Results 51 to 60 of about 862 (232)
A flexible freestanding HfO2‐based ferroelectric membrane is achieved via a water‐assisted exfoliation technique using a Sr4Al2O₇ sacrificial layer. The BaTiO3/Hf0.5Zr0.5O2/BaTiO3 heterostructure maintains robust ferroelectricity and exhibits reliable synaptic plasticity.
Han Zhang +13 more
wiley +1 more source
Gradient reproducing kernel particle method [PDF]
Alireza Hashemian, Hossein Shodja
openaire +1 more source
ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray +3 more
wiley +1 more source
A Janus‐like bio‐inspired strategy is proposed for integrally 3D‐printed bimetallic metamaterials. Inspired by shell bilayers, a heat‐resistant AlSiFeMnNiMg alloy and a SiC‐reinforced AlSi10Mg with different SiC volume fractions are arranged as an architected pair.
Zhicheng Dong +5 more
wiley +1 more source
A fully edible wheat bran–algae substrate is fabricated through scalable mould‐compression and spray‐coating, enabling robust, food‐grade platforms for sustainable electronics. A chitosan barrier improves water resistance and ink compatibility, while activated‐carbon conductive films form uniform electrodes with Ohmic behaviour.
Jaz Johari +7 more
wiley +1 more source
A closed‐loop, data‐driven approach facilitates the exploration of high‐performance Si─Ge─Sn alloys as promising fast‐charging battery anodes. Autonomous electrochemical experimentation using a scanning droplet cell is combined with real‐time optimization to efficiently navigate composition space.
Alexey Sanin +7 more
wiley +1 more source
Abstract Despite extensive modeling efforts in extraction research, transient column models are rarely applied in industry due to concerns regarding parameter identifiability and model reliability. To address this, we analyzed uncertainty propagation from estimated parameters in a previously introduced column model and assessed identifiability via ill ...
Andreas Palmtag +2 more
wiley +1 more source
Abstract Bayesian estimation enables uncertainty quantification, but analytical implementation is often intractable. As an approximate approach, the Markov Chain Monte Carlo (MCMC) method is widely used, though it entails a high computational cost due to frequent evaluations of the likelihood function.
Tatsuki Maruchi +2 more
wiley +1 more source
Feature selection combined with machine learning and high‐throughput experimentation enables efficient handling of high‐dimensional datasets in emerging photovoltaics. This approach accelerates material discovery, improves process optimization, and strengthens stability prediction, while overcoming challenges in data quality and model scalability to ...
Jiyun Zhang +5 more
wiley +1 more source
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

