Combination of Broad Light-Absorption Cu₉S₅ with S,C,N-TiO₂: Assessment of Photocatalytic Performance in Nitrogen Fixation Reaction

Inorganic Chemistry, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 16, 2025

In the field of solar energy storage, photocatalytic ammonia production is a next-generation technology. The rapid recombination charges and insignificant utilization sunlight spectrum are bottlenecks effective N2 fixation. introduction impurities in crystal lattice development heterojunctions could effectively segregate carriers improve solar-light-harvesting capability, which can boost NH3 generation. Therefore, this work, three-element doping by S, C, N was carried out to rectify feature TiO2, then it combined with broad-light-absorption Cu9S5 semiconductor. synthesized S,C,N-doped TiO2/Cu9S5 nanocomposites QD size almost 7.17 nm exhibited outstanding ability reduction, generation reached 23 567 μmol L–1 g–1 without sacrificial agents, 5.67 2.11 folds larger than TiO2 Cu9S5, respectively. promoted performance nanocomposite ascribed three elements construction Z-scheme system, attains efficacious separation supplies dedicated path for carrier migration. This research not only supports novel, sustainable, facile strategy synthesis S,C,N-TiO2/Cu9S5 inorganic materials biocompatible characteristics but also provides new insights into design TiO2-based through nonmetal low-cost three-elemental nitrogen

Language: Английский

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Artificial intelligence interventions in 2D MXenes-based photocatalytic applications

Coordination Chemistry Reviews, Journal Year: 2025, Volume and Issue: 529, P. 216460 - 216460

Published: Jan. 24, 2025

Language: Английский

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The Electron‐Rich Interface Regulated MBene by S‐Bridge Guided to Enhance Nitrogen Fixation under Environmental Conditions

Advanced Functional Materials, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 15, 2024

Abstract The underutilization of active sites limits the performance enhancement 2D transition metal boride (MBene) in electrocatalytic nitrogen reduction reaction (NRR). Herein, a highly efficient NRR electrocatalyst with S atoms bridging Fe and Mo on surface MBene is successfully constructed by using an site electron optimization strategy, which increases charge density around enhances activation ability catalyst to N 2 molecules. It noteworthy that FeS ‐MBene demonstrates low intrinsic potential for (−0.2 V vs RHE). more favorable adsorption comparison hydrogen atoms, thereby it can effectively inhibit evolution (HER). Under −0.2 versus RHE, ammonia yield rate 37.13 ± 1.31 µg h −1 mg , FE 55.97 2.63%. Density functional theory (DFT) calculations demonstrate serves as . formation heterostructure transfer, resulting becoming electron‐rich state favor subsequent hydrogenation steps. This work offers significant insights into design utilization MBene‐based catalysts NRR.

Language: Английский

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Flatland materials for photochemical and electrochemical nitrogen fixation applications: from lab-door experiments to large-scale applicability

Sustainable Energy & Fuels, Journal Year: 2024, Volume and Issue: 8(16), P. 3476 - 3495

Published: Jan. 1, 2024

Flatland materials were meticulously surveyed to explore their functionality in photochemical and electrochemical nitrogen reduction reaction applications. New insights are presented for pilot-scale NRR operations via 2D materials.

Language: Английский

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Unlocking the catalytic potential of iMXenes: selective electrochemical CO₂ reduction for methane production

Journal of Materials Chemistry A, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 1, 2025

We employ first-principles calculations to systematically investigate the electrocatalytic activity and selectivity of various iMXenes for CH 4 production. Our study includes thorough investigation bare O-terminated iMXenes.

Language: Английский

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Spin effects in electrocatalysis: Mechanisms, catalyst engineering, modulation, and applications

Materials Science and Engineering R Reports, Journal Year: 2025, Volume and Issue: 164, P. 100967 - 100967

Published: March 5, 2025

Language: Английский

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Advanced carbon nitride‐based single‐atom photocatalysts

SusMat, Journal Year: 2024, Volume and Issue: 4(5)

Published: July 18, 2024

Abstract Single‐atom catalysts (SACs) have rapidly become a hot topic in photocatalytic research due to their unique physical and chemical properties, high activity, selectivity. Among many semiconductor carriers, the special structure of carbon nitride (C 3 N 4 ) perfectly meets substrate requirements for stabilizing SACs; they can also compensate defects C materials by modifying energy bands electronic structures. Therefore, developing advanced ‐based SACs is great significance. In this review, we focus on elucidating efficient preparation strategies burgeoning applications SACs. We outline prospective enhancing performance future. A comprehensive array methodologies presented identifying characterizing This includes an exploration potential atomic catalytic mechanisms through simulation regulation behaviors synergistic effects single or multiple sites. Subsequently, forward‐looking perspective adopted contemplate future prospects challenges associated with encompasses considerations, such as loading, regulatory design, integration machine learning techniques. It anticipated that review will stimulate novel insights into synthesis high‐load durable SACs, thereby providing theoretical groundwork scalable controllable field.

Language: Английский

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Elevating photocatalytic H2 evolution over ZnIn2S4@[email protected] multilayer nanotubes via Au-mediating H–S antibonding-orbital occupancy

Chemical Engineering Journal, Journal Year: 2024, Volume and Issue: 499, P. 156455 - 156455

Published: Oct. 11, 2024

Language: Английский

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Sparse Gaussian process based machine learning first principles potentials for materials simulations: Application to batteries, solar cells, catalysts, and macromolecular systems

Chemical Physics Reviews, Journal Year: 2024, Volume and Issue: 5(4)

Published: Nov. 27, 2024

To design new materials and understand their novel phenomena, it is imperative to predict the structure properties of that often rely on first-principles theory. However, such methods are computationally demanding limited small systems. This topical review investigates machine learning (ML) approaches, specifically non-parametric sparse Gaussian process regression (SGPR), model potential energy surface (PES) materials, while starting from basics ML for a comprehensive review. SGPR can efficiently represent PES with minimal ab initio data, significantly reducing computational costs by bypassing need inverting massive covariance matrices. rank reduction accelerates density functional theory calculations orders magnitude, enabling accelerated simulations. An optimal adaptive sampling algorithm utilized on-the-fly molecular dynamics, extending interatomic potentials through scalable formalism. Through merging quantum mechanics methods, universal SGPR-based create digital-twin capable predicting phenomena arising static dynamic changes as well inherent collective characteristics materials. These techniques have been applied successfully solid electrolytes, lithium-ion batteries, electrocatalysts, solar cells, macromolecular systems, reproducing structures, energetics, properties, phase-changes, performance, device efficiency. discusses built-in library potential, showcasing its applications successes, offering insights into development future in advanced catering both educational expert readers.

Language: Английский

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Tuning organic ligands to optimize the nitrogen reduction performance of Co(II) or Ni(II)‐based MOFs

Materials Chemistry Frontiers, Journal Year: 2024, Volume and Issue: 8(19), P. 3203 - 3213

Published: Jan. 1, 2024

The electrocatalytic nitrogen reduction to NH 3 performance of five Co(Ni)-MOFs with a similar structure can be optimized significantly by adjusting the functional block pyridine-bridging ligands.

Language: Английский

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