Results 151 to 160 of about 1,268,311 (320)
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 +8 more
wiley +1 more source
Translations on the Triangular Grid
, 2019 The concept of the grid is broadly used in digital geometry and other fields of computer science; it consists of discrete points with integer coordinates. Coordinate systems are essential for making grids easy to use. Up to now, for the triangular grid, only discrete coordinate systems have been investigated.
openaire +1 more source
A Unifying Approach to Self‐Organizing Systems Interacting via Conservation Laws
Advanced Intelligent Discovery, EarlyView.The article develops a unified way to model and analyze self‐organizing systems whose interactions are constrained by conservation laws. It represents physical/biological/engineered networks as graphs and builds projection operators (from incidence/cycle structure) that enforce those constraints and decompose network variables into constrained versus ...
F. Barrows +7 more
wiley +1 more source
Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning
Advanced Intelligent Discovery, EarlyView.This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
wiley +1 more source
Harnessing Machine Learning to Understand and Design Disordered Solids
Advanced Intelligent Discovery, EarlyView.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
High‐Speed Altitude Regulation With Neuromorphic Camera and Lightweight Embedded Computation
Advanced Intelligent Systems, EarlyView.Neuromorphic cameras deliver rapid, high‐dynamic‐range sensing but overwhelm embedded processors at high speeds. This work presents a lightweight, optimized Lucas–Kanade optical flow method with parallelization, gyroscopic derotation, and adaptive event slicing.
Simon L. Jeger +3 more
wiley +1 more source
Large phase-shifting channel spacing phased array antenna with triangular grid
Tongxin xuebaoPhased arrays with large channel spacing could reduce costs and improve compatibility, but they significantly limit scanning performance. A phased array antenna with a channel spacing of λ0 was designed.
PAN Yangyi, HUANG Zhicheng, LIAO Shaowei
doaj
Reconfiguration of labeled matchings in triangular grid graphs
This paper introduces a new reconfiguration problem of matchings in a triangular grid graph. In this problem, we are given a nearly perfect matching in which each matching edge is labeled, and aim to transform it to a target matching by sliding edges one by one. This problem is motivated to investigate the solvability of a sliding-block puzzle called ``
Kakimura, Naonori, Mishima, Yuta
openaire +4 more sources
Advanced Intelligent Systems, EarlyView.Inspired by the multi‐tissue architecture of the human fingertip dermis (A), this work introduces a mixture design using three PolyJet materials (AC/TM/GM) to expand the achievable elastomer property space (B). An inverse design pipeline (i‐Tac) is developed to map target optical/mechanical requirements to optimal material compositions (C), enabling ...
Wen Fan, Dandan Zhang
wiley +1 more source
Adaptive Macroscopic Ensemble Allocation for Robot Teams Monitoring Spatiotemporal Processes
Advanced Intelligent Systems, EarlyView.We propose an online, environment feedback‐driven macroscopic ensemble approach to adapt robot team task allocation in spatiotemporal environments by controlling robot populations rather than assigning individual robots, all while maintaining robust team performance even for small teams. Our simulation and experimental results show better or comparable
Victoria Edwards +2 more
wiley +1 more source