Carbon quantum dots-modified tetra (4-carboxyphenyl) porphyrin/BiOBr S-scheme heterojunction for efficient photocatalytic antibiotic degradation

Science China Materials, Год журнала: 2024, Номер 67(2), С. 562 - 572

Опубликована: Янв. 23, 2024

Язык: Английский

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Rare earth oxide based electrocatalysts: synthesis, properties and applications

Chemical Society Reviews, Год журнала: 2023, Номер 53(2), С. 714 - 763

Опубликована: Дек. 18, 2023

The synthesis, properties and applications of rare earth oxide based electrocatalysts in electrocatalysis reactions.

Язык: Английский

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Carbon capture, utilization and sequestration systems design and operation optimization: Assessment and perspectives of artificial intelligence opportunities

The Science of The Total Environment, Год журнала: 2024, Номер 917, С. 170085 - 170085

Опубликована: Янв. 15, 2024

Язык: Английский

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Machine learning in energy storage material discovery and performance prediction

Chemical Engineering Journal, Год журнала: 2024, Номер 492, С. 152294 - 152294

Опубликована: Май 16, 2024

Язык: Английский

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Investigating explainable transfer learning for battery lifetime prediction under state transitions

eScience, Год журнала: 2024, Номер 4(5), С. 100280 - 100280

Опубликована: Май 21, 2024

Battery lifetime prediction at early cycles is crucial for researchers and manufacturers to examine product quality promote technology development. Machine learning has been widely utilized construct data-driven solutions high-accuracy predictions. However, the internal mechanisms of batteries are sensitive many factors, such as charging/discharging protocols, manufacturing/storage conditions, usage patterns. These factors will induce state transitions, thereby decreasing accuracy approaches. Transfer a promising technique that overcomes this difficulty achieves accurate predictions by jointly utilizing information from various sources. Hence, we develop two transfer methods, Bayesian Model Fusion Weighted Orthogonal Matching Pursuit, strategically combine prior knowledge with limited target dataset achieve superior performance. From our results, methods reduce root-mean-squared error 41% through adapting domain. Furthermore, strategies identify variations impactful features across different sets therefore disentangle battery degradation root cause transitions perspective data mining. findings suggest proposed in work capable acquiring multiple sources solving specialized issues.

Язык: Английский

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Insights into Operating Conditions on Electrocatalytic CO₂ Reduction

Advanced Energy Materials, Год журнала: 2025, Номер unknown

Опубликована: Фев. 5, 2025

Abstract Electrocatalytic CO 2 reduction (CO RR) is rapidly emerging as a promising sustainable strategy for transforming into valuable fuels and chemical feedstocks, crucial step toward carbon‐neutral society. The efficiency, selectivity, stability of RR are heavily influenced by the chosen catalyst operating conditions used. Despite substantial advances in development catalysts, there scarcity comprehensive reviews focusing on influence different environments performance. This review offers detailed examination internal external environmental control strategies designed to enhance efficiency. fundamental reaction mechanisms through situ operational techniques, paired with theoretical analyses, discussed while also identifying key challenges future research directions technology. By delivering overview current state field, this highlights critical role control, mechanistic insights, practical considerations needed successful commercialization

Язык: Английский

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Progress in prediction of photocatalytic CO2 reduction using machine learning approach: A mini review

Next Materials, Год журнала: 2025, Номер 8, С. 100522 - 100522

Опубликована: Фев. 10, 2025

Язык: Английский

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Optimization of kitchen wastewater-based microbial fuel cells by machine learning

Journal of Power Sources, Год журнала: 2025, Номер 632, С. 236379 - 236379

Опубликована: Янв. 31, 2025

Язык: Английский

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In-situ characterization technologies and theoretical calculations in carbon dioxide reduction: In-depth understanding of reaction mechanisms and rational design of electrocatalysts

Coordination Chemistry Reviews, Год журнала: 2025, Номер 533, С. 216541 - 216541

Опубликована: Фев. 28, 2025

Язык: Английский

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Engineered Cell Elongation Promotes Extracellular Electron Transfer of Shewanella Oneidensis

Advanced Science, Год журнала: 2024, Номер unknown

Опубликована: Сен. 5, 2024

Abstract To investigate how cell elongation impacts extracellular electron transfer (EET) of electroactive microorganisms (EAMs), the division model EAM Shewanella oneidensis ( S. ) MR‐1 is engineered by reducing formation divisome. Specially, blocking translation proteins via anti‐sense RNAs or expressing inhibitors, cellular length and output power density are all increased. Electrophysiological transcriptomic results synergistically reveal that programmed reinforces EET enhancing NADH oxidation, inner‐membrane quinone pool, abundance c ‐type cytochromes. Moreover, enhances hydrophobicity due to decreased cell‐surface polysaccharide, thus facilitates initial surface adhesion stage during biofilm formation. The current increase in positive correction with length. However, inhibition reduces growth, which then restored quorum sensing‐based dynamic regulation growth phases. QS‐regulated elongated strain enables a 143.6 ± 40.3 µm (72.6‐fold MR‐1), an 248.0 10.6 mW m −2 (3.41‐fold MR‐1) exhibits superior potential for pollutant treatment. Engineering paves innovate avenue EAMs.

Язык: Английский

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