Results 211 to 220 of about 178,930 (305)

Assessing Mesoscale Heterogeneities in Hard Carbon Electrodes Through Deep Learning‐Assisted FIB‐SEM Characterization, Manufacturing and Electrochemical Modeling

Advanced Energy Materials, EarlyView.
A combination of discrete and finite element method models for the current collector deformation and electrochemical performance analysis, respectively. The models are calibrated and validated with electrochemical and imaging data of hard carbon electrodes. These electrodes were manufactured with different parameters (slurry solid contents of 35 and 40
Soorya Saravanan, Imelda Cardenas‐Sierra, Pei Sun, Hari Raj, Daniele Duranti, Mahnoor Nafees, Edoardo Rossi, Marco Sebastiani, Paul Vigneaux, Martin Petit, Maxime Moreaud, Francisco Fernandez, Alejandro A. Franco   +12 more
wiley   +1 more source

Operando X‐Ray Diffraction and Total Scattering Characterization of Battery Materials: Not Just a Pretty Picture

Advanced Energy Materials, EarlyView.
This review focuses on operando studies of battery materials by X‐ray diffraction (XRD) and total X‐ray scattering (TXS). This work highlights potential pitfalls and identify best‐practices for operando studies and reviews some unusual experiments to illustrate how these methods can be applied beyond the evaluation of the early‐stage cycling mechanisms
Amalie Skurtveit, Eira Tiberg North, Izar Capel Berdiell, Wouter Van Beek, David S. Wragg, Alexey Y. Koposov   +5 more
wiley   +1 more source

Indirect estimates of cellular hydration and relative water content and their associations with muscle strength and physical function in older adults: a path analysis from the Pro-Eva study. [PDF]

Eur Rev Aging Phys Act
Sales WB, Ribeiro-Samora GA, E Silva Barbosa PE, Vieira ER, Souza GF, Maciel ÁCC.   +5 more
europepmc   +1 more source

Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories

Advanced Energy Materials, EarlyView.
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen, Zheyu Zhang, Kelvian T. Mularso, Bonghyun Jo, Hyun Suk Jung   +4 more
wiley   +1 more source

Swarm intelligence-optimized deep neural network for intelligent diagnosis of lithium‑ion battery state of health. [PDF]

Sci Rep
Li C, Yan B, Zhu C, Zhou X, Jia Y.
europepmc   +1 more source

Enabling Long Term, Shelf‐Stable Perovskite Solar Cells: Alumina Barriers to Protect Perovskite Devices from Moisture and Oxygen

Advanced Energy Materials, EarlyView.
This study reports a packaging strategy for perovskite photovoltaic devices using atomic layer deposition (ALD) of aluminum oxide. Through optimization of deposition temperature and oxidant chemistry, researchers develop a 50 nm barrier layer with superior water vapor (WVTR) and oxygen transmission rates (OTR).
Melissa A. Davis, Kelly Schutt, Duong Nguyen Minh, Xinwen Zhang, Chenchao Xie, Ross A. Kerner, Tianran Liu, Matthew O. Reese, Laura T. Schelhas, Michael D. Kempe, Axel F. Palmstrom, Joseph M. Luther   +11 more
wiley   +1 more source

Joint estimation of SOC and SOH for lithium-ion batteries based on FOAMIUHF-UKF model. [PDF]

Sci Rep
Ye Z, Deng Z, Xu Y, Lai L, Zhang R, Tong L, Zhang H, Li Y, Gong M, Liu G, Yan M.   +10 more
europepmc   +1 more source

Atomistic Insights Into Lithium Alloying and Crystallization at Metal Interlayers in Zero‐Excess Lithium Batteries

Advanced Energy Materials, EarlyView.
Molecular dynamics simulations with machine learning potentials, combined with experiments, reveal how interlayer metals govern Li alloying and crystallization in zero‐excess lithium batteries. Mg and Zn promote solid‐solution alloy‐mediated pathways that influence Li diffusion and structural uniformity, while Bi forms ordered intermetallics with more ...
Neubi F. Xavier Jr., Nicolas Rospars, Mohammed Srout, Matthew K. Sharpe, Pablo Hernández‐Martín, Callum D. McAleese, Satheesh Krishnamurthy, Tao Chen, Celia Polop, Andrea Ingenito, Qiong Cai   +10 more
wiley   +1 more source

A temperature- and impedance-aware LSTM-PINN framework for physically consistent battery SOH prediction. [PDF]

Sci Rep
Kumar PN, Upadhya PR, Nischay S, Pavan Kumar G, T S S, K B R.   +5 more
europepmc   +1 more source

Streamlined V3.5+ Electrolyte Production by Leveraging Chemical and Catalytic Reductions

Advanced Energy Materials, EarlyView.
A tuned catalytic process for V3.5+ electrolyte production is shown to streamline the conventional chemical‐to‐catalytic sequence by extending catalysis into the rate‐determining reduction regime. This study shows that initiating catalysis in this regime shortens the overall production time by 67% based on rigorous thermodynamic and kinetic analysis of
Kyunghwa Seok, Minseong Kang, Hee‐Tak Kim   +2 more
wiley   +1 more source