surface was investigated by scanning electron
	microscopy (SEM) (JEOL, JSM7001F) with an energy dispersive X-ray (EDX) analyzer and
	transmission electron microscopy (TEM) (JEOL ARM 200F) high-resolution transmission electron
	microscope (200 kV) with an EDX analyzer. The structural state of PAN/ZnO was analyzed by
	means of X-ray diffraction (XRD) (PANalytical, X'pert 3 pro MRD diffractometer) working with a

Table 1 .

 1 DNA). A comparison of typical optical (label-free) biosensors for AFB1 detection is presented in the Table1, in which the LOD of current immunosensor is at a low level, with the sensitivity range similar to the others. Representative results of recent label-free optical biosensors for AFB1 detection

	). The calculated value of LOD was

based biosensor is comparable with results obtained elsewhere

[START_REF] Myndrul | Gold coated porous silicon nanocomposite as a substrate for photoluminescence-based immunosensor suitable for the determination of Aflatoxin B1[END_REF][START_REF] Bhardwaj | A label-free ultrasensitive microfluidic surface Plasmon resonance biosensor for Aflatoxin B1 detection using nanoparticles integrated gold chip[END_REF][START_REF] Wei | A novel gold nanostars-based fluorescent aptasensor for aflatoxin B1 detection[END_REF]

or even lower than that reported by Alshannaq et al. and Moon et al.

[START_REF] Moon | On-Site Detection of Aflatoxin B1 in Grains by a Palm-Sized Surface Plasmon Resonance Sensor[END_REF][START_REF] Alshannaq | A Liquid Chromatographic Method for Rapid and Sensitive Analysis of Aflatoxins in Laboratory Fungal Cultures[END_REF]

. This result shows that the studied nanostructures and the detection approach could be further applied for the development of efficient immunosensors and novel biosensors with other types of biorecognition agents (e.g. enzymes,

Table 2 .

 2 Calculated parameters of realtime AFB1 detection and adsorption.

	LOD, pg/ml S, ng/ml	n	KD, ng/ml	KD, M	∆G, kJ/mol
	39 ± 1	0.1 -20	0.95 ± 0.01	0.96 ± 0.11 29.5•10 -10 ± 2.2•10 -11 -44.6 ± 1.2

Acknowledgments I.I., E.C., V.M., and M.B. acknowledge the financial support by project H2020-MSCA-RISE-2017, 'Novel 1D photonic metal oxide nanostructures for early stage cancer detection' (Project number: 778157). V.M. acknowledge the partial financial support from the project "Środowiskowe interdyscyplinarne studia doktoranckie w zakresie nanotechnologii" No. POWR.03.02.00-00-I032/16 under the European Social Fund -Operational Programme Knowledge Education Development, Axis III Higher Education for Economy and Development, Action 3.2 PhD Programme.