Results 151 to 160 of about 35,242 (295)

When is explainable AI useful?

In this paper I assess the ethical and epistemic utility of explainable AI algorithms. I first distinguish between different types of outputs that AI can have.
Robbins, Scott
core   +1 more source

Encyclopedia of 2D β′‐In2Se3 Growth Using Chemical Vapor Deposition: The Effects of Synthesis Parameters Onto Material Quality

Advanced Engineering Materials, EarlyView.
A distinct semi‐confined inner‐tube chemical vapor deposition geometry enables reproducible, large‐area growth of phase‐pure 2D β′‐In2Se3 from InI + Se precursors. Engineering local vapor transport and optimizing precursor delivery and temperature–time conditions yield uniform continuous films.
Dasun P. W. Guruge, P. Sanju S. Panawala, Joseph F. S. Fernando, Zhenhuan Chen, Chao Zhang, Dong‐Chen Qi, Liangzhi Kou, Konstantin L. Firestein, Dmitri V. Golberg   +8 more
wiley   +1 more source

Designing Polymer Nanocomposites for X‐Ray Shielding: Mechanisms, Architectures, and Scalable Processing

Advanced Engineering Materials, EarlyView.
This review highlights advances in lightweight, lead‐free polymer nanocomposites for diagnostic X‐ray shielding. By linking filler chemistry, dispersion, architecture, and photon interaction mechanisms, it establishes structure–performance relationships guiding material design.
Aklilu G. Messele, Hossein Ipakchi, Tizazu H. Mekonnen   +2 more
wiley   +1 more source

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

Advanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer, Christopher Mai, Luca Eisentraut, Andreas Bund, Ricardo Buettner   +4 more
wiley   +1 more source

Explainable AI for early-stage design

With the merging of vast amounts of data and advanced computing resources, machine learning has become a key tool in helping designers make informed decisions in early-stage design.
Hu, Xin
core   +1 more source

Comparison of Triply Periodic Minimal Surface Energy Absorbers Under Uniaxial Compressive Loading

Advanced Engineering Materials, EarlyView.
This study investigates LCD 3D printed Triply Periodic Minimal Surface (TPMS) structures as mechanical energy absorbers. By comparing various base designs and layered combinations under uniaxial compression, it identifies that a Diamond‐Gyroid sandwich structure offers superior performance.
Sergej Grednev, Noah‐Lean Roschlaub, Anne Jung   +2 more
wiley   +1 more source

Framework for evaluating explainable AI in antimicrobial drug discovery. [PDF]

J Cheminform
Onawole AT, Blaskovich MAT, Zuegg J.
europepmc   +1 more source

All‐in‐One Analog AI Hardware: On‐Chip Training and Inference with Conductive‐Metal‐Oxide/HfOx ReRAM Devices

Advanced Functional Materials, EarlyView.
An all‐in‐one analog AI accelerator is presented, enabling on‐chip training, weight retention, and long‐term inference acceleration. It leverages a BEOL‐integrated CMO/HfOx ReRAM array with low‐voltage operation (<1.5 V), multi‐bit capability over 32 states, low programming noise (10 nS), and near‐ideal weight transfer.
Donato Francesco Falcone, Victoria Clerico, Wooseok Choi, Tommaso Stecconi, Folkert Horst, Laura Bégon‐Lours, Matteo Galetta, Antonio La Porta, Nikhil Garg, Fabien Alibart, Bert Jan Offrein, Valeria Bragaglia   +11 more
wiley   +1 more source

Explainable AI in kidney stone detection and segmentation: a mini review. [PDF]

Front Digit Health
Hossen MJ, Haque BMT, Bannah H, Rahman MA, Ahmed A, Noman AA.   +5 more
europepmc   +1 more source

Polarizable Vanadium Dipoles Promote Water Dissociation on Vanadium‐Based Metal Organic Framework

Advanced Functional Materials, EarlyView.
The polarization of unpaired V 3d electrons weakens the H─O bond to improve water dissociation by the dual Vδ+:O─H and Pλ−:H─O coupling hydrogen bonds formation and relaxation. P@V‐MOF electrocatalyst shows low overpotentials (94 mV in acid, 178 mV in neutral, and 77 mV in alkaline solutions) with excellent stability for effective overall water ...
Xinjuan Liu, Jun Xu, Minmin Fan, Jingcheng Xu, Mengyuan Li, Yun Gong, Weiwei Yang, Lei Li, Yong Zhou, Deqiang Zhao, Yuhua Xue, Xingtao Xu, Chang Q. Sun, Liming Dai   +13 more
wiley   +1 more source