Results 171 to 180 of about 67,781 (329)

2D Nanomaterials for Solar Hydrogen Production

Advanced Energy and Sustainability Research, EarlyView.
This review gives comprehensively summarized latest advances on solar H2 production by various 2D nanomaterials using photocatalytic and photoelectrocatalytic H2 production methods, especially highlighting the photocatalytic one. After the summary, an outlook into the challenges and the future of 2D nanomaterials for solar H2 production is given.
Pengfei Cheng, Honglei Wang, Bo Wu, Guofu Zhou, Dong Wang, Peter Schaaf   +5 more
wiley   +1 more source

Machine Learning Phase Classification of Thermoelectric Materials. [PDF]

Materials (Basel)
Ma CT, Poon SJ.
europepmc   +1 more source

Accelerated Screening of Halide Double Perovskites via Hybrid Density Functional Theory and Machine Learning for Thermoelectric Energy Conversion

Advanced Energy and Sustainability Research, EarlyView.
This study integrates hybrid density functional theory, Boltzmann transport theory, and machine learning to accelerate the discovery of lead‐free halide double perovskites for thermoelectric energy conversion. By screening 102 compounds, the authors identify high‐performing candidates such as Rb2GeI6 and Cs2SnBr6, offering a sustainable pathway toward ...
Souraya Goumri‐Said, Ghouti Abdellaoui, Mohammed Benali Kanoun   +2 more
wiley   +1 more source

First principles study of multifunctional properties of Ga- and Tl-based quaternary materials for energy applications. [PDF]

RSC Adv
Al-Hmoud M, Gul B, Khan MS, Aziz SM, Benabdellah G, Binzowaimil AM.   +5 more
europepmc   +1 more source

Strategies for Paired Electrolysis with Enhanced Efficiency

Advanced Energy and Sustainability Research, EarlyView.
This review summarizes the fundamentals, challenges, and strategies for paired electrolysis, with examples in the chlor‐alkali, hydrogen production, CO2 reduction, and ammonia synthesis industries. Future directions include the development of advanced membranes, computational studies, process integration, scale‐up, and techno‐economic analysis.
Yuanyuan Yao, Xin Yang, Yuqi Pan, Leo Lai, Liuyue Cao, Li Wei, Yuan Chen   +6 more
wiley   +1 more source

Solution-Phase Design of Emerging Nanomaterials. [PDF]

Chem Mater
Schenk FM, Yarema M.
europepmc   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

Robust Material Properties in Epitaxial In₂Te₃ Thin Films across Varying Thicknesses. [PDF]

Small
Buchta M, Hoff F, Bothe L, Penner N, Ringkamp C, Schmidt T, Köttgen J, Veslin T, Mak KL, Frank J, Kim D, Wuttig M.   +11 more
europepmc   +1 more source

Structure and Spectroscopic Characterisation of Phenanthroline‐Based Iodobismuthate(III) Complexes Utilised for Raw Acoustic Signal Classification

Advanced Intelligent Discovery, EarlyView.
Memristors based on trimethylsulfonium (phenanthroline)tetraiodobismuthate have been utilised as a nonlinear node in a delayed feedback reservoir. This system allowed an efficient classification of acoustic signals, namely differentiation of vocalisation of the brushtail possum (Trichosurus vulpecula).
Ewelina Cechosz, Gisya Abdi, Andrzej Sławek, Marlena Gryl, Konrad Szaciłowski   +4 more
wiley   +1 more source

Alkali chalcogenides-assisted vapor-liquid-solid growth of WX₂ (X = S, Se, Te). [PDF]

Discov Nano
Chiang YC, Liu PY, Lin EC, Fan SH, Hung CC, Cheng YH, Lee YH.   +6 more
europepmc   +1 more source