Results 31 to 40 of about 1,153 (162)
Biomass‐ and solid waste‐derived sustainable single‐atom catalysts (Sus‐SACs) provide a cost‐effective and renewable approach to catalyst design. This review summarizes precursor selection, including AI‐assisted screening, synthesis strategies with emphasis on ultrafast methods, and advanced characterization techniques.
Hongzhe He +8 more
wiley +1 more source
Tb3+‐Doped Glass‐Ceramic Scintillating Plates and Fibers for X‐Ray Imaging and Flexible Detection
A Tb3+‐doped glass‐ceramic scintillator, with controlled Ba2GdF7 nanocrystal precipitation, was developed through a rational design strategy guided by phase diagrams and molecular dynamics simulations. The obtained material exhibits a high light yield of 41 800 photons/MeV (418%/BGO), a spatial resolution of 25.3 lp/mm, and exceptional thermal ...
Songxuan Liu +6 more
wiley +1 more source
This review provides a bottom‐up evaluation of sodium‐ion battery safety, linking material degradation mechanisms, cell engineering parameters, and module/pack assembly. It emphasizes that understanding intrinsic material stability and establishing coordinated engineering control across hierarchical levels are vital for preventing degradation coupling ...
Won‐Gwang Lim +5 more
wiley +1 more source
Trust‐region filter algorithms utilizing Hessian information for gray‐box optimization
Abstract Optimizing industrial processes often involves gray‐box models that couple algebraic glass‐box equations with black‐box components lacking analytic derivatives. Such systems challenge derivative‐based solvers. The classical trust‐region filter (TRF) algorithm provides a robust framework but requires extensive parameter tuning and numerous ...
Gul Hameed +4 more
wiley +1 more source
A trust‐region funnel algorithm for gray‐box optimization
Abstract Gray‐box optimization, where parts of optimization problems are represented by algebraic models while others are treated as black‐box models lacking analytic derivatives, remains a challenge. Trust‐region (TR) methods provide a robust framework for gray‐box problems through local reduced models (RMs) for black‐box components, but they are ...
Gul Hameed +4 more
wiley +1 more source
Harnessing Machine Learning to Understand and Design Disordered Solids
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley +1 more source
REWW‐ARM—Remote Wire‐Driven Mobile Robot: Design, Control, and Experimental Validation
The Remote Wire‐Driven robot “REWW‐ARM” demonstrates a new concept of remote actuation that separates electronics from harsh environments while retaining closed‐loop control. Combining tendon‐sheath mechanisms with decoupled joints, it achieves efficient power transmission and autonomous locomotion, manipulation, and underwater operation, suggesting ...
Takahiro Hattori +4 more
wiley +1 more source
ABSTRACT Liquid hydrogen, a zero‐carbon and high–energy‐density fuel, is a promising option for future oceangoing vessels. During maritime transportation, onboard cryogenic tanks are exposed to ambient heat leakage and ship‐induced roll motion, which can trigger sloshing and fundamentally modify the coupled thermo‐fluid processes governing boil‐off and
Yan Deng +5 more
wiley +1 more source
Risk‐aware safe reinforcement learning for control of stochastic linear systems
Abstract This paper presents a risk‐aware safe reinforcement learning (RL) control design for stochastic discrete‐time linear systems. Rather than using a safety certifier to myopically intervene with the RL controller, a risk‐informed safe controller is also learned besides the RL controller, and the RL and safe controllers are combined together ...
Babak Esmaeili +2 more
wiley +1 more source
This review presents a comprehensive summary and discussion of some optimization strategies for enhancing room‐temperature ionic conductivity of Na3Zr2Si2PO12 (NZSP) solid electrolyte for solid‐state sodium batteries, including foreign‐ion doping or substitution, sintering behavior modulation, and regulation of chemical composition based on precursors.
Jiawen Hu +5 more
wiley +1 more source

