Results 231 to 240 of about 113,357 (317)

A Computational Approach for Biomimetic Design of Liver‐On‐A‐Chip

Advanced Intelligent Discovery, EarlyView.
A biomimetic liver‐on‐a‐chip with antiparallel perfusion was designed using COMSOL‐guided simulation to replicate hepatic acinus transport. Full‐scale modelling revealed diffusion‐dominated, length‐dependent nutrient gradients and low‐shear conditions.
Zhenxu Yang, Qiankun Yin, Qingxin Liu, Zhejun Xu, Ye Zhang, Christopher Vega‐Sánchez, Xiaochen Liu, Daniele Vigolo, Jiao Jiao Li, Ken‐Tye Yong   +9 more
wiley   +1 more source

Adsorption Characteristics and Mechanistic Role of Ionic Species on the Chalcopyrite (112) Surface Based on DFT Simulations. [PDF]

Int J Mol Sci
Rios-Colque L, Robles PA, Quezada GR, Rios-Colque V.   +3 more
europepmc   +1 more source

FastCat: Autonomous Discovery of Multielement Layered Double Hydroxide Alloy Catalysts for Alkaline Oxygen Evolution Reaction

Advanced Intelligent Discovery, EarlyView.
A machine learning‐guided self‐driving laboratory screened over 500 nickel‐based layered double‐hydroxide catalysts for alkaline oxygen evolution. Out of the eight metals, the robot uncovered a quaternary Ni–Fe–Cr–Co catalysts requiring only 231 mV overpotential to reach 20 mA cm−2.
Nis Fisker‐Bødker, Enzo Raffaele Moretti, Jin Hyun Chang, Tejs Vegge   +3 more
wiley   +1 more source

Simulation of deformation characteristics of irregular rock specimens with different mining face lengths. [PDF]

Sci Rep
Zhang Y, Liu X, Wei S, Lin H, Xie J, Ni X.   +5 more
europepmc   +1 more source

Bayesian Exploration of Metal‐Organic Framework‐Derived Nanocomposites for High‐Performance Supercapacitors

Advanced Intelligent Discovery, EarlyView.
An AI‐assisted approach is introduced to decode synthesis–performance relationships in metal‐organic framework‐derived supercapacitor materials using Bayesian optimization and predictive modeling, streamlining the search for optimal energy storage properties.
David Gryc, Pritam Banerjee, Felipe Jacques Lima Duarte, Joerg R. Jinschek, Premkumar Murugesan, Babak Rezaei, Stephan Sylvest Keller, Roland A. Fischer, Mian Zahid Hussain   +8 more
wiley   +1 more source

Discovery of Novel Materials with Giant Dielectric Constants via First‐Principles Phonon Calculations and Machine Learning

Advanced Intelligent Discovery, EarlyView.
We discovered novel materials with giant dielectric constants by combining first‐principles phonon calculations and machine learning. Screening 525 perovskites identified six candidates. RbNbO3 was synthesized under pressure and showed ε ≈ 800–1000. This validates our framework as a powerful tool for high‐performance dielectric materials discovery.
Hiroki Moriwake, Kazuki Shitara, Rie Yokoi, Takeharu Kato, Isao Tanaka, Ayako Yamamoto, Kimitoshi Murase, Yosuke Hamasaiki, Yoshitaka Ehara, Mitsuru Itoh   +9 more
wiley   +1 more source

Study on coal wall spalling mechanism of large mining height working face based on folding mutation theory. [PDF]

Sci Rep
Li G, Zhang H, Li M, Shen Z, Tian A, Wang L.   +5 more
europepmc   +1 more source

Toward Capacitive In‐Memory‐Computing: A Device to Systems Level Perspective on the Future of Artificial Intelligence Hardware

Advanced Intelligent Discovery, EarlyView.
Capacitive, charge‐domain compute‐in‐memory (CIM) stores weights as capacitance,eliminating DC sneak paths and IR‐drop, yielding near‐zero standbypower. In this perspective, we present a device to systems level performance analysis of most promising architectures and predict apathway for upscaling capacitive CIM for sustainable edge computing ...
Kapil Bhardwaj, Ella Paasio, Sayani Majumdar   +2 more
wiley   +1 more source

Automatic identification and feature analysis of Min-ing-Induced surface cracks using an improved DRA-UNet. [PDF]

Sci Rep
Zhou W, Zou Y, Chai H.
europepmc   +1 more source

Advances in Thermal Modeling and Simulation of Lithium‐Ion Batteries with Machine Learning Approaches

Advanced Intelligent Discovery, EarlyView.
Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin, Kang Fu, Junjie Ding, Kai Sun, Peng Tan   +4 more
wiley   +1 more source