Lucile Marty
email: lucile.marty@liv.ac.uk

Blandine De Lauzon-Guillain

Maë Labesse

Sophie Nicklaus

Food choice motives and the nutritional quality of diet during the COVID-19 lockdown in France

Keywords: nutritional quality, food choice motives, lockdown, COVID-19

To limit the transmission of COVID-19, nationwide lockdown was imposed in France between March, 17 th and May, 10 th 2020. This disruption in individuals' daily routines likely altered food consumption habits. We examined how changes in food choice motives related to changes in nutritional quality during the lockdown compared to before. A convenience sample of 938 French adults completed online questionnaires on the Qualtrics platform at the end of April 2020. Participants were retrospectively asked about their food choice motives and food consumption during the month before and in the first month of the lockdown. The importance of nine food choice motives was assessed: health, convenience, sensory appeal, natural content, ethical concern, weight control, mood, familiarity, and price, scoring from 1 to 4. Food intakes were recorded using a food frequency questionnaire including 110 foods, 12 non-alcoholic beverages and 4 alcoholic beverages. Adherence to the French dietary recommendations before and during the lockdown was estimated using the simplified PNNS-GS2 score, scoring from -17 to 11.5. The nutritional quality of diet was lower during the lockdown compared to before SD 2.28, p<0.001). Food choice motives significantly changed and an increase in the importance of weight control was associated with increased nutritional quality (β=0.89, p<0.001, partial η 2 =0.032), whereas an increase in the importance of mood was associated with decreased nutritional quality (β=-0.43, p=0.021, partial η 2 =0.006). The lockdown period in France was related to a decrease in nutritional quality of diet on average, which could be partly explained by changes in food choice motives. The lockdown was indeed related to modification of food choice motives, notably with an increase of weight control, health, natural content and ethical concern.

Introduction

The world is currently facing the COVID-19 pandemic. To avoid fast-growing transmission of the virus, governmental authorities have had to impose nationwide lockdowns. In France, between March, 17 th and May, 10 th 2020, most of the population was asked to stay home. In order to limit drastically any human contact, the French were allowed to leave their home only for grocery shopping, medical care, legal obligations, physical activity within a 1 km radius; except for workers from essential sectors (e.g., healthcare, food factories and shops). During this period, all businesses that sold food remained open to the public. However, major disruptions in daily routines caused by the lockdown (e.g., homeworking, restaurant closures) were likely to alter food consumption habits in the French population. Moreover, closed borders led to changes in the distribution and availability of food products [START_REF] Morel | Coronavirus : la pénurie de saisonniers paralyse l'agriculture européenne[END_REF]Oxfam France, 2020).

A large part of humans' eating behaviours are habits, i.e., automatic associations between specific context cues and responses, which have history of repetition and reward.

Habits form as people pursue goals by repeating the same responses in given contexts, and become automatic and hard to change [START_REF] Wood | Psychology of habits[END_REF]. Because food choices are performed every day and usually in the same context, they likely result from a habitual response; notably, food choices have been shown to be stable in adulthood [START_REF] Borland | Stability of dietary patterns in young women over a 2-year period[END_REF][START_REF] Hu | Reproducibility and validity of dietary patterns assessed with a food-frequency questionnaire[END_REF][START_REF] Khani | Reproducibility and Validity of Major Dietary Patterns among Swedish Women Assessed with a Food-Frequency Questionnaire[END_REF][START_REF] Weismayer | Changes in the Stability of Dietary Patterns in a Study of Middle-Aged Swedish Women[END_REF]. However, when people are undergoing changes in their environment, their habits are vulnerable to change as they engage in a new nonautomatic process of decision making [START_REF] Verplanken | Interventions to Break and Create Consumer Habits[END_REF]. We thus hypothesised that the unusual lockdown period may have caused discontinuities in food choice habits.

In a constructionist perspective, food choice decisions result from one's personal food values that are shaped by life course events, personal and social factors [START_REF] Furst | Food choice: A conceptual model of the process[END_REF][START_REF] Sobal | Constructing food choice decisions[END_REF]. Food values are computed by integrating a set of attributes (food choice motives) based on their importance or salience for an individual at the point of choice [START_REF] Rangel | Regulation of dietary choice by the decision-making circuitry[END_REF]. A change in food choice motives may thus lead to a change in food choice decisions. The most important food choice motives have been shown to be taste, cost, nutrition and convenience with a large interindividual variability [START_REF] Glanz | Why Americans eat what they do: Taste, nutrition, cost, convenience and weight control concerns as influences on food consumption[END_REF]. We hypothesised that people engaging in a new process of food choice decision making during the lockdown period may have caused changes in food choice motives associated with changes in food choice habits, resulting in modification of the nutritional quality of diet.

The present study aimed to examine the extent of changes in food choice motives during the lockdown and how it related to changes in nutritional quality of diet. We hypothesised that food choice motives and nutritional quality of diet changed during the first month of lockdown (from March, 17 th to April, 16 th 2020) compared to the month just before the lockdown (from February, 17 th to March, 16 th 2020). We also hypothesised that changes in food choice motives were associated with changes in nutritional quality. Because poor nutritional quality diet is one of the main risk factors for non-communicable diseases [START_REF] Afshin | Health effects of dietary risks in 195 countries, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017[END_REF], it is of importance to examine the effect of the lockdown on nutritional quality to help anticipating health consequences at a population level. Moreover, this unique nationwide disruption in daily life gives the opportunity to investigate how changes in food choice motives may influence the nutritional quality of diet at an individual level. The results may inform future public health actions that aim at tackling diet related non-communicable diseases by identifying which food choice motives changes may increase or decrease the nutritional quality of diet.

Methods

Design and data collection

This was a cross-sectional, pre-registered online experiment conducted in Qualtrics survey platform (www.qualtrics.com). Participants were recruited by emailing individuals from a population registered in the Chemosens Platform's PanelSens database at Centre des Sciences du Goût et de l'Alimentation (Dijon). This database was declared to the relevant authority (Commission Nationale Informatique et Libertés; CNIL; n°1148039). Eligible participants were aged over 18, had been residing in France at least since February 17th, 2020 (i.e., one month before the lockdown) and had access to a computer or tablet with an internet connection. Eligible participants who completed the study received compensation in return for their participation (15€ Amazon voucher). The study was approved by the ethical evaluation committee for research of INSERM (reference: n°20-683, delivered on April 27 th , 2020). All participants were informed that the purpose of the study was to investigate food choices during the lockdown and provided consent for their participation. Data were collected on April, 30 th and May, 1 st 2020. Three attention check questions (e.g., 'How many times have you visited the planet Mars?') were included in various parts of the questionnaire.

Measures

Participants' characteristics

Participants' characteristics assessment included demographic questions (age, gender, employment status, highest educational qualification, professional situation during the lockdown, living area, type of housing, household composition, financial situation) and foodrelated behaviours questions (out-of-home eating habits before the lockdown, grocery shopping frequency and time spent cooking during the lockdown, changes in their eating habits during the lockdown, dietary restrictions, dieting status, weight and height at the time of the study). Participants also answered questions about their consumption of organic and local food products (not reported here). As participants were recruited during the COVID-19 pandemic, they were asked if they suspected having or having had COVID-19 and how worried they were about their health. We also asked for current levels of stress, depression, and loneliness (3 individual items) on a continuous scale from 0 to 100.

Food choice motives

Food choice motives were assessed using a French version of the Food Choice Questionnaire developed in English by [START_REF] Steptoe | Development of a Measure of the Motives Underlying the Selection of Food: the "Food Choice Questionnaire[END_REF] and adapted by [START_REF] Cottet | La compréhension des moteurs des comportements alimentaires : une approche par le food choice questionnaire[END_REF]. The French version included 24 items and nine subscales: health (3 items), convenience (3 items), sensory appeal (3 items), natural content (3 items), ethical concern (2 items), weight control (3 items), mood (3 items), familiarity (2 items), and price (2 items). See Additional file -section 1 for the items in French and in English. Instructions were adapted to assess food choice motives during the month before the lockdown and during the first month of the lockdown simultaneously. For each subscale, two scores were computed by averaging ratings for individual items before and during the lockdown, respectively. The scores ranged from 1 to 4: 1 = Not at all important; 2 = A little important; 3 = Moderately important; 4 = Very important. Δ motives were calculated as the difference of the score for each of the nine subscales during and before the lockdown. Δ motives > 0 indicated higher importance of the motives during the lockdown compared to before.

Food consumption and dietary nutritional quality

Food consumption was retrospectively assessed for the month before the lockdown and the first month of the lockdown simultaneously using a food frequency questionnaire (FFQ) including 110 foods, 12 non-alcoholic drinks and 4 alcoholic drinks with frequency assessed by a 6-item scale from "Never" to "Several times a day" [START_REF] Kadawathagedara | Adéquation des consommations alimentaires des femmes enceintes de l'étude ELFE aux recommandations du Programme national nutrition santé[END_REF]. Usual portion sizes before and during the lockdown were estimated with photos for different food types on a 5-level scale, derived from the SU.VI.MAX portion book [START_REF] Hercberg | Portions alimentaires : manuel photos pour l'estimation des quantités[END_REF], for 72 commonly eaten food items, and by the intermediate portion size for the 38 remaining food items. Participants were also asked the size of the glass or cup they used before and during the lockdown for each non-alcoholic beverage and standard servings were used to estimate alcoholic beverage amounts. Consumption frequency of each item before and during the lockdown was transformed into daily frequency, and daily intake was calculated by multiplying the daily frequency by the estimated portion size.

Individual nutrients intakes were calculated before and during the lockdown by multiplying the daily intake of each food item by its nutritional values from the SU.VI.MAX nutrient composition database [START_REF] Hercberg | Table de composition des aliments SU[END_REF].

Adherence to the French dietary recommendations was evaluated during the month before the lockdown and during the first month of the lockdown using the simplified PNNS-GS2 score (sPNNS-GS2), an index previously designed to reflect the 2017 French main dietary recommendations [START_REF] Chaltiel | Programme national nutrition santé -Guidelines score 2 (pnns-gs2): Development and validation of a diet quality score reflecting the 2017 French dietary guidelines[END_REF]. The sPNNS-GS2 builds on the distinction between malus components (less healthy food groups which consumption should be limited, carrying a negative score, i.e., red meat, processed meat, sugary foods, sweet-tasting beverages, alcoholic beverages, salt) and bonus components (healthier food groups carrying a positive score, i.e., fruits and vegetables, nuts, legumes, whole-grain food, milk and dairy products, fish and seafood). The sPNNS-GS2 calculation has been previously described by [START_REF] Chaltiel | Programme national nutrition santé -Guidelines score 2 (pnns-gs2): Development and validation of a diet quality score reflecting the 2017 French dietary guidelines[END_REF]. A weight for each component is defined according to the level of evidence of the association between food groups consumption and health status. sPNNS-GS2 scores were computed for each participant before and during the lockdown (range: -17 to 11.5). Slight modifications were brought to the calculation of the score. The sPNNS-GS2 originally included bonus points for added fat below 16% of energy intake [START_REF] Chaltiel | Programme national nutrition santé -Guidelines score 2 (pnns-gs2): Development and validation of a diet quality score reflecting the 2017 French dietary guidelines[END_REF]. The FFQ did not make it possible to calculate the percentage of energy intake accounted for added fat and this component was excluded from the score calculation.

However, a modified version of the sPNNS-GS2 including an added fat component based on the ratio of plant over animal fat was also calculated. The main analysis was performed on this indicator and results were similar (see Additional file -section 2). In addition, the only whole grain food included in the used FFQ was whole grain bread. To obtain an estimation of other whole grain foods consumption frequency as required by the sPNNS-GS2 calculation, we calculated the ratio whole grain bread/(whole grain bread + white bread) and multiplied the consumption frequency of other grains (pasta, rice and semolina) by this ratio.

Outcome

The primary outcome, Δ quality, was the difference in nutritional quality of diet (sPNNS-GS2) between during and before the lockdown. Δ quality > 0 indicated better nutritional quality during the lockdown compared to before.

Statistical analyses

Hypotheses were specified before the data were collected and we followed an analytic plan that was pre-registered before data analysis (https://osf.io/gwfdb/). Only participants who completed the study were included in the analyses. Participants who failed at least one attention check were excluded. We analysed data from participants who reported plausible energy intake, i.e. ≥ 500 kcal/day and ≤ 3500 kcal/day for women, and ≥ 800 kcal/day and ≤ 4000 kcal/day for men [START_REF] Banna | Examining Plausibility of Self-Reported Energy Intake Data: Considerations for Method Selection[END_REF][START_REF] Willett | Nutritional Epidemiology[END_REF].

For descriptive purposes, we compared food choice motives scores and sPNNGS-2 components scores before and during the lockdown using paired T-tests. As exploratory analyses, we also examined whether changes in food choice motives or nutritional quality during the lockdown compared to before differed across population subgroups using one-way ANOVAs: people who are younger vs. older, male vs. female, normal-weight vs. overweight, lower vs. higher educational level, facing financial difficulties vs. people who were not, living alone during the lockdown vs. with others, living in a city vs. in the countryside, usually having meal out of home at least four times a week vs. less than 4 times a week, infected by the corona virus vs. not infected. We then examined the influence of changes in food choice motives during and before the lockdown on the difference in nutritional quality of diet by running a multiple linear regression including the nine Δ motives as predictors and Δ quality as the dependant variable (main model). Sensitivity analyses were conducted to examine whether the pattern of results from the main model differed: 1/ including age, gender, highest educational level and reported BMI as covariates (adjusted model), 2/ excluding participants who declared that they did not make any noticeable change in their diet during the lockdown, 3/ excluding participants who declared that they often did not find in store what they wanted to buy during the lockdown, as change in diet quality could be due more to external constraints than to personal motives, 4/ excluding participants who declared that they went to work as normal during the lockdown. As an additional exploratory analysis, we also adjusted the main model for the variables with significant effects on Δ motives or Δ quality in the exploratory one-way ANOVAs.

All statistical analyses were performed using SAS version 9.3 (SAS Institute, Inc., 2012 SAS® 9.3. Cary, NC). The level of significance was set at p < 0.05 applying Bonferroni correction for multiple comparisons where appropriate.

Sample size calculation

We aimed to recruit a sample size of 1,000 participants to detect small differences in food choice motives scores and sPNNS-GS2 score before and during the lockdown using paired t-tests (d = 0.1) and small effects of Δ motives on Δ quality in a multiple linear regression including nine predictors (f 2 = 0.016) at power 0.80 and level of significance 0.05 (GPower 3.1).

Results

Participants

A total of 1353 participants consented to participate. Participants who were not eligible (n=110), did not complete the study (n=121), failed at least one attention check (n=84) or reported implausible energy intake (n=100) were excluded and data from 938 participants were analysed. Participants' characteristics are presented Table 1. Eighteen participants declared that they suspected having COVID-19 when they completed the study and 59 declared that they suspected having had COVID-19 before. Six hundred participants (64%) declared being slightly to very worried about their health. On average levels of stress, depression, and loneliness were 26 (SD 28), 23 (SD 25), and 34 (SD 28) respectively on a scale from 0 to 100.

Food choice motives and nutritional quality of diet before and during the lockdown

Food choice motives changed significantly during the lockdown compared to before (Table 2). In particular, 48% of the participants declared that mood was more important in their food choices during the lockdown compared to before and 48% declared that convenience was less important. Health and weight control were more important during the lockdown compared to before for 26 and 29% of the participants, respectively. On average, the participants consumed 1700 kcal/day (SD 596) during the month before the lockdown and 1935 kcal/day (SD 656) during the first month of lockdown and this increase was statistically significant (paired t-test: t(937) = 13.57, p < 0.001). Overall, the nutritional quality of diet significantly decreased during the first month of the lockdown compared to the month before (Table 3). Despite an increase in fruit and vegetables, pulses, fish and seafood consumption, the sharp increase in processed meat, sweet-tasting beverages and alcoholic beverages consumption negatively affected the sPNNS-GS2 score. EIWA, energy intake without alcohol. 249 a paired t-tests, Bonferroni corrected alpha level: 0.004, b without added fat component, range from -17 to 11.5. c one serving/handful of nuts = 30g [START_REF] Chaltiel | Programme national nutrition santé -Guidelines score 2 (pnns-gs2): Development and validation of a diet quality score reflecting the 2017 French dietary guidelines[END_REF].

We explored whether changes in food choice motives and nutritional quality during the lockdown compared to before differed across population subgroups and found relatively few significant differences (see Additional file -section 3).

When examining the influence of changes in food choice motives on changes of the nutritional quality of diet during the lockdown compared to before, we found that increased importance of weight control motives was associated with increased nutritional quality and that increased importance of mood motives was associated with decreased nutritional quality in both raw and adjusted multiple linear regressions (Table 4). Changes in other food choice motives were not associated with changes in the nutritional quality of diet. In the other three multiple linear regressions testing the influence of changes in food choice motives on changes of the nutritional quality conducted as sensitivity analyses (i.e., excluding participants who declared that they did not have made any noticeable change in their diet during the lockdown, excluding participants who declared that they often did not find in store what they wanted to buy during the lockdown, excluding participants who declared that they went to work as normal during the lockdown), Δ weight control and Δ mood remained significant or marginally significant predictors of Δ quality (see Additional file -section 4). In addition, the exploratory adjusted model, including the variables from exploratory analyses for which we found differences in Δ motives or Δ quality, also led to similar results (see Additional filesection 4). quality is the difference in sPNNS-GS2 score during the lockdown compared to before. Δ quality > 0 indicated better nutritional quality during the lockdown compared to before. Δ motives > 0 indicated higher importance of the motives during the lockdown compared to before.

a Control variables: age, gender, BMI, highest educational qualification.

Discussion

To our knowledge, this is the first study that investigated changes in food choice motives associated with nutritional changes during the lockdown in France. Significant changes in food choice motives during the lockdown were observed with an increase in the importance of health, weight control, ethical concern, natural content, sensory appeal, and mood, and a significant decrease in the importance of convenience, familiarity, and price. The participants reported a 14% increase in energy intake and a decrease in nutritional quality of their diet during the lockdown compared to before. An increase in the importance of weight control during the lockdown was associated with increased nutritional quality, whereas an increase in the importance of mood was associated with decreased nutritional quality.

Changes in the importance of other food choice motives were not associated with changes in nutritional quality of diet.

Increase in energy intake and unhealthier dietary patterns during the lockdown compared to before were also described in a study conducted among 37,252 French adults from the web-based NutriNet-Santé cohort [START_REF] Deschasaux-Tanguy | Diet and physical activity during the COVID-19 lockdown period[END_REF]. The authors found an energy intake of 1942 kcal/day during the lockdown, which is similar to the reported energy intake reported during the lockdown in the present study (1935 kcal/day on average).

The authors highlighted weight gain for 35% of the sample and increased consumption of sweets, biscuits, and cakes. Consistently, despite the fact that the participants of the present study increased their intake of fruit and vegetables, pulses, fish and seafood, they also increased their consumption of processed meat, sugary foods, sweet-tasting beverages and alcoholic beverages leading to a decrease in nutritional quality of their diet on average. These changes in food consumption patterns echo studies showing increased snacking during the lockdown [START_REF] Deschasaux-Tanguy | Diet and physical activity during the COVID-19 lockdown period[END_REF][START_REF] Sanchez | How COVID-19 is impacting our eating & drinking habits[END_REF], as fatty-sweet products and sweet-tasting beverages (including fruit juices) are usually consumed during snacking episodes by French adults [START_REF] Si Hassen | Energy, nutrient and food content of snacks in French adults[END_REF]. In addition, a survey on 3,000

French adults reported that 42% declared having pre-meal drinks ("apéritif") more often during than before the lockdown (Darwin Nutrition & IFOP, 2020). Pre-meal drinks are usually the first part of a meal, opening a social eating time and are often accompanied by finger foods [START_REF] Danesi | A cross-cultural approach to eating together: Practices of commensality among French, German and Spanish young adults[END_REF]. The deterioration of nutritional quality during the lockdown may be partly due to increased number of social and festive eating occasions within the home, associated with consumption of low-nutritional-quality foods (e.g., sweet-tasting beverages and alcoholic beverages, processed meat, sugary foods). Changes in health, ethical concern, natural content, sensory appeal, and price food choice motives during the lockdown are in line with the results of a survey conducted among a representative sample of 1,005 French adults where the participants declared changes in their perception of the ecological (49%), social (47%) and economical (57%) values of the food during the lockdown (YouGov, 2020). The decrease in the importance of convenience for 48% of our sample mirrored that 83% declared that they increased their time spent cooking during the lockdown. Collectively, these changes in food choice motives may reflect a growing awareness of the importance of the sustainability of food choices where preserving health and pleasure from eating, protecting the environment and guaranteeing decent wages to farmers are equally important [START_REF] Fao | Sustainable healthy diets -Guiding principles[END_REF].

Increase in the importance of weight control (29% of the participants) and mood (48% of the participants) food choice motives were prominent and associated with opposite changes in nutritional quality of diet. Stress, feeling of emptiness and boredom management by eating were common behaviours in the French population during the lockdown with 63%, 63%, and 57% prevalence in a 1,092 sample of French adults, respectively [START_REF] Cherikh | Behavioral Food Addiction During Lockdown: Time for Awareness, Time to Prepare the Aftermath[END_REF].

Occasional emotion regulation by eating is associated with the consumption of sweet foods [START_REF] De Lauzon | The Three-Factor Eating Questionnaire-R18 is able to distinguish among different eating patterns in a general population[END_REF][START_REF] Macht | Emotional Eating[END_REF] which may explain the negative relationship between changes in mood food choice motive and nutritional quality of diet. On the contrary, increased importance of weight control led to increased nutritional quality, suggesting that participants engaging in weight management behaviour successfully stuck with their goal by managing their food intake during the first month of the lockdown. In line with our results, a study investigating eating behaviour during the lockdown in 2,364 UK adults showed that 35% of the participants declared eating a more healthy and balanced diet during the lockdown compared to before (Robinson et al., unpublished results). It is worth noticing that in the present study increased importance of health as a food choice motive was not significantly correlated with increased nutritional quality; whereas people more motivated by health were reported to adopt healthier diet than people less motivated by health [START_REF] Konttinen | Socio-economic disparities in the consumption of vegetables, fruit and energydense foods: The role of motive priorities[END_REF][START_REF] Naughton | The creation of a healthy eating motivation score and its association with food choice and physical activity in a cross sectional sample of Irish adults[END_REF]. Moreover, we would have expected an increase in nutritional quality when price became less important because of the positive association between price and nutritional quality across individual food items [START_REF] Andrieu | Low-cost diets: more energy, fewer nutrients[END_REF][START_REF] Marty | Higher nutritional quality at no additional cost among low-income households: Insights from food purchases of "positive deviants[END_REF][START_REF] Rehm | The quality and monetary value of diets consumed by adults in the United States[END_REF], but this is not supported by these data. Similarly, we would have expected an increase in nutritional quality when convenience became less important because the degree of food processing and convenience were shown to be negatively associated with nutritional quality [START_REF] Steele | The share of ultra-processed foods and the overall nutritional quality of diets in the US: Evidence from a nationally representative cross-sectional study[END_REF][START_REF] Poti | Is the degree of food processing and convenience linked with the nutritional quality of foods purchased by US households?[END_REF]. Our results suggest that choosing more expensive and less convenient foods (i.e., requiring more effort and time to prepare) did not necessarily translate into better nutritional quality of diet. Overall, the difference in the measured food choice motives only explained 5.7% of the variance of the change in the nutritional quality during compared to before the lockdown. Nutritional quality is multidimensional by nature; food choices are complex decisions and various other variables may have influenced what people chose to eat and the resulting nutritional quality of their diet during the lockdown, for instance the availability of food products.

Strengths and limitations

We were able to collect detailed information about food consumption during the month before the lockdown and during the first month of the lockdown in a large sample of French adults. Our study was timely as the data were collected two weeks after the end of the first month of the lockdown. However, the participants retrospectively reported their food consumption which is a clear limitation of this study. We could not anticipate the lockdown and organise a measurement point before the lockdown. Participants were asked to report simultaneously for each food item their consumption before and during the lockdown which made it easier reporting differences in consumption frequency, even if a recall bias could have affected the responses for the period before the lockdown. In other respects, due to this exceptional situation, we compared food consumption in March (before the lockdown, end of winter) and in April (during the lockdown, beginning of spring). We could have expected a season effect in our data, with an improvement of the nutritional quality of diet in April compared to March due to increased availability of fresh fruit and vegetables, although access to fresh product may have been limited by the lockdown (Oxfam France, 2020). Finally, due to unexpectedly high numbers of participants who failed an attention check or reported implausible energy intake (16.4% of the eligible participants who completed the study), we did not reach the sample size of 1,000 participants we aimed for. However, a sample size of 938 participants still allowed to detect small effects of Δ motives on Δ quality in a multiple linear regression including nine predictors (f 2 = 0.017) at power 0.80 and level of significance 0.05 (GPower 3.1). A limitation of this study is that the sample was not representative of the French population and included more women and individuals with higher educational level. This is often the case in studies with volunteers on this topic [START_REF] Deschasaux-Tanguy | Diet and physical activity during the COVID-19 lockdown period[END_REF]. In addition, the participants were recruited from a population registered in the Chemosens Platform's PanelSens database, gathering individuals who agreed to be contacted to take part in research studies exploring eating behaviours. Thus, it is likely that our sample was biased towards individuals with an interest in food. However, this can also be viewed as a strength as these individuals were more likely to have paid attention to what they ate before and during the lockdown and consequently to have cautiously reported their food consumption.

Future research

In a follow-up study, it would be interesting to investigate whether changes in food choice motives and nutritional quality remain stable overtime. Moreover, we analysed the nutritional quality, but the lockdown may also have influenced other characteristics of diet (e.g., proportion of organic and local products). A secondary objective of this online survey was to compare consumption of organic and locally produced food before and during the lockdown and to examine how it related to nutritional quality of diet. The collected data about consumption of organic and local food products before and during the lockdown will be analysed separately. An unanswered question is how diet of more disadvantaged populations was modified during the lockdown and specific studies are needed to describe food choices and eating behaviours among these populations. Finally, only increased weight control food choice motive significantly predicted a better nutritional quality of diet. The increase in health food choice motive did not translate into better nutritional quality of diet. Yet, numbers of public health actions aim at increasing motivation towards health to encourage the individuals to make healthier food choices [START_REF] Capewell | An effectiveness hierarchy of preventive interventions: Neglected paradigm or self-evident truth[END_REF][START_REF] Frieden | A framework for public health action: The health impact pyramid[END_REF]. Our results suggest that increasing the importance of health as a food choice motive might not be sufficient to increase the nutritional quality of diet, maybe because of a lack of nutritional knowledge. From this perspective, making nutritional information easy to understand and directly accessible by consumers at the point of choice should be prioritised, e.g., the front-ofpack nutrition label Nutriscore [START_REF] Egnell | Objective understanding of Nutri-Score Front-Of-Package nutrition label according to individual characteristics of subjects: Comparisons with other format labels[END_REF].

Conclusion

The lockdown period in France was related to a decrease in nutritional quality of diet on average which could be partly explained by changes in food choice motives. The lockdown was indeed related to modification of food choice motives in this sample. For instance, whereas the importance of convenience and price motives decreased, the importance of health, natural content and ethic motives increased, suggesting a growing awareness of the importance of sustainable food choices.

  a range: 1 to 4, b paired t-tests, Bonferroni corrected alpha level: 0.006, c corresponds to participants with Δ motives > 0, d Δ motives = 0, e Δ motives < 0

Table 1 .

 1 Participants' characteristics, n=938

	Age, years, mean (SD)

a Excluding weight < 30 kg or > 250 kg, height < 1.45 m or > 3 m

(Hardy, Johnson, & Park, 2016; Miller, 2003)

Table 2 .

 2 Food choice motives before and during the lockdown, n=938

	Before	During	Difference	p-	Increased	Unchanged	Decrease
	lockdown	lockdown	during vs.	value b	during vs.	during vs.	during vs.

(0.72), Convenience (0.85), Sensory appeal (0.66), Natural content (0.86), Ethical concern (0.64), Weight control (0.84), Mood (0.64), Familiarity (0.64), Price (0.67).

Table 3 .

 3 Comparison of the nutritional quality of diet before and during the lockdown

			Before	During
		Recommendation	lockdown	lockdown	p-value a
			mean (SD)	mean (SD)
	sPNNS-GS2 score b		1.2 (2.5)	0.8 (2.8)	<.001
	Score components
	Fruit and vegetables	At least 5 servings/day	2.6 (1.6)	3.2 (1.8)	<.001
	(frequency/day)
	Pulses	At least 2 servings/week	0.7 (1.1)	0.9 (1.3)	<.001
	(frequency/week)
	Whole-grain foods	Every day	0.5 (0.6)	0.6 (0.7)	0.019
	(frequency/day)
	Nuts	A handful/day c	2.8 (5.2)	2.7 (5.8)	0.371
	(g/day)
	Dairy products	2 servings/day	2.3 (1.4)	2.5 (1.4)	<.001
	(frequency/day)
	Fish and seafood	2 servings/week	1.6 (1.5)	1.7 (1.5)	0.002
	(frequency/week)
	Red meat	<500 g/week	292 (266)	302 (280)	0.154
	(g/week)
	Processed meat	<150 g/week	113 (133)	145 (172)	<.001
	(g/week)
	Sugary foods	<10% EIWA	11.6 (7.1)	12.5 (7.9)	<.001
	(% EIWA)
	Sweet-tasting beverages	0 ml/day	177 (376)	213 (413)	<.001
	(ml/day)
	Alcoholic beverages	<100 g of alcohol/week	30 (59)	39 (72)	<.001
	(g of alcohol/week)
	Salt	<8 g/day	2.9 (1.1)	3.2 (1.2)	<.001
	(g/day)

Table 4 .

 4 Influence of Δ motives on the difference in nutritional quality of diet between during and before the lockdown, dependant variable: Δ quality

			Raw model			Adjusted model a
			(n=938)			(n=927)
			R 2 = 0.057			R 2 = 0.076
		β estimate	p-value	partial η 2	β estimate	p-value	partial η 2
	(Intercept)	-.39	<.001		0.24	0.656
	Δ Weight control	0.89	<.001	0.032	0.99	<.001	0.043
	Δ Mood	-.43	0.021	0.006	-.42	0.035	0.006
	Δ Health	0.31	0.227	0.002	0.29	0.285	0.002
	Δ Sensory appeal	0.21	0.491	0.001	0.27	0.418	0.001
	Δ Familiarity	-.15	0.312	0.001	-.14	0.391	0.001
	Δ Price	-.11	0.427	0.001	-.20	0.197	0.002
	Δ Ethical concern	-.09	0.621	<.001	-.30	0.155	0.003
	Δ Natural content	-.07	0.811	<.001	0.17	0.573	<.001
	Δ Convenience	0.01	0.895	<.001	0.04	0.765	<.001

Variance inflation factor: Δ Health (1.72), Δ Convenience (1.23), Δ Sensory appeal (1.17), Δ Natural content (1.80), Δ Ethical concern (1.40), Δ Weight control (1.37), Δ Mood (1.08), Δ Familiarity (1.18), Δ Price (1.08). Δ

Acknowledgments

We thank the ChemoSens platform for the help with data collection, in particular C. Martin and F. Durey; and V. Feyen for her help with participant management. This work was supported by grants from ANR (ANR-15-CE21-0014, PUNCH grant to SN), the Conseil Régional Bourgogne, Franche-Comte (PARI grant) and the FEDER (European Funding for Regional Economic Development). The funders had no role in planning, conducting, or interpreting the study.

Author contributions

LM and SN designed the study and were responsible for data collection. LM and ML analysed the data. BLG developed the food frequency questionnaire and assisted in data analyses. LM was responsible for initial drafting of the paper, and all authors read and approved the final manuscript.


Bang Gu

Cheng Zhou

Shun He b Simona Moldovan

Petr A Chernavskii

Vitaly V Ordomsky
email: vitaly.ordomsky@univ-lille.fr

Andrei Y Khodakov
email: andrei.khodakov@univ-lille.fr

Size and Promoter Effects on Iron Nanoparticles Confined in Carbon Nanotubes and their Catalytic Performance in Light Olefin Synthesis from Syngas

Keywords: Fischer-Tropsch, Particles size, Confinement, Lower olefins, Iron, Promoter

Light olefins are important products of high temperature Fischer-Tropsch synthesis over iron catalysts. In this paper, we found that the catalytic performance of iron catalysts was strongly affected by iron nanoparticle size, their encapsulation inside of carbon nanotubes and promotion with bismuth or lead. The presence of promoters and iron nanoparticle confinement leads to a major increase in the reaction rate. A gradual increase in the TOF numbers with the increase in the iron nanoparticle sizes from 2.5 to 12 nm was observed at both 1 and 10 bar over the carbon nanotubes containing encapsulated monometallic or Bi-or Pb-promoted iron nanoparticles. The size of monometallic iron nanoparticles encapsulated in carbon nanotubes does not show any noticeable effect on the light olefin selectivity, while in the Bi-and Pb-promoted catalysts, the light olefin selectivity was higher over smaller encapsulated iron nanoparticles and decreased with the increase in the nanoparticle size. The stability of iron nanoparticles versus sintering was also improved by the encapsulation.

Introduction

Light olefins (ethylene, propylene and butene) are key building-block chemicals, which are widely used in the chemical industry [1][START_REF] Kang | Advances in Catalysis[END_REF][START_REF] Gu | [END_REF]. Currently, light olefins are primarily produced via stream cracking of naphtha or methanol-to-olefins (MTO) process, while ethylene is also manufactured from ethane cracking [4]. The growing demand for light olefins and depletion of oil reserves have stimulated development of processes for light olefin synthesis from syngas, which might be produced from alternative feedstocks such as methane, biomass, coal or organic and plastic wastes.

Fischer-Tropsch (FT) synthesis produces hydrocarbons from syngas. High temperature FT synthesis (300-350 °C) is mainly used for production of gasoline and light olefins [START_REF] Steynberg | Studies in surface science and catalysis[END_REF][START_REF] Abelló | [END_REF]. FT synthesis is one of the most efficient ways to convert syngas directly into light olefins [7][8][9]. In the olefin synthesis from syngas, Fe-based catalysts can be the catalysts of choice, because of their low cost, high selectivity towards olefins and flexibility relative to the use of syngas with different H2/CO ratios [4,[10][11][12].

FT synthesis is often considered as a structure sensitive reaction and particle size may have noticeable effects both on the activity and selectivity [13][14][15][16]. The particle size effects over cobalt [17][18][19][20] and ruthenium-based [21][22][23] catalysts in low temperature FT synthesis have been addressed in numerous publications. The optimum cobalt and ruthenium size was found to be about 6-8 nm. The increase in the size of metal nanoparticles above 8 nm leads to lower overall activity, while the metal particles with the sizes smaller than 6 nm demonstrate both lower intrinsic activity (Turnover Frequency, TOF) and lower selectivity toward the C5+ hydrocarbons. The particle size effects over iron-based FT catalysts can be rather complex, because of simultaneous presence of different iron phases and catalyst deactivation.

Previous reports suggest that the selectivities to methane and lighter hydrocarbons increase, when iron nanoparticles in supported catalysts are getting smaller than 6-9 nm [24]. TOF increases with the increase in the particle sizes from 2.4 to 6.2 nm and it remains almost constant up to the particle size of 11.5 nm. The stability of iron particles in silica-supported catalysts was previously studied [25,26] in the nanoscale range (9-20 nm). On the one hand, smaller iron-carbide nanoparticles were found more difficult to obtain by carbidisation of iron oxides and on the other hand, they were less stable than larger particles.

The iron particle size effects on the catalytic performance in FT synthesis might be influenced by catalyst promotion and metal-support interactions. In the oxide-supported catalysts, the active metal can react with a support and form barely reducible aluminates or silicates and thus, hinder formation and reduce the stability of active iron carbide phase. The metal support interactions are usually weaker in the carbon-supported catalysts. De Jong [27,28] et al examined the influence of iron carbide particle size in the promoted and unpromoted carbon nanofiber supported iron catalysts on the syngas conversion to light olefins. The TOF numbers of unpromoted catalysts increased 6-8 times with particle size decreasing from 7 to 2 nm, while the selectivities to methane or light olefins were found independent on the particle size [27]. The iron catalysts promoted with sodium and sulphur showed similar variation of TOF as a function of particle size. The increase in TOF with decrease in iron particle size in the promoted catalysts was principally due to higher yield of methane over the smallest particles. Recently, we have discovered strong promoting effects of Bi and Pb on the catalytic performance of Fe catalysts in FT synthesis [29,30]. The effects have been attributed to the enhanced C-O dissociation on the surface of iron carbide nanoparticles in the presence of Bi and Pb, which significantly increases catalyst activity and selectivity to light olefins.

A number of previous works suggest important influence of iron nanoparticles confinement in carbon nanotubes (CNT) on the electronic structure, catalytic performance and stability of iron FT catalysts [31][32][33]. Bao [34] et al found that iron nanoparticles confined in CNT exhibited better reducibility, carbidisation and much higher activity in FT synthesis compared to the unconfined counterparts, while the selectivity to light olefins was not much affected by the confinement [35,36]. Higher reaction rate was principally attributed to higher extent of iron carbidisation inside CNTs. The encapsulation of nanoparticles also protects them from sintering [37].

Analysis of the electron distribution in CNT using DFT [38] showed that the curvature of the CNT induced a significant electron disparity. More electrons were distributed on the exterior surface of the CNT. This led to stronger bonding of iron species with the outside CNT surface than those located the inside CNT walls. These electronic effects might result in different catalytic activity of iron inside and outside CNT.

The present work addresses the size effects of iron nanoparticles encapsulated inside of CNT on syngas conversion to light olefins. To the best of our knowledge, there have been no studies about the effect of the size of iron nanoparticles confined inside CNT on their properties and catalytic performance. Both monometallic iron catalysts and catalysts promoted with bismuth and lead have been studied. The syngas conversion to lower olefins has been performed at both high and atmospheric pressures at the temperatures typical of high temperature FT synthesis.

Experimental

CNT pre-treatment

Prior to the deposition of iron and promoters, the CNTs were pre-treated according to previous literature [34]. CNTs (Iolitec nanomaterial, 95%, inter diameter 5-12 nm, outer diameter 10-20 nm) were exposed to boiling concentrated nitric acid in order to open the tube channels, to remove contaminations and to make CNT hydrophilic. Typically, 3.0 g of CNT were pre-treated in concentrated HNO3 (68%, 210 mL) during 14 h under reflux at 140 o C. Then the samples were filtered, washed with distilled water until pH = 7 and dried at 100 ºC overnight. CNT with closed tube channels were pre-treated under milder condition (34 wt. % HNO3 for 6h at 110 o C).

Catalyst preparation

The encapsulated iron catalysts were prepared by incipient wetness impregnation of CNT support with aqueous solutions of iron nitrate (Fe(NO3)3•9H2O, Sigma-Aldrich).

The amount of iron in the impregnating solutions was calculated in order to obtain 10 wt. % iron in the final catalysts. Lead nitrate (Pb(NO3)2, Sigma-Aldrich) and bismuth nitrate (Bi(NO3)3•5H2O, Sigma-Aldrich) were used for preparation of the Bi-and Pb-promoted iron catalysts by co-impregnation. The aqueous solutions were drawn into the CNT channels by capillary forces assisted by ultrasonic treatment and stirring. The molar ratios of Fe/Pb and Fe/Bi were 100/2. After the impregnation, the samples were dried in an oven at 80 o C for 12 h followed by thermal treatment for 4 h under a flow of nitrogen (50 mL/min). The temperature of thermal treatment was varied from 300 to 600 °C in order to obtain different iron particle size. The calcined catalysts are labelled as FeM/CNT-in-T, where "M" represents the promoters (Bi or Pb), "in" represents iron inside the CNT tubes and "T" stands for thermal treatment temperature. For comparison, the Fe/AC and Fe/CNT-out catalysts, where "out" indicates iron particles located outside the tubes, were prepared by the same procedure. The temperature of thermal treatment in the N2 flow for those 2 samples is 400 o C; the duration is 4h. The iron content in these two catalysts is 10 wt.%.

Catalyst characterization

Low temperature N2 physisorption measurements were carried out using a Micromeritics Tristar 3020 Surface Area and Porosimetry analyzer. The samples were degassed at 200 o C for 2 h to remove water before N2 adsorption. The N2 adsorption-desorption isotherms were measured at -196°C.

The X-ray diffraction patterns (XRD) were recorded using a Siemens D5000 diffractometer. The measurement conditions were: Cu(Kα) (λ = 0.15418 nm), tube pressure 40 kv, tube current 30 mA, and scanning rate 0.02° s -1 . The phase composition analysis of the samples was performed by comparing the XRD Standards Database of the Joint Committee on Powder Diffraction Standards (JCPDS). The average crystallite size of iron oxides (Fe2O3) was evaluated by the Scherrer equation [39] using the diffraction peak of Fe2O3 at 2θ of 30.2 o .

Quantitative elemental analyses were performed by inductively coupled plasma-optic emission spectroscopy 720-ES ICP-OES (Agilent) with axially viewing and simultaneous CCD detection. The quantitative determination of metal content in the catalysts was based on the analysis of standard solutions. The ICP ExpertTM software (version 2.0.4) provided metal concentration in the samples. The minimum detection limitation is 0.1 ppm and the accuracy is better than 5%.

The H2 temperature-programmed reduction (H2-TPR) experiments were carried out by the AutoChem II 2920 apparatus (Micromeritics) using 0.10 g of the sample in a flow of H2/Ar (5 vol. % H2) stream (50 ml/min). The temperature was increased from room temperature to 900 °C at the rate of 10 °C/min.

The TEM (Transmission Electron Microscopy) analyses were carried out on a

Phillips FEI G2 30 high resolution transmission electron microscope with an accelerating voltage of 300 KV. The sample was prepared by dispersing in an ethanol solution. After 1 h of ultrasonication, the sample slurry was dropped onto a 400-mesh carbon film copper mesh, and dried under an infrared lamp to test. High angle annular dark field (HAADF)-scanning transmission electron microscopy (STEM) imaging, and energy dispersive X-ray spectroscopy (EDX) of the calcined analysis were performed on a Jeol-ARM200 transmission electron microscope, operated at 200 kV and scanning speed 20 μs/px for imaging and 0.05 μs/px for EDX. More than 200 iron particles were counted to estimate the iron particles size distribution and average iron particle size.

In-situ magnetic characterization has been performed using a Föner vibrating-sample magnetometer. 1 mg of pure metallic Fe was used for the calibration before each experiment. 10 mg of the fresh catalysts was heated to 200 °C with the ramping rate 6.6 °C/min in the flow of CO or syngas (15 ml/min) and then sequentially heated to 350 °C (4.7 °C/min) for 2 h in CO or syngas. After activation, the sample was cooled to RT in the atmosphere of CO or syngas with the saturation magnetization curve recorded by the magnetometer.

Catalytic tests

The catalytic tests in FT synthesis were performed in a fixed-bed reactor (8 mm inner diameter). Typically, 0.1 g of fresh catalyst with the particle size of 100-150 μm was loaded in the reactor and then reduced in the CO gas flow (50 ml/min, atmospheric pressure) at 350 o C with a heating rate of 2 o C/min for 10 h before the reaction. After the reactor was cooled down to 180 o C, a syngas with the H2/CO ratio of 1/1 and under pressure of 10 or 1 bar was introduced into the reactor. Nitrogen with a fixed flow rate of 1 ml/min in the syngas was used as an internal standard for the calculation of CO conversion. After the pressure and gas flow rate stable, the temperature was raised with the ramping rate of 1 o C/min to the desired reaction temperature (350 o C). The absence of mass transport resistances was checked by Weisz-Prater Criterion (NW-P) for internal diffusion [40][START_REF] Weisz | Advances in Catalysis[END_REF][START_REF] Primo | [END_REF].

= ≤ 0.3
where R = observed reaction rate (molCO g -1 s -1 ), = catalyst particle radius (m), = effective diffusivity (cm 2 s -1 ), Cs = gas concentration of CO at the external surface of the catalyst (mol cm -3 ). We considered a total gas flow rate of 57 ml min -1 with ~ 60 % CO conversion and a catalyst particle size of 0.10 -0.15 mm. The pressure was 10 bar and the reaction rate was calculated from the measured FTY of 6.1*10 -4 molCO gFe -1 s -1 . Cs and are calculated according to the literature [43] with the values of 4.9*10 -5 and 0.0229 cm 2 s -1 , respectively. The Nw-p value is calculated to be 2 ×10 -3 , which is much lower than 0.3.

The reaction feed gas and gaseous products were analysed online using a gas chromatograph (Bruker GC-450), which was equipped with a thermal conductivity (TCD) and a flame ionization (FID) detectors. The packed CTR-1 column is connected to the TCD detector for separation of N2, CO, CO2, and CH4. The Rt-Q PLOT capillary column is connected to the FID detector for analysis of hydrocarbons and oxygenates. The liquid products were collected in a cold trap and analysed by gas chromatography. The selectivities were calculated on carbon basis. The CO2 free hydrocarbon selectivities were calculated considering only hydrocarbon production in FT synthesis. The carbon balance was better than 90%.

The iron time yields (FTY) were expressed as moles of CO converted per gram of total iron per second. Apparent turnover frequency (TOF) was calculated according with previous literature [16,27] using the bulk density of Fe5C2 (ρ = 7.57 g mL -1 ) and assuming the surface density of 14 Fe atoms nm -2 .

Results and discussion

Catalyst structure

Tables 1 and2 show textural properties and elemental composition of the CNTs supported monometallic and Bi-or Pb-promoted iron nanoparticles exposed to different temperatures. The impregnation of CNTs with iron decreases the surface area, total pore volume and mesopore diameter. Interestingly, the pore volume is decreased after introduction of iron from 0.83 cm 3 /g to about 0.50 cm 3 /g. This suggests that some iron particles are located inside of the CNT tubes. Localization of iron nanoparticles inside CNT leads to the decrease in the pore volume and partial blocking of the tubes. The presence of the Bi and Pb promoters, in addition to iron, results in only very small effect on the texture of CNT catalysts. Indeed, the BET surface area and pore volume are almost not affected by the presence of the promoters.

The elemental analysis (Tables 1 and2) shows that all monometallic iron catalysts supported by carbon nanotube treated in nitrogen at different temperatures contain around 10 wt.% iron. Iron content in the promoted catalysts was also close to10 wt. %, while the contents of bismuth and lead were respectively ~0.85 wt.% and ~0.90 wt.%. and 53.9° can be ascribed to the magnetite phase (Fe3O4, JCPDS 75-0449). The iron oxide peaks become sharper with higher pre-treatment temperature probably due to increase in the iron oxide particle sizes. The iron crystallite sizes have been evaluated

from the Scherrer equation (Table 1). The iron crystallite size increases from 2.6-2.8 nm for the iron catalysts treated at 300 °C to 11-12 nm for the catalysts treated in nitrogen at 600 °C. Note that the promotion with Bi and Pb does not noticeably affect the iron oxide particle size (Table 2). Our previous studies [29,30] also showed insignificant effect of the bismuth and lead promotions on iron dispersion and iron oxide nanoparticle sizes in the SiO2 and CNT supported iron catalysts. The confined iron catalysts contain smaller particles compared with the Fe/AC iron catalysts supported on active carbon (Figure S1 and Table S1, SI). The difference is more pronounced, when the Fe/AC catalysts were calcined at higher temperatures. It is interesting to note that maximum size of encapsulated metal oxide nanoparticles corresponds to the internal diameter of CNT (14.4 nm). This is consistent with localization of iron oxide nanoparticles inside the CNT and suggests that the growth of iron oxide crystallites inside the CNT could be limited by the CNT diameter.

The the pre-treatment temperature on the iron oxide particle sizes were observed with and without promoters (Table 1 and2). Thus, the characterisation suggests that the promoter does not affect the size of metal nanoparticles.

STEM-HAADF and STEM-EDS analysis have been performed in order to further confirm localization of iron and promoters in CNT (Figure 5). Bi is a heavier metal compared to iron. In the STEM-HAADF images, the Bi species correspond to brighter spots compared to iron. STEM-EDX indicates that Bi is uniformly distributed on the surface of Fe nanoparticles. These results are similar to our previous data obtained for iron-supported catalysts promoted by Bi and Pb over the SiO2 and CNT supports.

Because of low melting points, metallic bismuth and lead migrate to the iron nanoparticles and form core-shell structures during catalyst activation and reaction.

These core-shell structures were identified by the EDS analysis [29,30].

The reducibility of iron oxide nanoparticles encapsulated inside CNT was investigated by H2-TPR. Figure 6a shows the TPR profiles of the monometallic Fe/CNT-in catalysts with encapsulated iron oxide nanoparticles of different sizes. The TPR profiles exhibit three main broad peaks located at around 390, 450 and 650 o C.

According to the literature [33,45,46], the first peak can be assigned to the reduction of Fe2O3 to Fe3O4, the second peak to the reduction of Fe3O4 to FeO and the third peak to the reduction of FeO to metallic Fe. Note that some hydrogen consumption can due to the reductive removal of carboxyl and other oxygen-containing groups from the surface of CNT during the treatment in hydrogen. The small and broad peaks located at 700-800 o C can be caused by gasification of the CNT support [13]. Because of low amounts of bismuth and lead, no TPR peaks could be assigned to the reduction of the promoters. The Fe/CNT-out catalyst containing iron nanoparticles outside the CNT channels has been used as a reference (Figure 6a). Interestingly, the encapsulated iron catalysts can be reduced at lower temperatures compared with the Fe/CNT-out catalyst. This suggests that the confinement increases the iron reducibility in agreement with the works of Bao' group [34]. Moreover, as the iron particle size inside the CNT channels increases, the intensity of reduction peaks decreases and they slightly shift to lower temperatures. Similar effect also has been discovered by Park [24] over alumina supported iron catalysts with different crystal sizes. This effect might be explained by easier reducibility of larger iron oxide nanoparticles. Easier reducibility of larger metal oxide nanoparticles compared to smaller counterparts has been previously observed in numerous publications [25,47,48].

Introduction of the Bi and Pb promoters to the iron catalysts does not change significantly the relative position of the TPR peaks but shifts their maximums by approximately 10 ºC to lower temperatures (Figure 6b, Table 2). This indicates that promotion of the CNT containing confined iron nanoparticles enhances iron reducibility. Similar effects were also observed recently for the silica and CNT supported FeBi and FePb catalysts [29,30]. Note that previously prepared promoted iron catalysts supported over CNT contained iron nanoparticles only outside the CNT [30]. Thus, Bi and Pb also promote iron reducibility by increasing total hydrogen consumption and decreasing the reduction temperature in both confined and non-confined systems.

Iron carbide has been considered active phase for iron-based Fischer-Tropsch catalysts. Iron carbide can be formed during activation in the presence of CO prior to the reaction. The XRD for the used catalysts shows a broad peak, which corresponds to the mixture of different iron carbide phase (χ-Fe5C2, ε-Fe2.2C, Fe3C, or Fe7C3,

Figure S4, SI).

Similar results were obtained for the Fe/CNT and FeBi/CNT catalysts [30]. In order to identify iron carbide phase, the in-situ magnetic measurements [49,50] were conducted in the flow of CO or syngas at different temperatures (Figure S5, SI). The two examined Fe/CNT-in and FeBi/CNT-in catalysts present a similar shape of thermomagnetic curves with the Curie temperature of ~ 250 o C. According to our previous report [30], the main iron carbide phase has been identified as χ-Fe5C2 in the catalysts exposed to the flow of CO or syngas. Interestingly, the iron carbide concentration was higher in the Bi promoted iron catalyst.

Catalytic results

The catalytic data are shown in Tables 3 and4 and in For comparison, Fe/CNT-out and Fe/AC have been also tested under the same conditions (Table 3). The activity of Fe/CNT-out is 1.5 times higher than for the Fe/AC catalyst. Note however that the confined catalysts present 2-4 times higher reaction rate compared with the Fe/AC catalyst.

The selectivity to light olefins and C5+ hydrocarbons follows the sequence: Fe/AC< Fe/CNT-out< Fe/CNT-in, whereas the methane selectivity shows the opposite trend.

These results are consistent with earlier data of Bao's group [34]. The effect of confinement on the chain growth probability is relatively small, while the ratio of olefins to paraffins increases in the confined catalysts. Stronger interaction of CO with the CNT internal surface [51,52] can lead to lower H2/CO ratio inside the CNT and thus decreases the secondary olefin hydrogenation. S1, SI). Similar trend has been found as for the Fe/CNT-in-T catalysts. Thus, we found that over the unpromoted, confined or unconfined iron catalysts, particle size does not noticeable affect the light olefin selectivity. These results are consistent with the data of De Jong [27] who also observed similar selectivity to methane and lower olefins is over the iron particles of different sizes in FT reaction over unpromoted iron catalysts.

Different to the unpromoted iron catalysts, the size of Bi-promoted and encapsulated iron particles has strong effects both on the activity and selectivity (Figure 8). The presence of the promoters significantly increases the FT reaction rate. The FeBi/CNT-in catalyst shows more than 2 times higher FTY in comparison with the Fe/CNT-in catalyst at the pressure of 10 bar (Figures 9 and 10, S6, SI, Table 4). The reaction selectivity shifts to the C2-C4 light hydrocarbons compared to the monometallic Fe/CNT-in catalyst. The methane selectivity decreases from ~29 % to ~ 25 % and C5 + decreases from ~ 20 % to ~12%. In addition, the selectivity of lower olefins increases from ~ 35 % to ~ 45%. The selectivity to CO2 also increases over the FeBi/CNT-in catalysts compared with the monometallic Fe/CNT-in counterparts. The effect can be due to easing CO dissociation on iron carbide via oxygen removal from iron carbide by scavenging with the promoters [29,30]. The catalytic activity in the presence of the promoters increases with increase in iron nanoparticle size until 6 nm and then decreases at the larger iron nanoparticle sizes. More importantly, this promotion effect is also significant even under atmospheric pressure with the 2-3 times increase in the FTY in comparison with the non-promoted catalysts. Compared with the Bi promoted iron catalysts, the FePb/CNT-in catalysts present even much more significant increase in FTY (~2.5 times higher than Fe/CNT-in). Different to CNT containing monometallic iron nanoparticles, the C2-C4 olefin selectivity and olefin to paraffin ratio decrease with increase in the iron particle size both at 10 bar and under atmospheric pressure (Table 4, Figure 8 and9). Higher, but slightly different, light olefin selectivities over the promoted iron catalysts with different particle size might be ascribed to different coverages of the iron carbide surface with the promoters. De Jong [27] also observed this effect over Na and S promoted iron catalysts with different iron carbide particle size.

More detailed information about the intrinsic activity of CNT containing encapsulated monometallic iron nanoparticles and those promoted with Bi and Pb was obtained from the TOF values. The TOF values assuming the presence of the Fe5C2 under the reaction conditions are presented in Tables 3 and4. TOFs are plotted as a function of iron particle size for CNT containing encapsulated monometallic and promoted iron nanoparticles measured at the 10 bar and atmospheric pressure (Figure 11). As expected, higher TOF were obtained at higher reaction pressure. The TOF numbers for unpromoted catalysts at both high and low pressure reaction conditions increase rapidly with increase in the particle sizes up to 6 nm and stabilise for larger metal nanoparticles. These results are consistent with those for cobalt and ruthenium catalysts for which TOF increases with the particle size up to 6-8 and stabilize at larger sizes [20,23]. Park [24] also found the similar results over iron catalysts with varying particle size from 2 nm to 12 nm in FTS. It is noteworthy that the Bi and Pb promoted iron catalysts present ~3 times (10 bar) and ~ 5 times (1 bar) higher TOF values compared with monometallic iron catalysts.

Apart from the enhancement of FT reaction rate, confinement of iron nanoparticles in CNT also improves the catalyst stability. Figure S8, SI shows micrographs of two spent Bi-promoted iron catalysts and calculated respective particle size distribution.

The average particle size of spent FeBi/CNT-300 is 3.9 nm, while for the FeBi/CNT-in-400 the average size after reaction is 6.5 nm. Both the FeBi/CNT-in-300 and FeBi/CNT-in-400 catalysts show very slight sintering compared with the fresh catalysts. We can conclude that confinement is also an efficient way to improve the stability of small iron carbide nanoparticles.

Conclusion

Encapsulation inside carbon nanotubes affects the properties of iron nanoparticles, their catalytic performance and stability in high temperature FT synthesis. The temperature of catalyst thermal treatment has a strong effect on the size of iron nanoparticles encapsulated inside CNT. Larger iron nanoparticles were obtained after treatment at higher temperature and they exhibit better reducibility. The promoters (Bi and Pb) are located in the surface of iron with close contact and the iron sintering degree is restricted by confinement in CNT.

The presence of promoters strongly influences on the catalytic performance of iron carbide nanoparticles. The specific reaction rates (TOF) were 3-5 times higher over the Bi-and Pb -promoted catalysts compared to the unpormoted counterparts. In the unpromoted iron catalysts with confined iron nanoparticles, the TOF increases with the increase in the iron nanoparticle size from 2.5 nm to 6-8 nm and then remains stable with further increase in the iron particle size, while the product selectivity is not affected by the nanoparticle size variation.

affects both the activity and selectivity. The activity shows similar trend with the unpromoted iron catalysts, while the selectivity to light olefins decreases with the increase in the iron particle size. These findings shed further light the fundamental effects of confinement on catalysis, and provide more insights into the particle size effects in iron-based FT catalysts. b Single point desorption total pore volume of pores, P/P0=0.975.

c The pore diameter in the mesoporous region evaluated by the BJH method.

d Average particle size of iron oxide by XRD.

e Average particle size of iron oxide by TEM.

f The total H2 consumption and iron reducibility degree from TPR analysis.

g The Fe content from ICP-OES. c The pore diameter in the mesoporous region evaluated by the BJH method.

d Average particle size of iron oxide by XRD.

e Average particle size of iron oxide by TEM.

f The total H2 consumption and iron reducibility degree from TPR analysis.

g Fe, Bi, Pb content from ICP-OES.

Figure

  Figure 1a displays XRD profiles of the CNT containing confined monometallic

Figures 4 ,

 4 Figures 4, S2 and S3, Supporting Information (SI).Importantly, in the catalysts,

Figures 7 - 11 ,

 711 S6 and S7, SI. High temperature FT synthesis yields methane, C2-C4 hydrocarbons, C5+ hydrocarbons, CO2 and water. The CNT with encapsulated monometallic and Bi-or Pb-promoted iron nanoparticles with different sizes have been tested in a fix-bed reactor both at high (10 bar) and atmospheric pressure at T = 350 o C and H2/CO = 1/1.

Figure 7 8 .

 78 displays CO conversion and product selectivities for the CNT containing encapsulated iron monometallic nanoparticles as functions of iron particle sizes. At high pressure and at GHSV = 17 L/g.h, carbon monoxide conversion over monometallic iron catalysts increases from 18 to 34 % with the increase in the encapsulated iron particle sizes from 2.8 to 6 nm. Interestingly, further increase in the iron nanoparticle sizes leads to the decrease in the CO conversion. Note that the FT reaction rates were much lower at atmospheric pressure compared to the tests conducted at 10 bar. The selectivities to methane and light olefins over the iron unpromoted nanoparticles at the 10 bar test were about 28 % and 37 %, respectively. Interestingly, these two values do not change much with increasing iron particles size. In order to compare the reaction selectivities, the carbon monoxide conversion was adjusted to the 40-50% level by varying GHSV. Relevant selectivity data are presented in Figure The increase in the size of iron nanoparticles encapsulated in CNT does not significantly affect the olefin selectivity and olefin to paraffin ratio over the unpromoted iron catalysts. The selectivity to the C5+ hydrocarbons increases from 16.1 to 19.9% with the iron particles size increase from 2.8 nm to 6.0 nm and then stabilises. Further particle size increase from 6.0 nm to 11.4 nm does not affect the reaction selectivity[24]. For comparison, iron catalysts supported over active carbon with different particles size (Fe/AC) has been tested in FT synthesis (Table

Figure 1 .

 1 Figure 1. XRD profiles of the CNT supported iron catalysts with different calcination temperature.

Figure 2 .

 2 Figure 2. TEM images of the CNT confined iron catalysts under different calcination temperature.

Figure 3 . 8 .Figure 4 .

 384 Figure 3. Particle size distribution of the CNT confined iron catalysts under different calcination

Figure 6 .

 6 Figure 6. H2-TPR profiles of the CNT confined iron catalysts under different calcination

Figure 7 .

 7 Figure 7. CO conversion and products selectivity versus iron particle size over unpromoted iron

Figure 8 .

 8 Figure 8. C2-C4 olefin selectivity and olefin to paraffin ratio as function of the size of iron

Figure 9 .

 9 Figure 9. CO conversion and product selectivity versus iron particle size over Bi promoted iron

Figure 10 .

 10 Figure 10. Iron particle size effect on the CO conversion over Bi or Pb promoted and unpromoted

Figure 11 .

 11 Figure 11. Iron particle size effect on the TOF (350 o C, H2/CO = 1/1, GHSV = 17 L/g.h (10bar) or

Table 1 .

 1 Characterization of the supports and CNT confined monometallic Fe catalysts.

	Sample	SBET a	Vtot b	Dmeso c	Dmetal d	Dmetal e	Total H2	Fe
		(m 2 /g)	(cm 3 /	(nm)	(nm)	(nm)	consum	conte
			g)				ption f	nt g
							(mmol/g)	(wt%)
	CNT-raw	138.2	0.43	14.0
	CNT-HNO3	230.3	0.83	14.4	-	-	-	-
	Fe/CNT-in-300	205.3	0.53	10.9	-	2.8	2.40	10.9
	Fe/CNT-in-350	198.7	0.51	10.6	3.8	3.9	-	10.7
	Fe/CNT-in-400	192.9	0.52	10.8	6.0	6.0	1.80	10.3
	Fe/CNT-in-450	188.3	0.50	11.1	7.8	7.7	-	11.3
	Fe/CNT-in-500	193.6	0.51	10.8	11.2	9.9	1.60	11.1
	Fe/CNT-in-600	199.9	0.53	11.2	12.7	11.4	1.52	10.7

a BET surface area.

Table 2 .

 2 Characterization of CNT with confined iron nanoparticles promoted with Bi or Pb.

	Sample	SBET a	Vtot b	Dmeso c	Dmetal d	Dmetal e	Total H2	Fe	Bi or
		(m 2 /g)	(cm 3	(nm)	(nm)	(nm)	consum	conte	Pb
			/g)				Ption f	nt g	conte
							(mmol/g)	(wt%)	nt g
									(wt%)
	CNT	230.3 0.83	14.4	-	-	-	-
	FeBi/CNT-in-300 200.3 0.52	11.0	-	2.6	3.0	10.2	0.88
	FeBi/CNT-in-350 193.7 0.52	11.2	3.9	4.1	2.83	10.8	0.84
	FeBi/CNT-in-400 183.3 0.52	11.3	6.2	5.8	2.53	10.5	0.92
	FeBi/CNT-in-450 173.3 0.50	10.4	8.3	7.8	2.51	11.2	0.86
	FeBi/CNT-in-500 176.6 0.48	10.8	10.8	10.3	2.40	11.3	0.83
	FeBi/CNT-in-600 179.9 0.45	11.2	11.9	11.7	2.12	10.9	0.87
	FePb/CNT-in-300 208.2 0.51	10.7	-	2.7	2.70	10.9	0.90
	FePb/CNT-in-400 187.8 0.50	10.2	5.3	5.9	2.18	10.6	0.88
	FePb/CNT-in-600 180.1 0.48	10.5	11.5	11.8	1.85	11.0	0.87

a BET surface area.

b Single point desorption total pore volume of pores, P/P0=0.975.

Table 3 .

 3 Catalytic performance of CNT with encapsulated iron nanoparticles with different sizes in FT synthesis (350 o C, H2/CO = 1/1, GHSV = 17 L/g.h (10bar) or 3.4 L/g.h (1bar), TOS = 10 h)

			FTY		CO	CO2	Hydrocarbon selectivity (%)
		Pressure		TOF					C2-4 = /
	Catalysts		10 -4		conv.	sel.
		(bar)	molCOgFe -1 s -1	(s -1 )	(%)	(%)	CH4 C2-4 = C2-4 0	C5 +	C2-4 o
	Fe/AC	10	0.77	0.244	7.4	28.7 36.2 27.3 22.9 13.6 1.19
	Fe/CNT-out	10	1.25	0.288 12.0	29.8 33.6 32.5 19.8 14.1 1.64
		10	1.90	0.132 18.3	30.0 29.2 38.2 16.5 16.1 2.32
	Fe/CNT-in-300
		1	0.09	0.006	4.3	14.0 33.4 42.0 12.3 12.3 3.41
		10	2.50	0.242 24.2	32.0 28.9 37.3 15.5 18.3 2.41
	Fe/CNT-in-350
		1	0.12	0.012	5.6	20.0 32.5 41.6 12.1 13.8 3.44
		10	3.50	0.521 33.7	40.0 28.5 35.9 15.0 19.9 2.39
	Fe/CNT-in-400
		1	0.18	0.027	8.6	27.0 32.1 41.2 11.9 14.8 3.46
		10	2.70	0.516 26.0	36.0 28.6 35.7 15.7 20.0 2.27
	Fe/CNT-in-450
		1	0.11	0.021	5.4	18.0 31.9 40.9 11.7 15.5 3.50
		10	2.80	0.614 27.0	35.0 28.4 36.1 16.0 19.5 2.26
	Fe/CNT-in-500
		1	0.11	0.027	5.3	16.0 32.2 41.1 11.8 14.9 3.48
		10	2.70	0.651 26.3	33.0 28.1 36.2 16.3 19.4 2.22
	Fe/CNT-in-600
		1	0.11	0.031	5.2	15.0 31.5 40.1 11.6 16.8 3.46

Table 4 .

 4 Catalytic performance of CNT with encapsulated iron nanoparticles with different particle size promoted with Bi and Pb in FT synthesis (350 o C, H2/CO = 1/1, GHSV = 17 L/g.h (10bar) or

	3.4 L/g.h (1bar), TOS = 10 h)
		FTY		CO	CO2	Hydrocarbon selectivity (%)
	Pressure		TOF						C2-4 = /
	Catalysts	10 -4		conv.	sel.
	(bar)	molCOgFe -1 s -1	(s -1 )	(%)	(%)	CH4 C2-4 = C2-4 0	C5 +	C2-4 o
	10	3.7	0.239	35.7	40.1	26.4 49.0 15.1	9.5	3.25
	FeBi/CNT-in-300
	1	0.21	0.014	10.3	14.0	28.3 64.0	6.0	1.7 10.70
	10	4.8	0.488	46.2	42.9	25.9 47.0 17.0 10.1 2.76
	FeBi/CNT-in-350
	1	0.37	0.038	17.6	20.0	27.6 63.2	6.5	2.7	9.72
	10	6.1	0.878	58.7	46.0	25.5 45.0 17.0 12.5 2.65
	FeBi/CNT-in-400
	1	0.52	0.075	25.1	31.0	27.3 62.6	6.7	3.4	9.34
	10	5.0	0.968	48.0	43.3	25.3 43.8 18.7 12.2 2.34
	FeBi/CNT-in-450
	1	0.43	0.083	20.6	18.0	26.8 62.0	6.9	4.3	8.99
	10	4.9	1.252	47.0	41.3	24.6 42.2 20.7 12.5 2.04
	FeBi/CNT-in-500
	1	0.38	0.097	18.3	16.0	26.2 61.1	7.5	5.2	8.15
	10	4.8	1.394	46.3	41.0	24.1 40.8 22.8 12.3 1.79
	FeBi/CNT-in-600
	1	0.36	0.104	17.2	15.0	25.4 60.1	7.9	6.6	7.61
	10	4.4	0.295	42.7	40.1	25.0 44.2 19.1 11.7 2.31
	FePb/CNT-in-300
	1	0.38	0.025	18.3	20.2	25.8 62.0	6.0	6.2 10.30
	10	7.4	1.083	70.7	46.0	23.4 39.9 20.7 16.0 1.93
	FePb/CNT-in-400
	1	0.74	0.108	35.7	36.0	25.0 59.1	8.3	7.6	7.12
	10	4.9	1.406	49.3	41.0	20.1 36.5 23.5 19.9 1.55
	FePb/CNT-in-600
	1	0.42	0.123	20.2	26.0	22.1 55.5 10.7 11.7 5.19

Acknowledgements

The authors thank Olivier Gardoll, Laurence Burylo and Joelle Thuriot for help with TPR, XRD measurements and ICP-OES analysis. B. G. thanks the China Scholarship Council for providing him a stipend for PhD studies in France. The authors acknowledge financial support from European Union (Interreg V project PSYCHE).

The authors acknowledge financial support of the French National Research Agency (Project NANO4-FUT, ANR-16-CE06-0013).