Phocoena phocoena in set gillnets is routinely monitored in European Union fisheries, but generally relies on data collected at low spatio-temporal resolution or over short periods. In Denmark, a long-term monitoring programme started in 2010 using electronic monitoring to collect data on porpoise bycatch and gillnet fishing effort at a fine spatial and temporal scale, including time and position of each fishing operation, together with every associated bycatch event. We used these observations to model bycatch rates, given the operational and ecological characteristics of each haul observed in Danish waters. Data on fishing effort from the Danish and Swedish gillnet fleets were collected to predict fleet-wide porpoise bycatch in gillnets at regional level. Between 2010 and 2020, yearly total bycatch averaged 2088 animals (95% Cl: 667–6798). For the Western Baltic assessment unit, bycatch levels were above sustainability thresholds. These results demonstrate that fishing characteristics are key determinants of porpoise bycatch and that classical approaches ignoring these features would produce biased estimates. It emphasizes the need for efficient and informative monitoring methods to understand possible conservation impacts of marine mammal bycatch and to implement tailored mitigation techniques.Incidental captures (bycatch) remain a key global conservation threat for cetaceans. Bycatch of harbour porpoise  GillnetEstimating the bycatch of marine mammal species in an area requires fishing effort estimates for the fishing fleet(s) responsible for incidental captures and their respective bycatch rate estimates. Such data need to be representative of both fleet effort and bycatch rates, e.g. using randomized sampling stratification . EstimatBycatch rates in gillnets are dependent on a combination of biotic and abiotic factors such as the spatio-temporal distribution of the sensitive species and the target species, and the characteristics of the fishing gear  . The conPhocoena phocoena) is an abundant cetacean categorized globally as ‘Least Concern’ on the IUCN Red List [The harbour porpoise  (i)a).Bycatch of harbour porpoises in commercial gillnet fisheries in Denmark and Sweden was estimated using EM systems installed onboard 17 Danish gillnet vessels between 2010 and 2020. Individual vessels' monitoring varied from several consecutive months to years. The sampling area covered the most important commercial gillnet fishing grounds around mainland Denmark and Western Sweden, however not including the Baltic Proper a.Figurehttps://www.archipelago.ca/) was used on all participating vessels from 2010 and replaced in 2013 with Black Box Video . Both EM systems consisted of a control unit, associated with a position sensor (GPS) and a set of at least two waterproof CCTV (closed-circuit television) cameras recording the fishing activity. The cameras were positioned to allow (by)catch items to be observable from different angles—where the net appears from the water and at the sorting table—thus maximizing the chance of identifying target and bycatch species with certainty.Monitoring was conducted using two different EM systems. EM Observe .Each EM system came with its own analyser programme—respectively, EM Interpret  and Blackbox Analyzer (Anchorlab). These programmes show a map with the GPS trace of a vessel, alongside the videos. Trained EM analysts manually reviewed a census of the EM data to detect fishing events and bycatches. In short, EM data processing consisted of identifying each fishing event (setting and hauling of nets) and reviewing the entirety of the video data for each haul to spot harbour porpoise bycatches. Each bycatch event was marked with a timestamp recording location and time of day. Both EM analysing softwares could replay a sequence, adjust playback speed or zoom on areas of interest during the review process. Video quality could vary greatly depending on e.g. darkness, weather conditions or the general cleanliness of the camera lenses. Exceptionally, videos' feed quality was too bad to detect a porpoise bycatch event, and on such occasions ‘true’ bycatch rates would have been underestimated. However, based on the small amount of low-quality data, we considered this negligible. All EM data were saved to be reviewed multiple times if needed. A detailed protocol is available online (see  (b)Gadus morhua)—must be registered in daily-reported logbooks [In the European Union (EU), the fishing activity of all vessels above 10 m—the limit is down to 8 m in the Baltic Sea if the main target is cod . Although there are differences in reporting catches and landings between Denmark and Sweden, the gillnet fisheries in these countries share a common fishing ground and are largely similar in their fishing patterns, so we assumed that observations made in the Danish fleet of porpoise bycatch could be applied to Swedish vessels. Importantly, information from German gillnetters who also operate in the western part of the Baltic Sea was not included, as German gillnet fishing effort data are not reported at a comparable spatial and temporal scale [A census of the Danish and Swedish fisher-reported data, including all official logbooks, monthly declarations, sales notes and landing declarations, was collected for all the commercial vessels having registered set nets as their primary or secondary gear between 2010 and 2020 c. Althoual scale .ad hoc functions in the R statistical software [Danish and Swedish effort datasets were cleaned for clerical errors . We summarized the data, so that one row would correspond to a unique fishing day per ICES rectangle per vessel. When more than one mesh-size was reported for the same fishing day in the same ICES rectangle, only the mesh-size of the main target species  was kept. Electronic supplementary material, figure S1 summarizes the changes in fishing effort by mesh-size class. Soak-time was averaged out from the values reported in each stratum and net-length was calculated as the sum of all the net fleet lengths in each stratum. In the Danish data, soak-time and net-length were only readily available for the vessels monitored with EM. Retrieving these data was nevertheless essential to run the subsequent analytical modelling, so we used the vessels in the EM dataset as a reference fleet, estimated the average net-length and soak-times from the validated EM data and applied these values to the portion of the Danish fleet not monitored with EM, using expert judgement in the strata with low sampling effort . Smaller vessels for which only monthly declarations exist do not report their fishing locations, thus their fishing effort was allocated to the ICES rectangle in which their home harbour lies. Depth was estimated for each point in the datasets using a high-resolution bathymetric map and software ; for Dansoftware ,38 were  (c)The total number of harbour porpoise bycaught in the Danish and Swedish commercial gillnet fleets was estimated in two alternative ways. First, we estimated mean observed bycatch rates, stratified spatially and temporally, using EM data collected on Danish vessels  and raised these numbers to the number of fishing days in the fleet to estimate total bycatch. Next, we used the same EM data to build a statistical model to predict bycatch of porpoise from operational variables in the entire fleet and ecological variables in the surveyed areas. The results from these two approaches were then compared in terms of mean estimates and uncertainty. (i)Scaling-up observed bycatch rates to fleet-level is often used in bycatch studies . Here, w (ii)Mixed models allow for departure from independence in ecological data ,32. HereglmmTMB package to create the models and the bblme package to compare them [DHARMa package [predict in R). This was done using a modified version of the glmmTMB package that included an aggregate function (https://github.com/glmmTMB/glmmTMB/tree/aggregate), which allowed both quantification of the uncertainty and the performance of bias correction for sums of predictions on the natural scale . Bias correction is necessary because sums on the natural scale are a nonlinear transformation of the random effects in the model [https://github.com/gildas-glemarec/bias-corrected-estimates-of-harbour-porpoise-bycatch-in-gillnet-fisheries).Alternative models were compared using the Akaike Information Criterion modified for small sample size (AICc). All data treatments and analyses were conducted in R, using the are them ,40. The  package  (electrohe model . Corresp (d)As opposed to the scaling-up approach, a model-based method could account explicitly for variations in operational factors in the gillnet fishery, e.g. differences in vessel-length, mesh-sizes, or soak-time. In turn, we could explore the underlying reasons for possible trends by standardizing bycatch rates and fishing fleet effort. For this, the terms in the model formula were grouped in two categories. One group described the effect of different types of fishing effort on the amount of bycatch, i.e. vessel, mesh-size and soak-time effects, while the other group described changes in porpoise density over time and space. This separation of model terms allowed for calculating not only standardized bycatch numbers, but also standardized effort and porpoise BPUE relative to other years/areas.The standardized effort was calculated by fixing all porpoise density terms in the model to some arbitrary constant value for all years and spatial positions , and predicting the amount of bycatch given the observed effort data. The result was then proportional to the bycatch per individual porpoise for a given set of effort data, since it accounts for different values of e.g. mesh-size, soak-time and net-length having different risks of catching porpoise. Similarly, the standardized BPUE was calculated by fixing all the effort-related variables to constant values and predicting the bycatch for each year in all spatial positions.This separation of effort and porpoise density terms offers a possibility to produce spatially explicit estimates of relative porpoise densities (standardized BPUE) and relative porpoise mortality due to fishing (standardized effort) in addition to total bycatch estimates. The total bycatch is consequently the product of porpoise density and effort in each stratum . Moreover, what we refer to as ‘standardized effort’ is not necessarily indicative of the actual fishing effort but is rather the porpoise mortality induced by the fishing effort. (e)recovering to 80% of their carrying capacity in the long-term [modified PBR (mPBR) [et al. [2, 2281 km2 and 17 862 km2. Then, we estimated four threshold values (two PBR- and two mPBR-based) for each year in which an abundance estimate was available, with recovery factor values associated with uncertain estimation processes for abundance and bycatch, and with more accurate and precise estimates  = 0.5 or 1.0 for PBR, and Fr = 0.15 or 0.35 for mPBR).We estimated the potential biological removal limit (PBR) for harbour porpoise in the Western Baltic , to evaluate the sustainability of the bycatch levels in that assessment unit . There iong-term . This haR (mPBR) . Here, w [et al.  to tune  [et al. . This cl [et al. . However. 3In total, 6139 individual fishing days were recorded and analysed in the Danish EM fleet between 2010 and 2020, during which 525 harbour porpoise bycatches were observed in hauls where no pingers were used. At least one porpoise was registered as bycatch in 8.6% of the recorded fishing days. (a)id) was not retained in most models, suggesting that the bycatch rates depend foremostly on the characteristics of the fishing gears described by the fixed effects rather than on specific fishing vessel behaviour. Interaction terms generally increased model fit, with the final model retaining only the interaction between mesh-size and soak-time.The model selection  favoured a spatial autocorrelation component structure with a random variation of exponential decay in correlation with the distance within year and within quarter. This indicates that bycatch observations tend to cluster both in space and in time or, in other words, that there exist areas of higher risk of bycatch. The random variable coding for the unique vessel identifier  indicated that the most prominent contributors to porpoise bycatch were mesh-size, soak-time and vessel-length. (b)y-axes is arbitrary in the middle and bottom plots in Total porpoise bycatch estimates from model predictions were aggregated by year for two focal areas: the Western Baltic, and the North Sea and Skagerrak. These numbers were compared with the bycatch estimates obtained from scaling-up the mean EM observed bycatch rates to the entire fleet for the same two focal areas —top. UsiMean values of the bycatch estimates differed between the two methods —top. On Standardization demonstrated that, although there are important differences between the Western Baltic and the North Sea and Skagerrak focal areas, with higher mean bycatch rates in the latter —middle, Model-based estimates revealed areas and times of the year with higher risks of porpoise bycatch  and allo (c)Given the uncertain nature of the abundance estimates in 2012 and 2016, we selected the thresholds more robust to potential biases in abundance estimates for these years  reached 862 animals (238–3198) when assuming that pinger usage strictly follows the legislation and reduces bycatch by 100%, and up to 939 (206–3679) when pinger implementation is ignored . The sus. 4To the best of our knowledge, this study is the first to present fleet-level estimates of any cetacean species bycatch in commercial gillnets, correcting for fleet characteristics and using a long time series of fine-scale EM data. This work yields a model able to predict harbour porpoise bycatch from fisheries-dependent data. In the study area—the Eastern North Sea, Skagerrak and Western Baltic—2089 porpoises were predicted to have been bycaught in 2020, provided that acoustic deterrents are used according to the legislation and that they totally mitigate bycatch. Not accounting for pinger usage, we predicted 2617 bycatches in 2020 . Both esFor the Western Baltic, the estimates from model predictions showed very similar results to those using traditional BPUE extrapolation method, likely because the vessels here fish in a very homogeneous way . As the fleet is more homogeneous, the monitoring data are also more representative of the fleet, thus the two ways of predicting total bycatch yield similar outcomes. Conversely, the fishery in the North Sea is more heterogeneous, being characterized by a mixture of large and small vessels with varying fishing trip duration, and varying target species needing different net-lengths, mesh-size and soak-times. As the model accounts for these fishing characteristics, the predicted total bycatch estimates emerging from the modelled bycatch rates account for the fleet variability. The BPUE applied to fishing days assumes that all fishing days are equally likely to bycatch porpoises, regardless of fishing characteristics, which can therefore yield biased estimates when the sampling design cannot account for representativeness . This sh (a)We estimated that 939 porpoises (206–3679) were bycaught in 2020 in the Western Baltic, when no pingers are assumed to have been used . This isBased on our model predictions, 1678 porpoises (576–5074) were bycaught in gillnets in the Eastern North Sea and Skagerrak in 2020, assuming no pinger usage . This isIt is important to recall that, in this paper, German gillnet effort is not included in the estimation process, notably because of the peculiarities of fishing effort reporting in Germany, which is not standardized with other countries . This me (b)c; electronic supplementary material, figures S2 and S3). Instead, predicted high bycatch areas were associated with areas where fishing methods  are more conducive to bycatch. This has important implications for mitigation and shows that simply reducing the number of fishing days in an area of high bycatch may not be sufficient to reduce total bycatch. Our work highlights which fishing techniques should be prioritized for mitigation, once bycatch probability and fishing intensity have been accounted for .Total bycatch is not homogeneously distributed in the study area . Areas ofigure 1Our model prediction approach can help estimate how inferred relative porpoise density, fishing characteristics and fishing intensity interact to yield bycatch levels . Standardized bycatch rates  is the product of porpoise density and the bycatch probability of individuals. Our model allowed us to separate these two terms and give spatially explicit estimates of relative porpoise density, mortality due to bycatch, and total bycatch as the product of the two. Independent measures of porpoise density are therefore not necessary to estimate spatially explicit measures of relative porpoise densities and bycatch probabilities. The estimated bycatch probabilities capture the spatial heterogeneity in the species propensity to become entangled in fishing gear as the measure is standardized for fishing characteristics. This spatial heterogeneity could emerge from behavioural variance  or demographic characteristics . Regardless of causes, a spatially explicit bycatch probability estimate is an extremely useful tool to plan the best-suited mitigation methods. (c)The original EU pinger regulation and its succeeding iteration ,38 have  (d)Bycatch rate estimation depends on two important assumptions. First, the EM observed data need to be representative of the fleet in terms of area, time of year and fishing characteristics such as vessel-length and target species. Our voluntary EM observation covered most areas except the northern and central part of Kattegat and the southern North Sea . The EM All vessels participated voluntarily, and vessel crews were aware that the hauls were being monitored. There is a known tendency for fishers to shift from normal fishing practices when they know they are being observed , implyinWhen estimating bycatch using our modelling approach, assumptions had to be made about mean net-length and mean soak-time. These assumptions clearly come with errors as no fishers have exactly equal fishing patterns. However, it improves vastly on bycatch estimation methods earlier used by WGBYC, which assumes that all vessels have the same kind of ‘fishing day’ regardless of vessel-length and mesh-sizes. In all cases, this paper stresses the crucial need to have more accurate and precise national statistics on fishing effort. Key variables influencing bycatch probability  are required to derive robust bycatch estimates. In our case, although there are differences in reporting catches and landings between Denmark and Sweden, the gillnet fisheries in these countries share common fishing grounds in the Western Baltic and Eastern Greater North Sea and are largely similar in their fishing patterns, so we assumed that observations made in the Danish fleet of porpoise bycatch and resulting mean bycatch rates could be applied to Swedish vessels. (e)Regardless of threshold estimation assumptions, bycatch levels in the Western Baltic are above the threshold values estimated to yield sustainable bycatch limits. Nevertheless, PBR estimates do fall within the confidence intervals of the estimated yearly total bycatch . Yet thestricto sensu. Second, the assessment unit considered here is more open to immigration and/or movement of harbour porpoises from neighbouring regions than previously thought and is therefore ill-defined. Several hundreds of porpoises would need to immigrate yearly into the Western Baltic to maintain a stable population given the discrepancies between the estimated threshold and the level of bycatch predicted from our model. This would mean that the Western Baltic harbour porpoise assessment unit is extremely open to what is currently considered the North Sea assessment unit [This could be for two reasons. First, we could assume that the population can sustain the level of bycatch to which it is exposed, implying that the mPBR- and PBR-based threshold values are over-precautious. Regarding mPBR, this makes sense as the objective is to maintain or restore to carrying capacity a population far away from its maximum net productivity level (MNPL). In that state, the net productivity the population can achieve is much lower than MNPL, forbidding sustaining as many excess mortalities. The mPBR objective is to ensure that the population thrives, not that it cannot become depleted. For PBR, however, the objective is that the population remain at or above MNPL with high certainty. Hence, PBR estimates here are likely cautious and should be treated as reference points over which bycatch levels need greater attention rather than a threshold ent unit  as the Bent unit . In addient unit . The undTwo contrasting conclusions emerge from this work. One option is that we accept the current assessment unit. In this case, PBR is a more appropriate measure of sustainable bycatch limit than mPBR, as PBR falls within the confidence interval of the predicted total bycatch. This would mean that the alternative conservation objective (a restoration objective) first set by ASCOBANS, while well-intentioned, is not useful to guide bycatch management—in this instance at least. Under such a restoration objective, mitigation measures would likely be required from the moment a single porpoise is bycaught. The alternative is that the delineation of the assessment unit is not making sense and we need to consider large influx of porpoises from the North Sea to maintain the population and the bycatch levels observed; in which case the assessment unit needs to be merged with the North Sea one.. 5Globally, we need to prioritize the generation of fisheries statistics at a fine scale of effort. This information is crucial as we try to achieve ambitious biodiversity restoration targets while maintaining the vital food security provided by small-scale coastal fisheries .Coastal fisheries are facing rapid socioecological changes, like many other human activities in the 2020s. In the Western Baltic, gillnet fishing effort decreased significantly over the past decade , and this will most likely continue due to the current limitations on cod fishing. This will in turn yield a reduction in porpoise bycatch. Nonetheless, as cod gillnet fishers will switch to other target species, change gear, or stop fishing, the way in which changes in fishing practices and intensity will affect porpoise bycatch remains largely unknown. Furthermore, we show here that the current pinger deployment regulations are ineffective at reducing bycatch; not because pingers are not an effective tool to reduce bycatch, but because the regulated pinger deployment schedule is not targeting the vessels and instances yielding the greatest bycatch risk.


Background and objectiveChatGPT is an artificial intelligence (AI) language model that has been trained to process and respond to questions across a wide range of topics. It is also capable of solving problems in medical educational topics. However, the capability of ChatGPT to accurately answer first- and second-order knowledge questions in the field of microbiology has not been explored so far. Hence, in this study, we aimed to analyze the capability of ChatGPT in answering first- and second-order questions on the subject of microbiology.Materials and methodsBased on the competency-based medical education (CBME) curriculum of the subject of microbiology, we prepared a set of first-order and second-order questions. For the total of eight modules in the CBME curriculum for microbiology, we prepared six first-order and six second-order knowledge questions according to the National Medical Commission-recommended CBME curriculum, amounting to a total of (8 x 12) 96 questions. The questions were checked for content validity by three expert microbiologists. These questions were used to converse with ChatGPT by a single user and responses were recorded for further analysis. The answers were scored by three microbiologists on a rating scale of 0-5. The average of three scores was taken as the final score for analysis. As the data were not normally distributed, we used a non-parametric statistical test. The overall scores were tested by a one-sample median test with hypothetical values of 4 and 5. The scores of answers to first-order and second-order questions were compared by the Mann-Whitney U test. Module-wise responses were tested by the Kruskall-Wallis test followed by the post hoc test for pairwise comparisons.ResultsThe overall score of 96 answers was 4.04 ±0.37  with the mean score of answers to first-order knowledge questions being 4.07 ±0.32  and that of answers to second-order knowledge questions being 3.99 ±0.43  (Mann-Whitney p=0.4). The score was significantly below the score of 5 (one-sample median test p<0.0001) and similar to 4 (one-sample median test p=0.09). Overall, there was a variation in median scores obtained in eight categories of topics in microbiology, indicating inconsistent performance in different topics.ConclusionThe results of the study indicate that ChatGPT is capable of answering both first- and second-order knowledge questions related to the subject of microbiology. The model achieved an accuracy of approximately 80% and there was no difference between the model's capability of answering first-order questions and second-order knowledge questions. The findings of this study suggest that ChatGPT has the potential to be an effective tool for automated question-answering in the field of microbiology. However, continued improvement in the training and development of language models is necessary to enhance their performance and make them suitable for academic use. In recent years, natural language processing (NLP) and machine learning (ML) techniques have revolutionized the field of question-answering systems . ChatGPTMicrobiology is a fundamental subject in medical education and it deals with the study of microorganisms, including bacteria, viruses, fungi, and parasites. Medical students need to have a sound understanding of microbiology as it is directly related to the diagnosis and treatment of infectious diseases . CompeteAutomated question-answering systems have the potential to transform medical education by providing instant and accurate responses to complex questions . The useIn light of this, in this study, we aimed to evaluate the performance of ChatGPT in answering first- and second-order knowledge questions related to microbiology. This could aid in the development of effective educational tools that can help medical students master the subject of microbiology. The results of this study could also shed light on the strengths and weaknesses of ChatGPT as an automated question-answering system with regard to the field of microbiology and pave the way for further research in this field.Study design and settingThis cross-sectional observational study was conducted by the department of Microbiology, Pathology, and Physiology, All India Institute of Medical Sciences, Deoghar, Jharkhand, India in February 2023. We used an online AI language model - ChatGPT - to converse with and the responses were collected for analysis. The program is free for registered users at this point in time.Ethical considerationThis study does not involve any human or animal research participants. Responses generated by the language model were not shared in this paper. Hence, according to current guidelines in the country, this study does not require any ethical clearance.Question preparationAccording to the CBME curriculum for the subject of microbiology, we prepared a set of first- and second-order questions. The researchers prepared a total of 96 questions, with six first-order and six second-order knowledge questions for each of the eight modules, as shown in Table Data collectionThe questions were used to converse with ChatGPT by a single user. The responses were recorded for further analysis. We did not use the “regenerate response” and took the first response to be the final answer.Scoring of answersThe responses generated by ChatGPT were scored by three microbiologists. The scoring was done on a rating scale of 0-5, where 0 indicates an incorrect answer and 5 indicates a fully correct answer. The average of the three scores was taken as the final score for each response. The brief study protocol is depicted in Figure Having multiple evaluators to assess an answer can help reduce biases and increase the accuracy and reliability of the evaluation. Different evaluators may have different biases based on their personal experiences, perspectives, or preferences. Having multiple evaluators can help mitigate these biases. Hence, we employed three evaluators to reduce biases.Statistical analysisAs the data were not normally distributed, non-parametric statistical tests were used for analysis. The overall scores were tested using a one-sample median test with hypothetical values of 4 and 5. The scores of the first-order and second-order knowledge questions were compared using the Mann-Whitney U test. The module-wise responses were tested using the Kruskal-Wallis test, followed by the post hoc test for pairwise comparisons . All theThe overall mean score of 96 answers was 4.04 ±0.37 . The frequency distribution of scores of 96 answers to both first-order and second-order knowledge questions is shown in Figure The mean score of the answers to first-order knowledge questions was 4.07 ±0.32 , and that of answers to second-order questions was 3.99 ±0.43 . The scores for answers to first- and second-order knowledge questions were similar (Mann-Whitney p=0.4), as shown in Figure The score was significantly below the score of 5 (one-sample median test p<0.0001) and similar to 4 (one-sample median test p=0.09), indicating an accuracy rate of 80%.The highest score was obtained in the central nervous system infections category 4.25±0.27) and the lowest score was obtained in the gastrointestinal and hepatobiliary systems category (3.75±0.36). The competency topic-wise distribution of scores is shown in terms of descriptive statistics in Table 5±0.27 anWhen we compared the scores among various categories according to CBME, we found that there was an overall difference (p=0.02) among the scores, indicating that the application's performance may vary in different topics in microbiology. The comparison is shown in Figure Based on our findings, ChatGPT is capable of providing answers to both first- and second-order knowledge questions with approximately 80% accuracy. This corroborates the findings of Sinha et al . There wAcross different competency modules, the score was significantly different. The highest score was found for questions related to central nervous system infections and the lowest score was obtained in the gastrointestinal and hepatobiliary systems. The underlying cause may be attributed to the limitation of training the AI system. Any deviation from the uniformity of difficulty may be another reason for the different levels of performance of the language model. Hence, there is scope for further improvement of the model to make it more suitable for academic usage. The applicability of language models like ChatGPT in academic usage is wide-ranging and constantly expanding, and they can be used to enhance various aspects of academic work, including research, writing, teaching, and learning ,13.This study has certain limitations. We only evaluated the capability of ChatGPT in answering first- and second-order knowledge questions on the subject of microbiology, and the findings may not be generalizable to other subjects or domains. Secondly, the study only used a single user to converse with ChatGPT. Conversations with another user at different time points may generate a different response. Furthermore, paraphrasing the questions showed variations in the answers. The scoring of the responses was subjective; hence, evaluation bias may be present even after taking the average of three scores from three evaluators.The study showed that ChatGPT is a potential tool for answering both first- and second-order knowledge questions with equal vigor in the field of microbiology. The accuracy rate of approximately 80% indicates that ChatGPT has the capability to be a valuable automated question-answering system for students. Although the model showed high accuracy, there is still room for improvement, and it is necessary to fine-tune the model to enhance its performance to achieve nearly 100% accuracy. In the future, with further improvement, ChatGPT-like programs may be used for academic purposes.


Dynamically controlling friction in micro- and nanoscale devices is possible using applied electrical bias between contacting surfaces, but this can also induce unwanted reactions which can affect device performance. External electric fields provide a way around this limitation by removing the need to apply bias directly between the contacting surfaces. 2D materials are promising candidates for this approach as their properties can be easily tuned by electric fields and they can be straightforwardly used as surface coatings. This work investigates the friction between single layer graphene and an atomic force microscope tip under the influence of external electric fields. While the primary effect in most systems is electrostatically controllable adhesion, graphene in contact with semiconducting tips exhibits a regime of unexpectedly enhanced and highly tunable friction. The origins of this phenomenon are discussed in the context of fundamental frictional dissipation mechanisms considering stick slip behavior, electron-phonon coupling and viscous electronic flow. Electric fields achieved by applying electrical bias directly between the sliding surfaces are commonly used to tune friction. Here, the authors reveal that friction between graphene and a semiconductor is sensitive to the charge density of graphene while influenced by an indirect electric field. The ability to control the friction force at the sliding contact relies on understanding the underlying mechanisms. Beyond the passive control of friction through the selection of the design components , a more recent trend has been to investigate systems whose frictional response can be dynamically tuned in situ, especially as micro- and nanoscale devices become more common. One of the more promising avenues to achieve friction control is through the use of external electric fields that can modulate the properties of lubricants and material surfaces as well as the interactions between them4.Novel approaches to the design of interacting surfaces are necessary to move past the current state of the art, and 2D materials are a new and excellent material choice based on their high mechanical strength and chemical and thermal stability. Many 2D materials exhibit intrinsically low friction and are additionally interesting as they can be tuned or doped. This doping effect can be achieved in the traditional sense of atomic substitution, through interactions with the material’s environment , or through the application of external fields. Graphene, the 2D allotrope of carbon, has been widely studied in this context. Specifically, the graphene field effect transistor (FET) is a common device used to dynamically alter the sheet’s properties in situ. FET devices are constructed such that a voltage is applied to a gate that is electrically insulated from the material of interest. This leads to an indirect effect controlled by the resulting electric field, instead of the direct application of bias to the surface. This has the additional advantage that short circuits can be avoided, which protects machine components and lubricants. It is important to point out that while traditional FETs are designed to be turned on and off, graphene FETs exhibit a gradual response due to graphene’s unique band structure7. Prior research has also investigated the electronic contribution to friction for semi- and superconductors as their carrier density was modified11. Friction between a tip and doped semiconductor substrates was shown to vary with the local carrier concentration; here, a charge depletion (accumulation) resulted in a substantial decrease (increase) in friction11. While the contribution of electron wind, charge carrier dragging, and fluctuating electric fields was estimated to be negligible for gallium arsenide covered with an oxide layer11, the charges trapped in the near-surface layers were responsible for the electrostatically-induced adhesion that justified the variation of the friction force11. These studies demonstrated the relative importance of factors such as charge density and carrier concentration as well as the electrostatic interaction between the two surfaces. Measurements of nanoscale friction on 2D materials with varying in-plane bias have also shown that applying an increasing bias can decrease the measured friction. This has been primarily attributed to a change in the atomic stick-slip behavior and therefore to the frictional dissipation process12. A recent investigation of indirect out-of-plane bias to control carrier concentration via an electric field in a semiconducting MoS2 system associated changes in friction to effects on the electron-phonon coupling13. These previous studies were performed under ambient conditions, and hence, the effects of water traces on the results cannot be excluded. Similar effects have not been investigated for graphene either under out-of-plane or indirect bias yet, particularly through the lens of controlling graphene’s charge density.Previous works have reported the effects of an electric field between an atomic force microscopy (AFM) tip and semiconducting or graphene surfaces—between which a varying bias was directly applied—on adhesion and friction but have focused on revealing the role of water in humid environmentsIn this work, we study the friction at a single asperity nanoscale contact between the graphene surface of graphene FETs and an AFM tip in a dry nitrogen atmosphere, while the doping level of graphene is modulated in situ by changing the potential applied to the device’s back gate. In contrast to conducting or insulating contacts, graphene in contact with semiconducting tips exhibits an enhanced and tunable friction sensitive to the charge density in graphene.2 dielectric layer, and degenerate silicon backgate. Details of sample preparation are described in the Methods section. Raman spectroscopy on the annealed graphene FETs revealed monolayer characteristic peaks (IG/I2D < 0.5) and marginal D peak intensity  microspheres or thermally oxidized Si tips with a thick oxide layer. Insulating tips do not transfer any charge upon contact with graphene. Reference AFM measurements were carried out on 300 nm SiO2 on Si wafer and 50 nm Au-coated Si wafers, which are labeled as insulating and conductive surfaces, respectively. More information about the experiments is found in the Methods section.Three different tip types were used in AFM measurements on the graphene FET devices. Sharp Si tips used directly as supplied by the vendor are referred to as either unmodified or Si tips. Si tips are covered by a thin oxide layer upon exposure to ambient air2) surface  are shown in Fig. ips Fig.  increaseFigure 20, potentially justifying the difference between the local minimum of The electrostatic attraction between graphene and Si tips Fig.  exhibitscf. to reference silica and gold surfaces in Supplementary Fig. X axis shows the potential difference 2 surfaces , the variation of friction with entclass1pt{minimange Fig. , inset. Friction measurements on graphene with Si tips are summarized in Fig. When friction is plotted against ial Fig. . If the Reference measurements on silica surfaces with Si and conducting tips show the same trends as with insulating tips  is roughly half of the CoF, indicating that friction at contacts with minimal charge transfer is more influenced by a varying normal load than a change of electric field. Moreover, this eCoF0 is overestimated based on the magnitude of electrostatic attraction at the distance it is necessarily measured vs. the magnitude in contact . The average value of eCoF1 is comparable to, if not slightly larger than, eCoF0, which indicates that the Si tips act similarly to purely insulating tips in this range. Above the Dirac point, there is a sharp increase in the coefficient of friction (eCoF2 > eCoF1). This value is on average larger than the CoF or eCoF for any other system, suggesting an outsized dependence of friction on the electric field. This frictional response happens when the deviation of the electrostatic attraction before and after contact is observed  and might be partially responsible for the irregular slip features.Figure 25. In this context, the AFM tip is connected by a spring to a moving support that drags the tip with constant velocity over a periodically varying potential landscape 26. Careful analysis of the stick slip reveals a mixture of single and double slips, with more double slips with increase in 27, and hence, they should contribute to the increase of the frictional force with The Prandtl-Tomlinson (PT) model for atomic-scale friction of crystalline surfaces attributes the microscopic origin of the energy dissipation to the stick-slip motion of the tip, where the slip length depends on the dimensions of the crystal lattice28. The results show the monotonic increase in G band energy with −1), while the linewidth is reduced (−1). The smaller linewidth above the Dirac point implies a longer phonon lifetime, which is linked to the increased electron density in n-type doped graphene. While the linewidth quickly plateaus at its reduced value after crossing the Dirac point the monotonic increase of the G band energy continues after crossing the Dirac point; this indicates that a stronger electron-phonon coupling exists in n-doped graphene compared to p-doped graphene and continues to become stronger further past the Dirac point. Note that a previous work showed a symmetric variation of the G band energy and linewidth around the Dirac point, but this was at much lower temperature. At room temperature, asymmetric responses of the G band, similar to our results, have been reported29.A graphene microFET sample with a Dirac point 9. To exclude the influence of thermal effects arising from the applied backgate potential, time-dependent Raman spectroscopy was conducted; experimental details and results are described in the Supplementary Discussion of Supplementary Fig. Both phononic and electronic contributions to friction have been also shown to be temperature dependentIn summary, AFM measurements were carried out on graphene FET devices, while the electric field modulated the charge carrier density in graphene. These results demonstrate the prominent influence of the charge transfer across graphene-tip single asperity contacts on the frictional response. When using insulating tips, charge transfer is minimized; the electric field leads to a large electrostatic attraction, and friction scales linearly with this attraction, with a hysteresis due to the effect of trapped charges. Insulating tips thus enable to tune friction via the electric field, in the same way as directly controlling the tip-sample voltage. The electrostatic attraction is eliminated in gold-coated tips due to their conductive nature, allowing charge transfer upon contact, which counteracts the polarization and significantly reduces the dependence of friction on 31. Raman spectroscopy  sea or flow, while sliding. The carrier density within graphene is modulated by 2 s−1 at finite carrier density, can be speculated to be analogous to the viscosity of a fluid, hence, to impose a resistance to the motion of the AFM tip, which increases friction, and more so with the increase in sliding velocity. The friction of nanoscale systems in fluids is often interpreted in terms of sliding through a rate-dependent potential energy surface, a model adapted by Bell and Eyring37. The analysis of An alternative or complementary explanation is based on the description of the charge carrier flow in high-mobility graphene via a hydrodynamic approachmentclasspt{minima38. A study of metal-supported graphene in a conductive AFM demonstrated that current transfer while sliding is associated with higher friction than sliding with no current across the interface, both under an electric field39. These authors also observed an enhanced friction not fully explained by changes in the electrostatic attraction. In their fully conductive system, they invoke an electronic property fluctuation model that assumes changes in friction are influenced by both an altered electron density at the interface and the promotion of charge transfer between the sliding surfaces due to the electric field. Similar to the present work, these changes are invoked in the context of the PT model, with both the electron density redistribution and charge transfer leading to an enhanced energy barrier for sliding. Our stick slip measurements do suggest a change of the potential energy landscape when charge transfer occurs, but unfortunately the current across the sliding interface cannot be measured in situ due to the electronically floating semiconducting (Si) tip. So, while we cannot definitively say this for our system, another potential explanation is that the measured excess friction is also influenced by the magnitude and rate of charge transferred between the tip and graphene, which change depending on the tip material, graphene’s doping state, and the quantity of induced trapped charges at the interface. The Si tips are more sensitive to these factors than the other two tip types representing the extreme possibilities of charge transfer, and charge transfer can be encouraged, discouraged, and rate-controlled depending on the charge density in graphene and the material properties of the countersurface, an AFM tip in our case. The interplay between triboelectric currents and the field effect, particularly in semiconducting contacts, thus presents a route for further experimental investigation into electronic contributions to nanoscale friction.Looking at electronic effects of a slightly larger scale, recent work also performed using AFM has associated increased friction with large tribocurrents across the sliding interface of chemically modified semiconductorsFrom a device and application perspective, the use of electric field in comparison to electric bias eliminates the need for any direct current flow between the two contacting surfaces and allows energy-efficient operation of friction tuning. Furthermore, our results with graphene also open up opportunities for tunable friction in 2D semiconductor materials-based FET devices where distinct on/off states can be achieved with single polarity charge carriers.2, Sigma Aldrich) on 35 μm-thick copper foil at 6000 rpm for 30 seconds, followed by baking on a hot plate at 110 °C for 2 minutes. Backside graphene was removed by oxygen plasma treatment (500 W for 10 seconds). Then, PMMA-coated graphene/Cu was floated on a sodium persulfate solution  for 3 hours to completely etch away copper film. The PMMA/graphene was rinsed by immersing into a DI water bath several times and transferred to target substrates, including 300 nm-thick SiO2/Si wafers (UniversityWafer) or metal-coated silicon wafers . After overnight drying, the PMMA layer was removed by soaking in acetone bath. Graphene was then annealed in a quartz tube furnace at 350 °C for 4 hours under Ar/H2 flowing atmosphere to enhance graphene/substrate adhesion and to eliminate polymer residue on graphene surface. After graphene annealing, source/drain electrodes were prepared using silver paste on both sides of the graphene channel. The fabricated graphene FETs were stored in a vacuum desiccator to prevent degradation and adsorption of water and airborne contamination. The quality of the graphene FET device was confirmed by Raman spectroscopy  using a 532 nm excitation laser and 2400 l/mm grating. For the electrical characterization, we used a 2-channel sourcemeter . Constant source-drain bias was maintained at 50 mV (for continuous sweeping) or 1 mV (for discrete sweeps), while the gate bias was swept from 0 V to 30 V (in continuous sweeps) or to 100 V (discrete sweeps). The effect of different atmospheres (dry nitrogen and air) on I-V curves of the graphene FET devices was separately examined and compared to vacuum conditions using a vacuum-controlled probe station .Graphene FET devices were fabricated by transferring chemical vapor deposition (CVD)-grown graphene to the target substrate. Poly(methyl methacrylate)  was spin-coated on graphene (grain size ~5 μm40. Three different tip categories were used in AFM measurements. The first is referred to as Si (unmodified) tips. These are sharp tips as-provided by the manufacturer . The tips are made of n-doped silicon with a typical normal spring constant of ~0.3 N/m and nominal tip radius of 8 nm. The second category of tips is referred to as conducting tips. These are Si tips coated with 5 nm Cr followed by 50 nm Au using an e-beam evaporator . The third tip type is referenced as insulating tip. These are either colloidal silica microspheres  with nominal radius of 5 µm that have been manually glued to tipless cantilevers  or Si tips that were thermally annealed in ambient atmosphere to induce the growth of a thick oxide layer. There was no significant difference between the AFM results conducted with these two types of insulating tips . All measurements were performed in a constantly refreshed dry nitrogen atmosphere  in order to exclude the effects of air humidity and water adsorption. AFM tips had a nominal normal spring constant of 0.3 N/m. Normal spring constants for each cantilever were measured using the Sader’s method42. Friction is averaged along each scan line. Ten scan lines are taken at the same conditions and each single data point results from the average of the ten scan lines. The lateral spring constant is estimated using the thermal noise method43.Friction measurements were performed as a function of the applied load at constant sliding velocity of 1 µm/s and as a function of sliding velocity at constant load (5 or 10 nN), while the backgate bias was maintained constant at a selected value. The gate bias was varied in steps of 10 V from 0 to 100 V, first increasing and then decreasing. All friction scans were performed along a 100 nm line on a flat area of the graphene free from visible contamination. The friction force was calculated from the lateral deflection signal during sliding. A single scan line consists of a trace and retrace line, and friction is calculated by subtracting the retrace from the trace lateral deflection and dividing by two40. The adhesion between tip and graphene is given by the measured pull-off force (the difference between the out-of-contact baseline and the lowest point on the retraction curve), and the values and error shown are the average and standard deviation for five repeated measurements at each held backgate voltage. Adhesion measurements were performed across multiple tips, samples, and locations on samples to ensure qualitative and quantitative reproducibility.The measured vertical deflection of the cantilever at a separation from the surface of 3.5 µm yields the non-contact interaction between tip and surface, and as described in Results is of electrostatic origin. The vertical deflection is recorded before the power source applying the gate voltage is turned on. The deflection towards the surface from this baseline is considered a positive value for the electrostatic attraction. Each value is the average of approximately five seconds of measurement of deflection, and the small error bars are the standard deviation over these 5 seconds  images of an unused tips and of the same tip used only for initial calibration procedures (approach to surface in nitrogen atmosphere and ~5 force curves at a 20 nN or less setpoint) demonstrated that this tip damage, indeed, happened during calibration. Supplementary Fig. The wear of both the surface and AFM tips needs to be avoided and/or accounted for to ensure reliable analysis of the measured friction. To exclude the influence of surface wear on AFM results, the investigated areas were imaged both before and after sliding friction; any measurements with changes after measurement in topography, adhesion (images collected in QI mode), or lateral deflection (in contact mode) were not considered. Tip wear (and/or breakage) is also of concern, particularly for sharp Si tips, as unexpected changes in tip geometry and contact area can have noticeable effects on tip-sample interactions. An increase in radius has been previously reported for sharp AFM tips2 films leading to RMS roughness ~200–300 pm and peak-to-valley roughness of 1–2 nm for most 100 nm2 areas, which may interfere with the measurement of the atomic stick slip. Hence, graphene/hBN/SiO2 FET devices were fabricated to provide smoother surfaces  for stick-slip measurements. First exfoliated hexagonal boron nitride (HQ Graphene) flakes were exfoliated on a clean SiO2/Si wafer using scotch tape. Thin flakes of hBN were found in optical microscope based on the color contrast to the substrate. Target thickness of hBN ranged from 10 to 30 nm, as measured by AFM . Pre-annealing of exfoliated hBN/SiO2 samples was carried out at 400 °C for 3 hours in 50 sccm Ar flow in order to remove the tape residue and improve the adhesion between hBN and SiO2. Then, CVD-grown graphene was transferred on hBN/SiO2 substrate similar to the macrochannel graphene FET fabrication process, described earlier. The presence of hBN underneath graphene resulted in increased number of nanobubbles/blisters trapped at the interface of graphene and hBN, which was observed by dark-field optical microscopy. Subsequent annealing at 350 °C for 4 hours in Ar/H2 atmosphere  substantially reduced the density of trapped bubbles in graphene/hBN. Because of the limited areal fraction of hBN flakes to SiO2 substrate, no substantial changes in charge transport characteristics were observed compared to graphene/SiO2 FET devices.Graphene conforms to SiOStick-slip data shown in the main text were collected using the same JPK AFM previously described, while the data shown in the SI were collected using an Asylum Cypher system  in lateral force mode, both with purged nitrogen atmosphere. All experimental conditions  were the same as previously described. The same unmodified sharp tips as previously described were also used for all stick-slip measurements. New tips were used for every new measurement attempt to ensure a radius of 10-20 nm. Suitable hBN flakes were found using each system’s optical microscope, followed by minimal AFM imaging of the graphene on hBN  to find suitably flat and clean areas. For these measurements in both systems, a 10 nN load was applied while the tip was dragged over a 100 nm scan line at 20 nm/s for 3–5 repeated scans. Stick-slip was found to be more reliably measured at this scan speed using relatively low gain values, the software default for both instruments.Supplementary InformationPeer Review FileSource Data


Patient education has been transformed using digital media and online repositories which disseminate information with greater efficiency. In dermatology, this transformation has allowed for patients to gain education on common cutaneous conditions and improve health literacy. Xanthelasma palpebrarum is one of the most common cutaneous conditions, yet there is a poor understanding of how digital materials affect health literacy on this condition. Our study aimed to address this paucity of literature utilizing Brief DISCERN, Rothwell’s Classification of Questions, and six readability calculations. The findings of this study indicate a poor-quality profile (Brief DISCERN < 16) regarding digital materials and readability scores which do not meet grade-level recommendations in the United States. This indicates a need to improve the current body of educational materials used by clinicians for diagnosing and managing xanthelasma palpebrarum. The utilization of digital applications in healthcare serves an imperative role in the physician–patient relationship . Mobile Xanthomas are common well-circumscribed deposits of lipids that may be found in skin, tendons, or fasciae . They prThis study did not require Institutional Review Board approval as all data utilized in this study is available for public use and did not involve human or animal subjects.Inclusion criteria for extracted articles required them to provide pertinent information regarding xanthelasma palpebrarum. This was determined by the screeners after a joint education session on medically accurate and relevant information for xanthelasma. Additionally, articles were evaluated for the following: (1) Written in the English language; (2) Contained over 200 words; (3) Content was publicly available without the need for a content subscription; (4) Content was pertinent to providing information on the search query of interest. Articles were excluded if the associated access link was nonfunctional, a duplicate of a previous link, or did not meet further inclusion criteria .Additionally, frequently asked questions and associated online articles regarding xanthelasma palpebrarum were investigated using publicly available data from May 2023 using the Google RankBrain  machine learning algorithm after the application of inclusion and exclusion criteria. This algorithm was specifically utilized via the search engine function of Google ,17. The ® .After questions and articles were extracted, two independent raters evaluated questions for Rothwell’s Classification of Questions. Regarding extracted articles, their content was further reformatted into plain text on Microsoft Word ,21,22,23n = 24). Upon subclassification, questions regarding “Technical Details” were most common at 70.0% (n = 21) followed by questions regarding cost at 6.7% (n = 2) and timeline of recovery at 3.3% (n = 1). Following this category, questions were next classified as “Policy” at 13.3% (n = 4). Upon subclassification of the “Policy” category, all questions pertained to the risks and complications of xanthelasma palpebrarum. The least common classification of questions was “Value” at 6.7% (n = 2). Upon subclassification of the “Value” category, questions regarding “Evaluation” and “Pain” were found at 3.3% each . The source of questions and articles was most commonly a “Commercial” source at 40% (n = 12). This was followed by the source “Medical Practice” at 26.7% (n = 8), then “Government Website” at 20.0% (n = 6). Furthermore, sources from “Academic Institution” and “Media Outlet” were the least common at 6.7% each   . The intp = 0.17).Regarding assessment of the quality of websites, the Brief DISCERN instrument implemented a maximum score of 30, and the average Brief DISCERN of this analysis was 9.3  . The graThis study aimed to describe the content, readability, and quality of publicly available digital educational resources on xanthelasma palpebrarum ,27. UtilAdditionally, the findings of our readability calculations provide further explanation for the findings of Rothwell’s Classification of Questions in this study. The use of Rothwell’s Classification of Questions was implemented to categorize the frequently asked questions regarding xanthelasma palpebrarum. Specifically, this tool served to understand the specific components of xanthelasma palpebrae that patients’ inquiries focused on. Rothwell’s classification was implemented in previous literature which used internet-based public resources in clinical medicine, but to the best of our knowledge, this has not been utilized for xanthelasma palpebrae before ,38. The Brief DISCERN was implemented as the third tool  to address the aim of this study. Specifically, this tool has been validated to serve as a threshold marker for quality, evidence-based information. However, this dataset of educational materials of xanthelasma palpebrarum was classified as low quality for most resources, regardless of source . Only two resources were classified as good quality. Specifically, the Brief DISCERN tools observe deficits in the clarity of references used, addressal of the associated question, and sources of support. This tool categorizes these materials to be of low quality, in addition to the low readability found in this study ,42,43,44To our knowledge, this was the first cross-sectional study that analyzed the quality, readability, and content of patient educational materials of xanthelasma palpebrarum. Given this study is the first in addressing this aim, it is not without its deficits that can be addressed in future studies. For example, this study implemented the use of the RankBrain algorithm. This tool has been utilized in previous literature, and Google’s search engine share of the internet is greater than other engines by over 90% ,46. HoweXanthelasma palpebrarum may indicate underlying chronic diseases which significantly contribute to general morbidity and mortality, such as dyslipidemia. Patients with xanthelasma are turning to the internet for education on this condition. This study implemented tools established in the literature to profile the quality, readability, and content of patient educational materials on xanthelasma palpebrarum. The overall profile of these materials is poor and requires dissemination of higher-quality materials. This finding is important for clinicians when aiming to educate their patients on this condition. Moreover, we recommend that clinicians involved in the diagnosis and management of xanthelasma palpebrarum educate their own patients directly in the clinical setting to circumvent the currently poor profile of online educational materials. Thereby, patients may rely on their providers for healthcare literacy as opposed to unreliable online sources. Furthermore, we aim to repeat this analysis for another serious or high-burden disease.


These findings are confirmed through various spectroscopy and surface characterization techniques. Controlling flake size, thickness, and yield are demonstrated via optimization of the sonication process, centrifuge time, and H2SO4 pretreatment.Graphene is a 2D material with promising commercial applications due to its physicochemical properties. Producing high-quality graphene economically and at large scales is currently of great interest and demand. Here, the potential of producing high-quality graphene at a large scale via water-phase exfoliation methods is investigated. By altering exfoliation parameters, the production yield of graphene and flake size are evaluated. Pretreatment of the precursor graphite powder using acidic solutions of H Additionally, it has high electron mobility in the range of 10,000–50,000 cm2 V−1 s−15 and excellent thermal conductivity of above 3000 W/m K8. These superior properties allow graphene to be used in a range of applications, from drug delivery and chemical sensors to energy absorption and flexible electronics. Recent exciting applications include 3D printing of graphene-reinforced metal matrix composites for tailored properties that involve enhancing the mechanical or electrical properties of the metal matrix9. Graphene’s attractive ability to be used as a reinforcing material was also seen in lightweight cement composites where the compressive strength and specific energy absorption were increased significantly10. Further, graphene’s unique nanostructure allows it to be used as a robust material platform for quantum computing13. Another potential application of graphene is in membrane technology for water desalination15.The discovery of graphene and its remarkable properties has fascinated the scientific community. Single-layer graphene (SLG) has exceptional mechanical properties, with a Young’s modulus in the order of 1 TPa16 and the mass-scale production of high-quality graphene in an economical way. In fact, graphene commercialization has been inactive in the past decades due to the issues related to the supply chain in providing high-quality and reliable graphene material. Regardless of all the challenges, a sharp increase in graphene use in commercial products in recent years has been observed and is predicted to grow significantly in the coming years18. Finding an easy-scalable technique to produce graphene is now, therefore, more important than ever.Despite having remarkable properties and promising applications, the commercialization of graphene has been rather slow, mainly due to the zero-band gap nature that hinders graphene from being integrated into the semiconductor industry20. On the other hand, a plasma enhanced CVD (PECVD) process could provide monolayer to few layers terminated 3D graphene sheets22. However, a major issue in using CVD/PECVD was in the production cost and the mass scale production inefficiency in a reasonable amount of time. Recently, few groups have attempted to overcome such problems by inducing roll-to-roll concept for continuous production of graphene23. Despite the lab-scale success, commercially, it remains a challenging issue. The production up-scaling of the roll-to-roll (R2R) method is limited by the efficiency in the change of the carbon phase, complexity of infrastructure, need for high temperature, and high vacuum25. Slow manufacturing and high equipment costs are also considered as the major bottlenecks for the mass production of graphene using the R2R method26. In parallel, several graphene exfoliation routes from bulk graphite material are investigated and explored. A few examples are graphene exfoliation using layer engineered method27, electrochemical exfoliation process29, laser ablation method30, liquid phase exfoliation method32, etc. Out of the aforementioned methods, liquid-phase exfoliation (LPE) has been a popular approach for graphene synthesis due to its straightforward nature in processing, synthesis, and inherent capability for mass-scale synthesis at a relativity low cost. LPE works by extracting graphene from graphite by overcoming the interlayer van der Waals force for mass-scale graphene synthesis33. This can be done by applying ultrasound to produce a few layer-multilayer graphene sheets at a large scale35. Additionally, the process is economical and is a potential route to produce high-quality graphene for commercial applications36.A promising route to synthesize large-scale, high-quality monolayer to few layers graphene is via chemical vapor deposition (CVD) approaches35. The solvent choice38, sonication mode39, time, and power could be considered as the critical parameters in this case. By tuning these parameters, properties, including graphene dimension and thickness, can be altered for the desired application. The use of the exfoliation method needs to be better understood so it can be used on a larger scale.Despite recognizing LPE as a low-cost graphene production method, there are still various critical parameters that could control the quality of the exfoliated graphene39. However, mostly, few-layer nanosheets of approximately 1–10 monolayers are regularly produced40. Furthermore, the sizes range between 10 nm and 10 µm41. Nevertheless, this method allows for an easier scale-up for industrialization, making it highly important to refine. Therefore, by exploring ways to ease the exfoliation process between the layers, such as introducing functional groups44 in a simple and economical way to reduce the van der Waals force between the layers, the process can become extremely efficient.The LPE process still needs to be polished to produce a few layers of graphene characterized by a uniform and intact size. Furthermore, the flake thickness and size distribution of the produced flakes ranges greatly for liquid phase exfoliated graphene. It has been observed that this exfoliation method could give nanosheets of thickness of approximately 1–2 nm46. The use of water as a liquid phase exfoliation medium using probe sonication with acid pretreatment has not been widely studied. Morton et al.47 analysed in-depth the degree of exfoliation, quality, and stability of graphene exfoliation in a mixture of water and ethanol. Tyurnina et al.48 focused on ultra-sound assisted LPE technique using a dual frequency approach in pure water. Further assessment to analyse the optimum solution temperature was done by the same group to highlight the importance of temperature and its effects49. Gao et al.50 designed a novel cyclic ultrasound-assisted exfoliation apparatus that utilized cavitation due to abrupt pressure fluctuations from water bubbles. Kim et al.51 utilized a bath sonicator to exfoliate and disperse 2D materials and found that the dissolution of graphite in water would be around 40 °C. These studies have shown the promising nature of using water as a potential solvent for graphene exfoliation and its vast area of optimization.The use of pure water as a medium for LPE can be very suitable as using deionized (DI) water helps to avoid any foreign chemical , which could be unfavorable and adds an additional task to remove them during the post-process part. Additionally, synthesizing powder material with inherent morphology of the synthesized material using freeze drying adds further advantage with water solution. The exfoliation of graphene sheets in water is highly desirable as the formation of small active cavitation bubbles in water can stimulate the exfoliation as well as support a stable dispersionIn this work, we have systematically investigated the graphene exfoliation in deionized water using the probe sonication method. The impact of pretreatment role of bath sonication in acid solution and the effect of centrifuging process has been explored.2SO4 : 3 M and 5 M were considered for the pretreatment process. The bath sonication method was carried out at a continuous ultrasonic frequency of 40 kHz for 60 min. The sonication was carried out at room temperature (RT) water. However, during the experiment, the bath temperature was observed to increase, which was then flushed with RT water while pausing the sonication process. The temperature variation was kept within 5–7 °C. Probe Sonicator manufactured by Hielscher Ultrasonics GmbH (UP400St) was implemented to homogenize and exfoliate the graphene flakes. The Sonotrode was made of Titanium with an amplitude ratio of approx. 1:2.55, Ø14 mm (173 mm2), and an approximate length of 100 mm. The pulse sonication was performed at 57 W, 40% continuous, and 28% Amplitude parameters.Commercially available high-quality graphite powder (IMERYS: Graphite & Carbon) was used as a source material for the exfoliation. The median particle size reported by the manufacturer was 17 µm. Two different molar concentrations of HA centrifuge model Sigma 3-18K manufactured by Sigma Laborzentrifugen GmbH was used to separate the graphene thin layers from the thicker layers. The centrifuging step was carried out at 5000 rpm in a swinging type rotor at a g force of 4332*g and at a temperature of 19 °C for different duration of time. The tool that we have been using is a refrigerated centrifuge type (Sigma 3-18K). The refrigerated centrifuges counteract the temperature fluctuations that could occur during the centrifugation process. Additionally, we have not observed any noticeable fluctuation in the set value in the temperature monitor. Samples (a few drops from the top portion) were collected at different intervals of the centrifuging time of 0 min, 15 min, 30 min, 60 min, 120 min, and 180 min for characterization and analysis of the exfoliated flakes.Various characterization tools were employed to evaluate the quality of the exfoliated graphene layers. As a first step, a scanning electron microscope (SEM) (Scios 2) manufactured by ThermoFisher Scientific was implemented to have an initial understanding of the particle size and morphology. The tool, also equipped with an energy dispersive spectroscopy (EDS) detector manufactured by Oxford Instrument (Ultim Max 40), was used for compositional analysis. The crystalline nature of the pristine graphite powder was assessed by X-ray diffraction . Additionally, a Raman microscope (LabRAM Soleil) was used with an excitation laser of 532 nm. X-ray photoelectron spectroscopy (XPS) analysis was performed using a PHI 5000 VersaProbe Scanning X-ray Photoelectron Spectrometer. The system was equipped with a monochromated Al X-ray source (1486.6 eV) which was used as a probe for the experiments. Further, transmission electron microscope (TEM) images were collected using a Titan G2 model (ThermoFisher Scientific) to evaluate the thin flakes. Atomic force microscopy (AFM) was also used to analyze the thickness of the exfoliated thin layers. The AFM measurements were conducted in tapping mode using a Jupiter-XR system manufactured by Asylum Research Oxford Instruments. The scan rate was set to 1 Hz, with a high setpoint of ˂ 500 mV. The absorption study of the solutions was carried out in a PerkinElmer LAMBDA 1050 + UV–Vis–NIR spectrometer.40.Figure 40. On the contrary, the pulse mode can reduce sample heating if proper cycle times are used. It is worth mentioning that the probe sonication process also produces strong convection of the solution/medium. Since we have been using a lab scale beaker in our experiments, the observed convection is strong enough to distribute the temperature rise (produced by the probe tip) within seconds throughout the solution/medium. The probe induced temperature rise was then mitigated by keeping the dispersion in ice bath, replenishing the ice every two hours. Additionally, air flow at ~ 19 °C and 0.5 m/s was kept during the process as a further measure to keep the temperature rise in check. Hence, in the current study pulse mode with proper amplitude and cycle was implemented. Gradually, intermediate steps of acid treatment and centrifuging were integrated.Probe sonication was performed in continuous and pulse modes. Pulse mode was found to be a more efficient exfoliation method to produce graphene flakes compared to continuous sonication. The continuous mode quickly raised the temperature of the sample dispersion, and it was difficult to stabilize even with ice bath. Controlling overheating is crucial to avoid chemical degradation and reduced concentration of the nanosheets51. Generating shock waves, liquid jets from bubble implosion and rapid oscillating forces all add to the powerful shear forces that proliferate layer delamination. It is also seen that within the cavitation zone/under the probe the bulk graphite flake layers were subject to layer tearing47. Therefore, ultrasonic cavitation can be used to physically exfoliate 2D materials by breaking the bulk lamellar materials into thinner flakes, which is the main mechanism for exfoliating graphene. After sonicating the sample for a specific time in pulse mode, the dispersion was left unperturbed during periods of time to separate the graphene flakes via sedimentation. Drops from the top portion of the dispersion were collected after 1, 24, and 94 h, drop-casted on precleaned Si substrates, and dried on a hot plate at 100 °C. The samples are named 1hr_sed, 24hr_sed and 94hr_sed, respectively. Once dried, the samples were investigated by SEM  water. During sonication, the probe is in direct contact with the sample where it utilizes ultrasound energy. This ultrasonic agitation creates energetic cavitation bubbles due to the abrupt pressure fluctuations from the creation and bursting of these small bubblesAfterward, the supernatant was further subjected to sonication with the previous parameters. Every two hours, the sonication was stopped, the dispersion was sedimented for an hour, and a sample was collected from the top portion for characterization. These samples are denoted as 4hr_son, 6hr_son, and 8hr_son, as shown in Fig. Further, a TEM sample was prepared from the 8hr_son sample. Figure 52 and so a trade-off between the sonication time and flakes with lesser defects must be made. In our study, a sonication time of 6 h was considered for further experiments  generates high number of defects in the graphene dispersion even though thinner flakes are created. This is in accordance with previous studies2SO4. The ionic size of sulfate ion is 0.46 nm, which is comparable to the graphite interlayer spacing (0.335 nm). This makes the sulfate ions a favorable candidate for the intercalation process for effective exfoliation of the graphene layers57. Sulfate-based ions are also used during anodic exfoliation of graphene from graphite58. Therefore, H2SO4 is chosen as the most appropriate pretreatment medium allowing sulfate ions intercalation between the graphene sheets and assisting in the exfoliation. The obtained acid pre-treated solution was rinsed with DI, filtered, and dried. The dried powder was resuspended in DI for further sonication following the parameters discussed above. After centrifugation, the samples were analyzed by SEM. Figure 2SO4 solutions. Here, it is important to point out that during imaging we noticed that it was easier to find separated flakes in the pre-treated samples, suggesting an increased yield. However, the lateral size of the flakes was consistently reduced when increased H2SO4 concentration was used  from analyzing graphene’s baseline absorbance at 660 nm and applying Beer-Lambert’s law:To further quantify graphene’s yield due to the pretreatment of the graphite powder, absorption study of the graphene solutions was performed. Figure −1 m−1, was within the range reported in the literature61. The pretreatment step has been found to increase the exfoliation yield by 24% as seen in Fig. 62, see supplementary Table 2 and this could impact the sulfate ion intercalation. Besides, the flake size is likely to impact as well. The sulfate ion intercalation starts from the edges which is the c-axis of the graphite structure. Coverage of the sulfate ion in the material/flake can be insignificant in the case of large flakes and this can decrease the graphene exfoliation. However, extensive parametric studies should be carried out in order to establish a flake size-dependent graphene exfoliation process.The absorption coefficient, calculated to be 1415.7 ml mg−163. In the case of pre-treated 0 M, 3 M, and 5 M samples, the D bands are localized at 1347, 1350, and 1349 cm−1, respectively. The G bands shift to 1577 (0 M), 1581 (3 M), and 1581.5 (5 M) cm−1 with respect to graphite  in stage-2  after acidic pretreatment69. This suggests the formation of GICs in our samples, although partial rather than an ideal full intercalation  may produce gaseous molecules such as, CO2, SO2 and H2O that can further push the layers to separate from each other75.To better understand the effect of the acidic pretreatment on the exfoliation process, the samples were analyzed by Raman spectroscopy. As shown in Fig. 76. Besides, a high oxygen content was found on specific regions of the flakes, indicating a partial oxidation of these  during the chemical process. The high resolution C1s peak with different acid concentrations, elemental analysis, and corresponding peak deconvolution are shown in Fig. 77, while the peaks at around 286, 288 and 290 eV corresponds to hydroxyl or epoxide groups (C–OH or C–O–C), carboxyl group (C=O), and the pi–pi* peaks, respectively78. XPS analysis confirmed that the atomic concentration of oxidized carbon increases from 3% for the 3 M to 29.7% for the 5 M.The survey scans revealed the presence of three main components in all samples, which are denoted as: C1s at 286 eV, O1s at 532 eV and Si at 99 eV and 120 eV Fig. a. The ap79. According to several applied research80 and DFT simulations, the XPS peak at 285.2 eV indicates the existence of defects, while the peak broadening is directly related to the size of the defect83. Barinov et al.84 demonstrated that the line broadening and extra peaks are caused by the point defects present in the hexagonal carbon lattice. Additionally, as the defect density increases significantly, the form of the C1s line broadens significantly. The evolution of defect bands at the lower BE regime of C1s band requires an extra peak with BE of 285 eV to accommodate the substantial line broadening, and this peak was attributable to the existence of C adatoms or sp3-C bond over the surface. Additionally, the peak at 285 eV was attributed to defects such as nonconjugated carbon (nc-C) bonding in multi-walled CNTs and C–H bonding in hydrogenated graphite85.XPS measurements have been also used to evaluate the defect density in graphene89.As observed in Fig. 90. The quantity of C=C sp2 bonding in the hexagonal lattice determines the conjugation strength, which relates to the relative amplitude of this ShU signal. The relative area under the curve (AShU) was greater in 5 M sample, as shown in Fig. 2SO4, has the lowest total defect concentration whereas the sample 5M, pre-treated with higher acid concentration, has the largest vacancy and nc-C defects.As shown in Fig. C/O was calculated from the XPS data and found that it was about 1 for the 0 M sample, which increased to about 1.54 for 3 M and 2.98 for the 5 M, in agreement with the ID/IG value estimated from the Raman analysis  without the addition of any surfactant is a promising path for graphene exfoliation. We have also shown that the addition of an acid pretreatment is a simple and easy approach to increase the exfoliation yield of graphene. It is found to be very effective in overcoming the van der Waals forces and could generate thinner graphene flakes. As demonstrated, acid treatment with optimum molar concentration, such as 3 M or 5 M could introduce a sufficient number of functional groups to the graphene flakes, which can be further considered as a source material for the production of useful other graphene derivatives, such as holey graphene2.There are many techniques for the production and processing of graphene, but LPE is the simplest and most versatile method to produce stable dispersions. However, as Backes et al.The use of probe sonication allows the exfoliation of the graphene layers effectively. Increasing sonication time proves to be useful in thinning down the graphite flakes; however, it comes at the cost of reduction of the flake lateral sizes. This highlights the deteriorating side of probe sonication and limits its indefinite use in exfoliating graphene layers with high surface area. Despite the limitation, a trade-off could be made for an efficient use of the sonicating method. This could be beneficial for certain applications, such as controlling thermal reduction and pore creation or changing the inherent properties of the flakes.In this work, we have studied the exfoliation of graphene layers from graphite powder. Probe sonication was largely employed where parameters such as time, power, and centrifuge time were optimized to produce few-layer graphene flakes with size ˂ 1 µm. An intermediate sulfuric acid treatment was incorporated to increase the exfoliation yield. Increasing acidic concentrations produces thinner flakes but also increases the number of defects. Acidic pretreatment also introduces functional groups, which can be evident in the XPS studies. Thus, although sulfuric acid could help achieve thinner flakes, it inadvertently introduces certain functional groups and defects. Further, since the lateral size of the flakes decreased with increased acid concentration, we can conclude that the pretreatment with probe sonication not only promotes exfoliation between layers but also reduces their lateral size. This proves to be the major bottleneck for the full use of ultrasonic exfoliation, and a trade-off must be made between the flake size and thickness. Lastly, pretreatment with 3 M offers a 24% increase in graphene exfoliation yield with respect to the 0 M samples. The results also indicate that 3 M sample could be an ideal trade-off for obtaining thinner flakes with the highest yield and lower defect density. Further, the study and the understanding of the exfoliation process could be extended to other van der Waals materials for gaining thinner layers of 2D materials.Supplementary Information.


The production of highly stable, defect-free, and electricallyconducting 3D graphene structures from graphene oxide precursors ischallenging. This is because graphene oxide is a metastable materialwhose structure and chemistry evolve due to aging. Aging changes therelative composition of oxygen functional groups attached to the grapheneoxide and negatively impacts the fabrication and properties of reducedgraphene oxide. Here, we report a universal strategy to reverse theaging of graphene oxide precursors using oxygen plasma treatment.This treatment decreases the size of graphene oxide flakes and restoresnegative zeta potential and suspension stability in water, enablingthe fabrication of compact and mechanically stable graphene aerogelsusing hydrothermal synthesis. Moreover, we employ high-temperatureannealing to remove oxygen-containing functionalities and repair thelattice defects in reduced graphene oxide. This method allows obtaininghighly electrically conducting graphene aerogels with electrical conductivityof 390 S/m and low defect density. The role of carboxyl, hydroxyl,epoxide, and ketonic oxygen species is thoroughly investigated usingX-ray photoelectron and Raman spectroscopies. Our study provides uniqueinsight into the chemical transformations occurring during the agingand thermal reduction of graphene oxide from room temperature up to2700 °C. These steps can be performed simultaneously orone after the other. Although the GO-based methods are simple andversatile, there are challenges associated with them.Several synthesis methodshave been developed using GO as a startingmaterial for the preparation of 3D graphene materials  into graphene oxide aging and chemical transformationsto graphene occurring during the annealing from room temperature upto 2700 °C. We demonstrate that the high-temperature annealingat 2700 °C completely removes all the residual oxygen speciesand repairs intrinsic structural defects in the materials withoutaffecting their structure. As a result, we obtain highly mechanicallystable and conductive graphene aerogels with extremely low defectdensity. We demonstrate a practical and universal strategy to healdefects and improve the electrical properties of complex 3D graphenestructures without affecting their morphology.2 plasma environment for120 s, at 50 W, process pressure of 50 Pa with 50 sccm of O2 gas, and frequency f = 8.0 MHz (TESLA Rožnov)to produce pGO.The graphene aerogelswere prepared using different kinds of graphene oxide precursors:new GO, aged GO (aGO), and plasma-treated aged GO (pGO). The new GOpowder was purchased commercially from XFNano. The GO aging was performedby keeping the GO powder for 12 months in a sealed container to makeaGO. Then aGO was exposed to an O–1 mbar) at −70 °Cfor 16 h to remove the residual water content. The rGO aerogels beforethe annealing are termed nonannealed rGA.A GO and deionized (DI) water solution was preparedby mixing 2 mg/mL of the GO powders in DI water. A homogeneous dispersionsolution was obtained after ultrasonication for 30 min. Then the solution(30 mL) was sealed in a Teflon-lined autoclave of 50 mL size. Theautoclave was heated at 180 °C for 6 h to yield a self-assembledinterconnected 3D microporous network of reduced graphene oxide (rGO)hydrogels. The 3D rGO hydrogels were subsequently freeze-dried ina vacuum  was utilized with a graphite paperheating element that surrounded the annealed samples. All the annealingwas performed in the vacuum furnace at 2.3 × 10–4 mbar for 30 min. The annealing temperature was monitored by a pyrometer.The obtained freeze-driedrGA samples were annealed at differenttemperatures, i.e., 400, 750, 1000, 1300, and 2700 °C, to obtaingraphene aerogels (GA). For annealing, a homemade vacuum furnace (see Scanning electron microscopy(TESCAN MAIA3) was used to characterize the rGA and GA morphology.The materials were measured by X-ray photoelectron spectroscopy  and Raman spectroscopy (Renishaw inVia setupusing a 442 nm laser). Zeta potential and flake size measurementswere performed with a ZetaNano ZS  device equippedwith a He/Ne laser operating at 633 nm as a light source and an avalanchephotodiode as a detector. The DLS analysis used in this work is basedon the model which considers spherical particles. DC conductivitymeasurements were performed by linear four-point probe method by applyinga constant current of 0.05 mA using a constant current source  and measuring the voltage via a multimeter . The measurement was done by slightly pressing thesample (≤5% strain) on the top of predeposited electrodes toachieve good electrical contact.17 GO used in this study was purchased from commercial sources. Thatis why its properties can vary from batch to batch due to aging ordifferent storage conditions. In most cases, the purchased GO enabledformation of a stable hydrogel using hydrothermal synthesis. However,older GO affected by 1 year aging (aGO) did not yield a consolidatedgraphene hydrogel. Instead, distorted and broken pieces were producedfrom aGO precursors using the same hydrothermal synthesis parameters(rameters1. Some nWe have found that this issue could be overcomeby exposing themto oxygen plasma. The plasma-treated aGO (pGO) materials have formeda compact and stable rGO hydrogel using hydrothermal synthesis again. –1, which are associated with the D and G bands of graphene oxide.The ID/IG ratioof GO and aGO is 0.87 and 0.81, respectively. No major noticeablechange can be observed in the Raman spectra of GO compared to aGO.The FTIR absorbance spectra of GO and aGO (–1), hydroxyl , epoxide (C–O–C at 1200–1385cm–1), sp2-hybridized (C=C at1550–1650 cm–1), and ketonic species (C=Oat 1725–1810 cm–1).43 The main difference between the FTIR spectra of the GO and aGO samplesis observed in the relative intensities of the peaks. This observationshows a quantitative difference between the total content of oxygenand oxygen functional groups in the new and aged GO samples. However,due to the overlap of the peaks, quantitative analysis of the chemicalchanges is difficult and inaccurate from FTIR.43 Therefore, quantitative chemical analysis was done usingXPS.To understand the effects of the GOaging, a thorough examination of the structure and chemical compositionof GO before and after the aging was performed in  and aGO 2b revealTables S2–S4) confirmsthat the aged samples are slightly chemically different from the freshGO. The C 1s spectrum of the fresh GO  are located at 287.1 eV, and the carboxylspecies (COOH) are at 288.5 eV.46 The corresponding O 1s spectra with the deconvoluted C–O,C=O, and COOH peaks of the GO are shown in XPS analysis of GO and aGO (fresh GO 2c after Tables S3 and S4) reveal that the aging causes a loss of the oxygen-functionalizedcarbon, while the relative percentage of the sp2 + sp3 carbon content increases. A 7% decrease is observed relatedto the C–OH groups and an ∼1% decrease in the contentof C=O in aGO. Overall, the aging results in the loss of oxygenand modification of the oxygen-related functional groups in GO.After the aging, the C 1s and O 1s spectra 2c,d depiID/IG ratio down to 0.65 compared to theaGO and GO samples and improvement of the crystallinity of the sample.This observation can be explained by the partial removal of defectsrelated to oxygen functional groups with the plasma.40 There is no major difference in the FTIR spectrum of pGOwith respect to aGO. On the other hand, XPS exhibits notable chemicalchanges in pGO compared to aGO (Tables S2–S4). The deconvoluted XPS peaks in the C 1s and O 1s spectra show thatthe absolute oxygen content was decreased by 4% after the plasma treatment.This is mainly reflected in the decrease of hydroxyl (C–OH),epoxide (C–O), and ketonic (C=O) functional groups.However, the relative content of carboxyl (COOH) was increased from6.1 to 8.3% in pGO compared to aGO (see Table S3). The amount of sp2-bonded carbon is also increasedby the plasma treatment. Interestingly, the amount of defect-relatedsp3 carbon remains unchanged in the pGO after plasma treatment,which is in line with the Raman observation.The structural and chemical compositionanalysis of the plasma-treated aged graphene oxide (pGO) in 2 plasma treatment.Most of the oxygen species are diminished in the GO samples, exceptfor COOH, which is increased. As the carboxyl groups are negativelycharged, this observation suggests that a small increase in the COOHspecies by plasma is sufficient to recover the highly negative chargeof aGO and improve the solubility in water, as demonstrated below.However, it needs to be highlighted that it is challenging to drawany concrete conclusion from the structural, vibrational, and compositionalanalysis due to the insufficient sensitivity of the spectroscopictechniques to the carbon–oxygen bonds.3 This is because, in reduced GO, all carbon atoms in the defectiveregions are bonded to three neighbors that maintain a planar sp2 configuration, making them undetectable by spectroscopictechniques.32 Therefore, the GO properties,such as the surface charge and flake size distribution, influencedby the aging and plasma treatment are analyzed in water solutionsin the next section.From XPS analysis,the following conclusion can be derived. There are minor compositionalchanges in graphene oxide caused by the OAs the hydrothermalsynthesis of GA is started with an aqueous solution of GO, it is necessaryto have good colloidal stability of GO suspensions in water for thesuccessful preparation of 3D graphene hydrogels. 47Dynamic light scattering (DLS) and zeta potentialmeasurements3b–dreve48 The fresh GO solution exhibits a broad distributionof zeta potentials with peak boundaries from −66 to −7mV and a peak center at −39 mV  are inherited from the starting GO material because it containsa high density of sp3-hybridized carbon bonds due to theadsorbed oxygen species.31 Some intrinsicdefects, including lattice/topological and edge defects, are thenproduced during the ultrasonication and reduction of GO during thehydrothermal synthesis of rGA due to the loss of oxygen functionalgroups.56 3D porous graphene structuresmade of interconnected graphene sheets also contain other types oflonger-range defects, such as pore defects, cracks, and lack-of-fusionpore structures . The high-temperatureannealing can significantly improve the electrical conductivity (σ)of the aerogels (58 At lower temperatures (≤1000 °C), thechange in σ is low due to the presence of numerous oxygen-relatedfunctional groups. The electrical conductivity increases significantlyat high temperatures, demonstrating σ of ∼390 S/m at2700 °C. This electrical conductivity is one of the highest thatwas reported in the literature for graphene aerogels.17In 60 The ratioof the intensity of the D to G peaks can be used for the determinationof the defect density61 (nD) and crystallite size (La) using the equation defined by Cancado et al.62 For the nonannealed rGA, the crystallite size is foundto be around 10 nm, and the density of defects is roughly 4.3 ×1011 cm–2  and C=C(sp3) hybridized carbon atoms along with several carbon–oxygenfunctional groups, such as C–O , C=O , and O–C=O .66 The rGA sample is composed of 89% of carbon and 11% of oxygen. Annealingof the GA at 400 °C shows almost no change in the composition.Once the annealing temperature is increased to 750 °C, the relativecontent of carbon is increased to 96% and oxygen is decreased to 4%.When the aerogel is further annealed at 1000 °C, the carbon andoxygen content remains almost the same as in the GA annealed at 750°C. A significant reduction of oxygen is observed after 1300°C annealing. The GA sample annealed at 1300 °C has >99.4%of carbon and <0.6% of oxygen content. The oxygen is completelyremoved from the sample when the GA is annealed at 2700 °C (Table S5). After this high-temperature annealing,a highly mechanically stable and intact graphene aerogel is obtainedat 9.1 eV. The experimentally obtained values from our XPS measurementsare in line with this sequence of the theoretical binding energies.The amounts of different oxygen species at a specific annealing temperaturein the GA samples determined from XPS are summarized in Tables S6 and S7. The experiments show that hydroxylgroups are removed first. As a result, the GA sample annealed to 1000°C contains mainly carboxyl and ketonic species.69 After 1300 °C annealing, all the remaining oxygenspecies are removed from the sample.72 As no more oxygen functionalgroups are bound to the GA samples at temperatures above 1300 °C,the observed increase of the sp2 carbon content in GA between1300 and 2700 °C  annealingwas able to remove only hydroxyl species from the aerogels. The completeremoval of oxygen species was achieved at temperatures above 1300°C. Furthermore, it is observed that even after the completeremoval of oxygen from GA, the electrical conductivity is still limiteddue to the presence of intrinsic structural defects. The crystallographicdefects can be up to a large extent repaired by heating the aerogelsat extremely high temperatures (≥2700 °C). The high-temperatureannealing is found as an effective strategy to heal defects and improvethe electrical properties of complex 3D graphene structures withoutaffecting their morphology.In this work, we investigated the effectsof the aging and deoxidationof graphene oxide in the synthesis of complex 3D graphene aerogelstructures. We also demonstrated a universal strategy to reverse theaging and remove defects using O