Feeding frequency efficacy on biogas yield of oily substrate anaerobic digestion in continuous stir tank reactor.

Anaerobic treatment of oily substrate, known as grease trap waste (GTW), was investigated for its practicability via continuous stirred tank reactor (CSTR) at different operating conditions and selected recovery strategies of feeding frequency efficacy. This study determine the performance of feeding frequency efficacy, namely feeding every 24 hours (R24H) and feeding every 12 hours (R12H). Under organic loading rate (OLR) of 2.2 gCOD/L.day, R12H exhibited methane composition of 57%, methane production rate of 0.27 LCH4/L.day, and methane yield of 0.14 LCH4/gCODremoved. At the same OLR, R24H recorded methane composition of 60%, methane production rate of 0.29 LCH4/L.day and similar methane yield as R12H. Findings indicated that R24H showed performance comparable to that of R12H. Given minor variation observed in performance, it is recommended that plant operators may consider scheduling two feedings per day for low loading conditions and switch to one feeding per day for higher loading conditions. This strategy is designed to balance the system and prevent shock loads, which could lead to plant shutdowns. This mechanism will induce their conversion to volatile fatty acids (VFAs); thus, reducing the risk of acid accumulation and pH drops, which could inhibit methanogens to produce methane, especially for oily substrate.

Assessing methane emissions from paddy fields through environmental and UAV remote sensing variables.

Concerns about methane (CH4) emissions from rice, a staple sustaining over 3.5 billion people globally, are heightened due to its status as the second-largest contributor to greenhouse gases, driving climate change. Accurate quantification of CH4 emissions from rice fields is crucial for understanding gas concentrations. Leveraging technological advancements, we present a groundbreaking solution that integrates machine learning and remote sensing data, challenging traditional closed chamber methods. To achieve this, our methodology involves extensive data collection using drones equipped with a Micasense Altum camera and ground sensors, effectively reducing reliance on labor-intensive and costly field sampling. In this experimental project, our research delves into the intricate relationship between environmental variables, such as soil conditions and weather patterns, and CH4 emissions. We achieved remarkable results by utilizing unmanned aerial vehicles (UAV) and evaluating over 20 regression models, emphasizing an R2 value of 0.98 and 0.95 for the training and testing data, respectively. This outcome designates the random forest regressor as the most suitable model with superior predictive capabilities. Notably, phosphorus, GRVI median, and cumulative soil and water temperature emerged as the model's fittest variables for predicting these values. Our findings underscore an innovative, cost-effective, and efficient alternative for quantifying CH4 emissions, marking a significant advancement in the technology-driven approach to evaluating rice growth parameters and vegetation indices, providing valuable insights for advancing gas emissions studies in rice paddies.

Enhancing physicochemical, rheological properties, and in vitro rumen fermentation of starch with Melastoma candidum D. Don fruit extract.

The utilization of polyphenol-modified starch in ruminants has not undergone extensive exploration. This study aimed to investigate the impact of the complex formed between starch and Melastoma candidum D. Don fruit extract on physicochemical properties, phenol release kinetics in various buffers simulating the gastrointestinal tract, methane production, and post-rumen digestibility. The interaction between starch and M. candidum D. Don fruit extract significantly (p < 0.001) increased resistant starch and particle size diameter. The maximum phenolic release from complex between starch and M. candidum D. Don fruit extract, due to gastrointestinal tract-simulated buffers, ranged from 22.96 to 34.60 mg/100 mg tannic acid equivalent. However, rumen and abomasum-simulated buffers released more phenolic content, whereas the intestine-simulated buffer showed higher antioxidant activity (ferric ion-reducing antioxidant power). Furthermore, complex between starch and M. candidum D. Don fruit extract significantly decreased dry matter rumen digestibility (p < 0.001) and maximum methane gas production (p < 0.001).

Effect of rice bran fermented with Ligilactobacillus equi on in vitro fermentation profile and microbial population.

This study was conducted to assess the effects of fermented rice bran (FRB) with Ligilactobacillus equi on ruminal fermentation using an in vitro system. Oat hay, corn starch, and wheat bran were used as substrate for control. Ten percent of wheat bran was replaced with rice bran (RB), rice bran fermented with distilled water, and rice bran fermented with L. equi for T1, T2, and T3, respectively. The experimental diets were mixed with buffered rumen fluid from wethers under nitrogen gas and incubated for 24 h at 39°C. The fermentation profile and microbial population were analyzed after the incubations. The results revealed that the RB and FRB (with or without L. equi) significantly reduced the gas, methane (CH4), and CH4 per dry matter digested (p < 0.001). Total short-chain fatty acid was also reduced in T1 and T2 in comparison with the control (p < 0.001). Propionate proportion was increased while butyrate proportion was reduced in response to treatment addition in cultures (p < 0.001). Anaerobic fungi and Fibrobacter succinogenes abundance were decreased in treatments (p < 0.001). Overall, CH4 production in vitro can be reduced by RB and FRB supplementation as a result of the reduction of fiber-degrading microorganisms and a decrease in gas production.

Estimated greenhouse gas emissions in the Mbalmayo thermal power plant between 2016-2020 using the genetic-Gaussian algorithm coupling.

The greenhouse gas (GHG) emissions inventories in our context result from the production of electricity from fuel oil at the Mbalmayo thermal power plant between 2016 and 2020. Our study area is located in the Central Cameroon region. The empirical method of the second level of industrialisation was applied to estimate GHG emissions and the application of the genetic algorithm-Gaussian (GA-Gaussian) coupling method was used to optimise the estimation of GHG emissions. Our work is of an experimental nature and aims to estimate the quantities of GHG produced by the Mbalmayo thermal power plant during its operation. The search for the best objective function using genetic algorithms is designed to bring us closer to the best concentration, and the Gaussian model is used to estimate the concentration level. The results obtained show that the average monthly emissions in kilograms (kg) of GHGs from the Mbalmayo thermal power plant are: 526 kg for carbon dioxide (CO2), 971.41 kg for methane (CH4) and 309.41 kg for nitrous oxide (N2O), for an average monthly production of 6058.12 kWh of energy. Evaluation of the stack height shows that increasing the stack height helps to reduce local GHG concentrations. According to the Cameroonian standards published in 2021, the limit concentrations of GHGs remain below 30 mg/m3 for CO2 and 200 µg/m3 for N2O, while for CH4 we reach the limit value of 60 µg/m3. These results will enable the authorities to take appropriate measures to reduce GHG concentrations.

Green synthesis of Fe3O4@ceramsite from sludge improving anaerobic digestion performance of waste activated sludge.

Anaerobic digestion (AD) is a promising technique for waste management, which can achieve sludge stabilization and energy recovery. This study successfully prepared Fe3O4@ceramsite from WAS and applied it as an additive in sludge digestion, aiming to improve the conversion of organics to biomethane efficiency. Results showed that after adding the Fe3O4@ceramsite, the methane production was enhanced by 34.7% compared with the control group (88.0 ± 0.1 mL/g VS). Further mechanisms investigation revealed that Fe3O4@ceramsite enhanced digesta stability by strong buffering capacity, improved sludge conductivity, and promoted Fe (III) reduction. Moreover, Fe3O4@ceramsite has a larger surface area and better porous structure, which also facilitated AD performance. Microbial community analysis showed that some functional anaerobes related to AD such as Spirochaeta and Smithella were enriched with Fe3O4@ceramsite treatment. Potential syntrophic metabolisms between syntrophic bacteria (Syntrophomonas, associated with DIET) and methanogens were also detected in the Fe3O4@ceramsite treatment AD system.

Nitrous oxide respiration in acidophilic methanotrophs.

Aerobic methanotrophic bacteria are considered strict aerobes but are often highly abundant in hypoxic and even anoxic environments. Despite possessing denitrification genes, it remains to be verified whether denitrification contributes to their growth. Here, we show that acidophilic methanotrophs can respire nitrous oxide (N2O) and grow anaerobically on diverse non-methane substrates, including methanol, C-C substrates, and hydrogen. We study two strains that possess N2O reductase genes: Methylocella tundrae T4 and Methylacidiphilum caldifontis IT6. We show that N2O respiration supports growth of Methylacidiphilum caldifontis at an extremely acidic pH of 2.0, exceeding the known physiological pH limits for microbial N2O consumption. Methylocella tundrae simultaneously consumes N2O and CH4 in suboxic conditions, indicating robustness of its N2O reductase activity in the presence of O2. Furthermore, in O2-limiting conditions, the amount of CH4 oxidized per O2 reduced increases when N2O is added, indicating that Methylocella tundrae can direct more O2 towards methane monooxygenase. Thus, our results demonstrate that some methanotrophs can respire N2O independently or simultaneously with O2, which may facilitate their growth and survival in dynamic environments. Such metabolic capability enables these bacteria to simultaneously reduce the release of the key greenhouse gases CO2, CH4, and N2O.

Methane output across life stages in sheep, how it differs from lambs to adult ewes using portable accumulation chambers.

Methane (CH4) produced from enteric fermentation is a potent greenhouse gas produced by ruminant animals. Multiple measurements are required across life stages to develop an understanding of how CH4 output changes throughout the animal's lifetime. The objectives of the current study were to estimate CH4 output across life stages in sheep and to investigate the relationship between CH4 output and dry matter (DM) intake (DMI). Data were generated on a total of 266 female Suffolk and Texel animals. Methane and carbon dioxide (CO2) output, estimated using portable accumulation chambers, and DMI, estimated using the n-alkane technique outdoors and using individual penning indoors, were quantified across the animal's life stage; as lambs (<12 mo), nulliparous hoggets (12 to 24 mo) and ewes (primiparous or greater; > 24 mo). Ewes were further classified as pregnant, lactating, and dry (non-pregnant and non-lactating). Multiple measurements were taken within and across the life stages of the same animals. A linear mixed model was used to determine if CH4 and CO2 output differed across life stages and using a separate linear mixed model the factors associated with CH4 output within each life stage were also investigated. Methane, CO2 output, and DMI differed by life stage (P < 0.05), with lactating ewes producing the greatest amount of CH4 (25.99 g CH4/d) and CO2 (1711.6 g CO2/d), while also having the highest DMI (2.18 kg DM/d). Methane output differed by live-weight of the animals across all life stages (P < 0.001). As ewe body condition score increased CH4 output declined (P < 0.05). Correlations between CH4 output measured across life stages ranged from 0.26 (SE 0.08; lambs and lactating ewes) to 0.59 (SE 0.06; hoggets and pregnant ewes), while correlations between CO2 output measured across life stages ranged from 0.12 (SE 0.06; lambs and hoggets) to 0.65 (SE 0.06; hoggets and lactating ewes). DMI was moderately correlated with CH4 (0.44; SE 0.04) and CO2 output (0.59; SE 0.03). Results from this study provide estimates of CH4 output across life stages in a pasture-based sheep production system and offer valuable information for the national inventory and the marginal abatement cost curve on the optimum time to target mitigation strategies.

Obtaining accurate estimates of methane (CH4) output across life stages is important to assess how CH4 output changes throughout the production cycle in pasture-based sheep production systems. This study investigated the factors associated with CH4 output at each life stage (lambs, hoggets, pregnant, lactating, and dry ewes), the relationship between CH4 output measured across life stages and the relationship between CH4 output and dry matter intake (DMI) in an Irish lowland sheep production system. Methane and carbon dioxide (CO2) output and DMI were measured on 266 purebred Suffolk and Texel females across their lifetime. Lactating ewes produced the highest CH4 and CO2 output, along with having the highest DMI. Across all life stages, CH4 output increased with increasing live weight while CH4 output decreased as body condition score increased. Weak to moderate relationships were found between CH4 output measured across life stages, with the strength of the relationship decreasing as the time between life stages increased. A positive relationship was found between DMI and CH4 output. Results from this study lead to the development of a profile of CH4 output across the production cycle of a pasture-based sheep system.

Physiological basis for atmospheric methane oxidation and methanotrophic growth on air.

Atmospheric methane oxidizing bacteria (atmMOB) constitute the sole biological sink for atmospheric methane. Still, the physiological basis allowing atmMOB to grow on air is not well understood. Here we assess the ability and strategies of seven methanotrophic species to grow with air as sole energy, carbon, and nitrogen source. Four species, including three outside the canonical atmMOB group USCα, enduringly oxidized atmospheric methane, carbon monoxide, and hydrogen during 12 months of growth on air. These four species exhibited distinct substrate preferences implying the existence of multiple metabolic strategies to grow on air. The estimated energy yields of the atmMOB were substantially lower than previously assumed necessary for cellular maintenance in atmMOB and other aerobic microorganisms. Moreover, the atmMOB also covered their nitrogen requirements from air. During growth on air, the atmMOB decreased investments in biosynthesis while increasing investments in trace gas oxidation. Furthermore, we confirm that a high apparent specific affinity for methane is a key characteristic of atmMOB. Our work shows that atmMOB grow on the trace concentrations of methane, carbon monoxide, and hydrogen present in air and outlines the metabolic strategies that enable atmMOB to mitigate greenhouse gases.

Mechanisms of secondary biogenic coalbed methane formation in bituminous coal seams: a joint experimental and multi-omics study.

Coal seam microbes, as endogenous drivers of secondary biogenic gas production in coal seams, might be related to methane production in coal seams. In this study, we carried out anaerobic indoor culture experiments of microorganisms from three different depths of bituminous coal seams in Huainan mining area, and revealed the secondary biogas generation mechanism of bituminous coal seams by using the combined analysis of macro-genome and metabolism multi-omics. The results showed that the cumulative mass molar concentrations (Molality) of biomethane production increased with the increase of the coal seam depth in two consecutive cycles. At the genus level, there were significant differences in the bacterial and archaeal community structures corresponding to the three coal seams 1#, 6#, and 9#(p < 0.05). The volatile matter of air-dry basis (Vad) of coal was significantly correlated with differences in genus-level composition of bacteria and archaea, with correlations of R bacterial = 0.368 and R archaeal = 0.463, respectively. Functional gene analysis showed that the relative abundance of methanogenesis increased by 42% before and after anaerobic fermentation cultivation. Meanwhile, a total of 11 classes of carbon metabolism homologues closely related to methanogenesis were detected in the liquid metabolites of coal bed microbes after 60 days of incubation. Finally, the fatty acid, amino acid and carbohydrate synergistic methanogenic metabolic pathway was reconstructed based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. The expression level of mcrA gene within the metabolic pathway of the 1# deep coal sample was significantly higher than that of the other two groups (p < 0.05 for significance), and the efficient expression of mcrA gene at the end of the methanogenic pathway promoted the conversion of bituminous coal organic matter to methane. Therefore, coal matrix compositions may be the key factors causing diversity in microbial community and metabolic function, which might be related to the different methane content in different coal seams.

Including Methane Emissions from Agricultural Ponds in National Greenhouse Gas Inventories.

Agricultural ponds are a significant source of greenhouse gases, contributing to the ongoing challenge of anthropogenic climate change. Nations are encouraged to account for these emissions in their national greenhouse gas inventory reports. We present a remote sensing approach using open-access satellite imagery to estimate total methane emissions from agricultural ponds that account for (1) monthly fluctuations in the surface area of individual ponds, (2) rates of historical accumulation of agricultural ponds, and (3) the temperature dependence of methane emissions. As a case study, we used this method to inform the 2024 National Greenhouse Gas Inventory reports submitted by the Australian government, in compliance with the Paris Agreement. Total annual methane emissions increased by 58% from 1990 (26 kilotons CH4 year-1) to 2022 (41 kilotons CH4 year-1). This increase is linked to the water surface of agricultural ponds growing by 51% between 1990 (115 kilo hectares; 1,150 km2) and 2022 (173 kilo hectares; 1,730 km2). In Australia, 16,000 new agricultural ponds are built annually, expanding methane-emitting water surfaces by 1,230 ha yearly (12.3 km2 year-1). On average, the methane flux of agricultural ponds in Australia is 0.238 t CH4 ha-1 year-1. These results offer policymakers insights into developing targeted mitigation strategies to curb these specific forms of anthropogenic emissions. For instance, financial incentives, such as carbon or biodiversity credits, can mobilize widespread investments toward reducing greenhouse gas emissions and enhancing the ecological and environmental values of agricultural ponds. Our data and modeling tools are available on a free cloud-based platform for other countries to adopt this approach.

Simultaneous methane mitigation and nitrogen removal by denitrifying anaerobic methane oxidation in lake sediments.

Methane (CH4) is a potent greenhouse gas, with lake ecosystems significantly contributing to its global emissions. Denitrifying anaerobic methane oxidation (DAMO) process, mediated by NC10 bacteria and ANME-2d archaea, links global carbon and nitrogen cycles. However, their potential roles in mitigating methane emissions and removing nitrogen from lake ecosystems remain unclear. This study explored the spatial variations in activities of nitrite- and nitrate-DAMO and their functional microbes in Changdanghu Lake sediments (Jiangsu Province, China). The results showed that although the average abundance of ANME-2d archaea (5.0 × 106 copies g-1) was significantly higher than that of NC10 bacteria (2.1 × 106 copies g-1), the average potential rates of nitrite-DAMO (4.59 nmol 13CO2 g-1 d-1) and nitrate-DAMO (5.01 nmol 13CO2 g-1 d-1) showed no significant difference across all sampling sites. It is estimated that nitrite- and nitrate-DAMO consumed approximately 6.46 and 7.05 mg CH4 m-2 d-1, respectively, which accordingly achieved 15.07-24.95 mg m-2 d-1 nitrogen removal from the studied lake sediments. Statistical analyses found that nitrite- and nitrate-DAMO activities were both significantly related to sediment nitrate contents and ANME-2d archaeal abundance. In addition, NC10 bacterial and ANME-2d archaeal community compositions showed significant correlations with sediment organic carbon content and water depth. Overall, this study underscores the dual roles of nitrite- and nitrate-DAMO processes in CH4 mitigation and nitrogen elimination and their key environmental impact factors (sediment organic carbon and inorganic nitrogen contents, and water depth) in shallow lake, enhancing the understanding of carbon and nitrogen cycles in freshwater aquatic ecosystems.

Metal-(Acyclic Diaminocarbene) Complexes Demonstrate Nanomolar Antiproliferative Activity against Triple-Negative Breast Cancer.

Invited for the cover of this issue are Tatiyana Serebryanskaya, Mikhail Kinzhalov and co-workers at St. Petersburg State University, the Research Institute for Physical Chemical Problems, Belarusian State University, Togliatti State University and Blokhin National Medical Research Center of Oncology. The image depicts the shield of Pallas Athena with the structure of a palladium carbene complex that protects against triple-negative breast cancer. Read the full text of the article at 10.1002/chem.202400101.

Sulfur cycling likely obscures dynamic biologically-driven iron redox cycling in contemporary methane seep environments.

Deep-sea methane seeps are amongst the most biologically productive environments on Earth and are often characterised by stable, low oxygen concentrations and microbial communities that couple the anaerobic oxidation of methane to sulfate reduction or iron reduction in the underlying sediment. At these sites, ferrous iron (Fe2+) can be produced by organoclastic iron reduction, methanotrophic-coupled iron reduction, or through the abiotic reduction by sulfide produced by the abundant sulfate-reducing bacteria at these sites. The prevalence of Fe2+in the anoxic sediments, as well as the availability of oxygen in the overlying water, suggests that seeps could also harbour communities of iron-oxidising microbes. However, it is unclear to what extent Fe2+ remains bioavailable and in solution given that the abiotic reaction between sulfide and ferrous iron is often assumed to scavenge all ferrous iron as insoluble iron sulfides and pyrite. Accordingly, we searched the sea floor at methane seeps along the Cascadia Margin for microaerobic, neutrophilic iron-oxidising bacteria, operating under the reasoning that if iron-oxidising bacteria could be isolated from these environments, it could indicate that porewater Fe2+ can persist is long enough for biology to outcompete pyritisation. We found that the presence of sulfate in our enrichment media muted any obvious microbially-driven iron oxidation with most iron being precipitated as iron sulfides. Transfer of enrichment cultures to sulfate-depleted media led to dynamic iron redox cycling relative to abiotic controls and sulfate-containing cultures, and demonstrated the capacity for biogenic iron (oxyhydr)oxides from a methane seep-derived community. 16S rRNA analyses revealed that removing sulfate drastically reduced the diversity of enrichment cultures and caused a general shift from a Gammaproteobacteria-domainated ecosystem to one dominated by Rhodobacteraceae (Alphaproteobacteria). Our data suggest that, in most cases, sulfur cycling may restrict the biological "ferrous wheel" in contemporary environments through a combination of the sulfur-adapted sediment-dwelling ecosystems and the abiotic reactions they influence.

High production of ectoine from methane in genetically engineered Methylomicrobium alcaliphilum 20Z by preventing ectoine degradation.

BACKGROUND: Methane is a greenhouse gas with a significant potential to contribute to global warming. The biological conversion of methane to ectoine using methanotrophs represents an environmentally and economically beneficial technology, combining the reduction of methane that would otherwise be combusted and released into the atmosphere with the production of value-added products. RESULTS: In this study, high ectoine production was achieved using genetically engineered Methylomicrobium alcaliphilum 20Z, a methanotrophic ectoine-producing bacterium, by knocking out doeA, which encodes a putative ectoine hydrolase, resulting in complete inhibition of ectoine degradation. Ectoine was confirmed to be degraded by doeA to N-α-acetyl-L-2,4-diaminobutyrate under nitrogen depletion conditions. Optimal copper and nitrogen concentrations enhanced biomass and ectoine production, respectively. Under optimal fed-batch fermentation conditions, ectoine production proportionate with biomass production was achieved, resulting in 1.0 g/L of ectoine with 16 g/L of biomass. Upon applying a hyperosmotic shock after high-cell-density culture, 1.5 g/L of ectoine was obtained without further cell growth from methane. CONCLUSIONS: This study suggests the optimization of a method for the high production of ectoine from methane by preventing ectoine degradation. To our knowledge, the final titer of ectoine obtained by M. alcaliphilum 20ZDP3 was the highest in the ectoine production from methane to date. This is the first study to propose ectoine production from methane applying high cell density culture by preventing ectoine degradation.

Effect of residual methane emission on physiological characteristics and carcass performance in Japanese Black cattle.

This study investigated the physiological characteristics and carcass performance associated with residual methane emissions (RME), and the effects of bull differences on CH4-related traits in Japanese Black cattle. Enteric methane (CH4) emissions from 156 Japanese Black cattle (111 heifers and 45 steers) were measured during early fattening using the sniffer method. Various physiological parameters were investigated to clarify the physiological traits between the high, middle, and low RME groups. CH4-related traits were examined to determine whether bull differences affected progeny CH4 emissions. Ruminal butyrate and NH3 concentrations were significantly higher in the high-RME group than in the low-RME group, whereas the propionate content was significantly higher in the low-RME group. Blood urea nitrogen, ß-hydroxybutyric acid, and insulin concentrations were significantly higher, and blood amino acids were lower in the high-RME group than in the other groups. No significant differences were observed in the carcass traits and beef fat composition between RME groups. CH4-related traits were significantly different among bull herds. Our results show that CH4-related traits are heritable, wherein bull differences affect progeny CH4 production capability, and that the above-mentioned rumen fermentations and blood metabolites could be used to evaluate enteric methanogenesis in Japanese Black cattle.

New insights on ecological roles of waste activated sludge in nutrient-stressed co-digestion.

There have been extensive applications of waste activated sludge (WAS) in anaerobic co-digestion (AcoD). Nonetheless, mechanisms through which AcoD systems maintain stability, particularly under nutrient-stressed conditions, are under-appreciated. In this study, the role of WAS in a nutrient-stressed WAS-food waste AcoD system was re-evaluated. Our findings demonstrated that WAS-based co-digestion increased methane production (by 20-60%) as WAS bolsters such systems' resilience via establishing a core niche-based microbial balance. The carbon utilization investigation suggested a microbial niche balance is attainable if two conditions are satisfied: 1) hydrolysis efficiency is greater than 50%; and 2) both the acidogenesis-to-hydrolysis and acetogenesis-to-hydrolysis efficiencies surpass 0.5. Metagenomic assembly genome (MAG) analysis indicated that the versatile metabolic characteristics strengthened the microbial niche balance, rendering the system resilient and efficient through a syntrophic mode, contributing to both acidogenesis and acetogenesis. The findings of this study provide new insights into the ecological effects of WAS on AcoD.

Chemiresistors Based on Hybrid Nanostructures Obtained from Graphene and Conducting Polymers with Potential Use in Breath Methane Detection Associated with Irritable Bowel Syndrome.

This paper describes the process of producing chemiresistors based on hybrid nanostructures obtained from graphene and conducting polymers. The technology of graphene presumed the following: dispersion and support stabilization based on the chemical vapor deposition technique; transfer of the graphene to the substrate by spin-coating of polymethyl methacrylate; and thermal treatment and electrochemical delamination. For the process at T = 950 °C, a better settlement of the grains was noticed, with the formation of layers predominantly characterized by peaks and not by depressions. The technology for obtaining hybrid nanostructures from graphene and conducting polymers was drop-casting, with solutions of Poly(3-hexylthiophene (P3HT) and Poly[(9,9-dioctylfluorenyl-2,7-diyl)-co-bithiophene] (F8T2). In the case of F8T2, compared to P3HT, a 10 times larger dimension of grain size and about 7 times larger distances between the peak clusters were noticed. To generate chemiresistors from graphene-polymer structures, an ink-jet printer was used, and the metallization was made with commercial copper ink for printed electronics, leading to a structure of a resistor with an active surface of about 1 cm2. Experimental calibration curves were plotted for both sensing structures, for a domain of CH4 of up to 1000 ppm concentration in air. A linearity of the curve for the low concentration of CH4 was noticed for the graphene structure with F8T2, presenting a sensitivity of about 6 times higher compared with the graphene structure with P3HT, which makes the sensing structure of graphene with F8T2 more feasible and reliable for the medical application of irritable bowel syndrome evaluation.

Prediction of Individual Gas Yields of Supercritical Water Gasification of Lignocellulosic Biomass by Machine Learning Models.

Supercritical water gasification (SCWG) of lignocellulosic biomass is a promising pathway for the production of hydrogen. However, SCWG is a complex thermochemical process, the modeling of which is challenging via conventional methodologies. Therefore, eight machine learning models (linear regression (LR), Gaussian process regression (GPR), artificial neural network (ANN), support vector machine (SVM), decision tree (DT), random forest (RF), extreme gradient boosting (XGB), and categorical boosting regressor (CatBoost)) with particle swarm optimization (PSO) and a genetic algorithm (GA) optimizer were developed and evaluated for prediction of H2, CO, CO2, and CH4 gas yields from SCWG of lignocellulosic biomass. A total of 12 input features of SCWG process conditions (temperature, time, concentration, pressure) and biomass properties (C, H, N, S, VM, moisture, ash, real feed) were utilized for the prediction of gas yields using 166 data points. Among machine learning models, boosting ensemble tree models such as XGB and CatBoost demonstrated the highest power for the prediction of gas yields. PSO-optimized XGB was the best performing model for H2 yield with a test R2 of 0.84 and PSO-optimized CatBoost was best for prediction of yields of CH4, CO, and CO2, with test R2 values of 0.83, 0.94, and 0.92, respectively. The effectiveness of the PSO optimizer in improving the prediction ability of the unoptimized machine learning model was higher compared to the GA optimizer for all gas yields. Feature analysis using Shapley additive explanation (SHAP) based on best performing models showed that (21.93%) temperature, (24.85%) C, (16.93%) ash, and (29.73%) C were the most dominant features for the prediction of H2, CH4, CO, and CO2 gas yields, respectively. Even though temperature was the most dominant feature, the cumulative feature importance of biomass characteristics variables (C, H, N, S, VM, moisture, ash, real feed) as a group was higher than that of the SCWG process condition variables (temperature, time, concentration, pressure) for the prediction of all gas yields. SHAP two-way analysis confirmed the strong interactive behavior of input features on the prediction of gas yields.