Results 201 to 210 of about 117,350 (296)

Machine Learning Interatomic Potentials for Energy Materials: Architectures, Training Strategies, and Applications

Advanced Energy Materials, EarlyView.
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park, Saeed Pourasad, Jinhong Mun, Arunkumar Chitteth Rajan, Tae Hyeon Park, Anand Rohit, Mohammad Zafari, Tan‐Lien Pham, Eunjae Jung, Bonseung Koo, Miran Ha, Gi Beom Sim, Hyun Gyu Park, Won Woong Choi, Kwanghyeon Jo, Soohaeng Yoo Willow, David ChangMo Yang, Chang Woo Myung, Geunsik Lee, Kwang S. Kim   +19 more
wiley   +1 more source

Silicon‐Based Anodes for Sulfide Solid‐State Batteries: Failure Mechanisms and Multiscale Design Strategies

Advanced Energy Materials, EarlyView.
Silicon anodes in sulfide SSBs face coupled electrochemo‐mechanical failure by interface instability. This review examined recent advances and proposed mitigation strategies via material‐, electrode/interface‐, and cell‐level‐ engineering. We further evaluate scalable synthesis of sulfide SEs.
Murugesan Karuppaiah, JaeWook Seo, SeEun Park, Seung Hyeok Chu, Jung Kyoo Lee   +4 more
wiley   +1 more source

Numerical Investigations on Heat Transfer Characteristics of Mono and Hybrid Nanofluids Using Microchannel Cooling for 21700 Batteries in Electric Vehicles. [PDF]

Micromachines (Basel)
Le TD, Lee MY.
europepmc   +1 more source

From continuous to interruptible distillation: Flexible electric heating column architecture with fast start‐up

AIChE Journal, EarlyView.
Abstract Electrification of distillation offers a promising route to reducing scope‐1 emissions from one of the chemical industry's most energy‐intensive unit operations. However, conventional adiabatic columns are dynamically inflexible: Long, energy‐intensive start‐ups make shutdown and restart impractical under variable electricity prices and ...
Samuel Mercer, Michael Baldea
wiley   +1 more source

Optimizing charge discharge cycles using QPPONet-enabled hybrid learning framework for energy management and safety in electric vehicles. [PDF]

Sci Rep
Sujan Kumar MV, Khekare G.
europepmc   +1 more source

Challenges and enablers in fluidization technology

AIChE Journal, EarlyView.
Abstract Gas–solid fluidized beds provide excellent heat and mass transfer for high‐throughput operations from coating to catalytic conversion and underpin emerging low‐carbon technologies. Yet industrial reliability, scale‐up, and control lag scientific understanding, particularly as finer, stickier, and more variable feedstocks increasingly challenge
J. Ruud van Ommen, Jia Wei Chew
wiley   +1 more source

Graphene-silver hybrid nanoparticle embedded phase change materials for enhanced thermal management of lithium-ion batteries. [PDF]

RSC Adv
Akshay B, Seyas Mumthas FS, Mohan M, Bhuvanachandran Rajeswari V, Ravikumar C.   +4 more
europepmc   +1 more source

CFD modeling and sensitivity‐guided design of silicon filament CVD reactors

AIChE Journal, EarlyView.
Abstract Filament‐based chemical vapor deposition (CVD) for silicon (Si) coatings is often treated as an adaptation of planar deposition. But this overlooks fundamental shifts in transport phenomena and reaction kinetics. In filament CVD, the filament acts as a substrate, heat source, and flow disruptor simultaneously. In this work, we ask: What really
G. P. Gakis, G. Loachamín‐Suntaxi, I. G. Aviziotis, E. D. Koronaki, P. P. Filippatos, G. Chatzigiannakis, S. P. A. Bordas, D. Davazoglou, A. G. Boudouvis   +8 more
wiley   +1 more source

Numerical Study on Heat Transfer Characteristics of Microchannel with Ferrofluid Under Influence of Magnetic Intensity. [PDF]

Micromachines (Basel)
Hwang SG, Le TD, Lee MY.
europepmc   +1 more source

Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion

Advanced Intelligent Discovery, EarlyView.
This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia, Christian Mark Pelicano   +1 more
wiley   +1 more source