Results 131 to 140 of about 23,844,245 (252)
We report a novel interpretation method for deep learning models based on feature extraction and clustering. Applying this method to an atomistic line graph neural network (ALIGNN) model trained on optical absorption spectra of 2,681 inorganic compounds obtained from first‐principles calculations, we successfully identify key factors underlying ...
Akira Takahashi +3 more
wiley +1 more source
Crystal Structure Prediction of Inorganic Materials: A Benchmark and Modern Evaluation
Predicting a crystal’s structure from composition alone is a long‐standing challenge in materials discovery. The CSP180 benchmark of 180 inorganic crystals evaluates thirteen crystal structure prediction algorithms requiring no density functional theory (DFT) against DFT‐based baselines across twelve metrics.
Lai Wei +9 more
wiley +1 more source
Smart Bioinspired Material‐Based Actuators: Current Challenges and Prospects
This work gathers, in a review style, an extensive and comprehensive literature overview on the development of autonomous actuators based on synthetic materials, bringing together valuable knowledge from several studies. Furthermore, the article identifies the fundamental principles of actuation mechanisms and defines key parameters to address the size
Alejandro Palacios +4 more
wiley +1 more source
This article reviews the current state of bioinspired soft robotics. The article discusses soft actuators, soft sensors, materials selection, and control methods used in bioinspired soft robotics. It also highlights the challenges and future prospects of this field.
Abhirup Sarker +2 more
wiley +1 more source
The Solar system small bodies: relationship criterion
Разработан μ, ν, Тi-критерий родственности малых тел Солнечной системы, включающий три первых интеграла уравнении движения двукратно осредненной задачи трех тел.
Мусий, В.И. +3 more
core
Accelerating Materials Discovery: A Review of Machine Learning in X‐Ray Absorption Spectroscopy
This review systematically details how machine learning transforms X‐ray absorption spectroscopy (XAS) analysis. It covers advanced deep learning architectures for structure‐spectra mapping and inverse tasks, while discussing key challenges like the simulation‐to‐reality gap.
Melaku Lake Tegegne +5 more
wiley +1 more source
Shape Sensing, Mapping, and Obstacle Avoidance of the Continuum Manipulator in Confined Environments
An integrated sensing framework combines capacitive sensors, IMU, and laser array sensor. The shape reconstruction is finished by backpropagation neural network. Accurate shape estimation (relative error of 1.04%) is maintained under a 110 g tip load, while a miniaturized VL6180X array enables local environmental reconstruction and reactive obstacle ...
Pengyuan Wang +9 more
wiley +1 more source
Abstract Germany's Renewable Energy Sources Act (REA), enacted in 2000 and subsequently amended, subsidized national renewable energy production with fixed feed‐in tariffs for renewable energy sources (RE) from wind, solar, and biogas. Empirical studies suggest that the policy was creating windfall effects for landowners and attribute farmland use ...
Lars Isenhardt +6 more
wiley +1 more source
Nucleosynthetic constraints on the origin of Bennu and CI-like asteroids. [PDF]
Schönbächler M +15 more
europepmc +1 more source
High‐elevation endemic plants predicted to lose habitat from changing climate in Washington State
Abstract Premise High‐elevation plants face unique challenges from potential climate change impacts that will likely require upslope migration into increasingly smaller suitable habitat. This situation is particularly acute for endemic species that by definition occupy small geographic ranges.
Nicholas L. Gjording +4 more
wiley +1 more source

