Results 111 to 120 of about 1,438,246 (328)

Topology‐Aware Machine Learning for High‐Throughput Screening of MOFs in C8 Aromatic Separation

Advanced Intelligent Discovery, EarlyView.
We screened 15,335 Computation‐Ready, Experimental Metal–Organic Frameworks (CoRE‐MOFs) using a topology‐aware machine learning (ML) model that integrates structural, chemical, pore‐size, and topological descriptors. Top‐performing MOFs exhibit aromatic‐enriched cavities and open metal sites that enable π–π and C–H···π interactions, serving as ...
Yu Li, Honglin Li, Jialu Li, Wan‐Lu Li
wiley   +1 more source

Lobachevski descubridor de la Geometría Hiperbólica

Revista de Matemática: Teoría y Aplicaciones, 2012
We offer an overview of the geometric studies of the russian mathematician N.I. Lobachevski (1792?1856), which culminated with the discovery of the hyperbolic geometry.
Juan Boza Cordero
doaj   +1 more source

Whirl-similitudes, euclidean kinematics, and non-euclidean geometry [PDF]

, 1942
Jacob Feld
openalex   +1 more source

Solving olympiad geometry without human demonstrations

Nature
Proving mathematical theorems at the olympiad level represents a notable milestone in human-level automated reasoning1–4, owing to their reputed difficulty among the world’s best talents in pre-university mathematics. Current machine-learning approaches,
Trieu H. Trinh, Yuhuai Wu, Quoc V. Le, He He, Thang Luong   +4 more
semanticscholar   +1 more source

A Generalized Framework for Data‐Efficient and Extrapolative Materials Discovery for Gas Separation

Advanced Intelligent Discovery, EarlyView.
This study introduces an iterative supervised machine learning framework for metal‐organic framework (MOF) discovery. The approach identifies over 97% of the best performing candidates while using less than 10% of available data. It generalizes across diverse MOF databases and gas separation scenarios.
Varad Daoo, Jayant K. Singh
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

Urban Compression Patterns: Fractals and Non-Euclidean Geometries - Inventory and Prospect [PDF]

, 2012
Daniel A. Griffith, Sandra Lach Arlinghaus   +1 more
openalex   +1 more source

Skin‐Conformal Myography for Real‐Time Hand Tracking Using a Laser‐Induced Graphene Strain Sensor Array

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
A skin‐conformal wearable device based on laser‐induced graphene is developed for continuous strain measurement across the circumference of the forearm for gesture recognition and hand‐tracking applications. Post material optimization, the strain sensor array is integrated with a wearable wireless readout circuit for real‐time control of a robotic arm,
Vinay Kammarchedu, Monther AlSiyabi, Aida Ebrahimi   +2 more
wiley   +1 more source

Soft Magnetic Sensor Array for Amphibious Measurement of 3D Muscle Deformation Distribution for Human Motion Recognition

Advanced Intelligent Systems, EarlyView.
This article develops a soft magnetic sensor array to extract 3D and distributional muscle deformations, which has highly consistent measurements in amphibious environments, robustness to hydraulic pressure, and about 200 ms faster response than an inertial measurement unit, achieving over 98% classification accuracy and below 3% phase estimation ...
Yuchao Liu, Zihan Chen, Chuxuan Guo, Zijie Liu, Yibin Chen, Xuan Wu, Zhuo Li, Qining Wang, Jiajie Guo   +8 more
wiley   +1 more source

Riemannian Geometry for the Classification of Brain States with Intracortical Brain Recordings

Advanced Intelligent Systems, EarlyView.
Geometric machine learning is applied to decode brain states from invasive intracortical neural recordings, extending Riemannian methods to the invasive regime where data is scarcer and less stationary. A Minimum Distance to Mean classifier on covariance manifolds uses geodesic distances to outperform convolutional neural networks while reducing ...
Arnau Marin‐Llobet, Sergio Sánchez‐Manso, Arnau Manasanch, Lluc Tresserras, Xinhe Zhang, Yining Hua, Hao Zhao, Melody Torao‐Angosto, Maria V Sanchez‐Vives, Leonardo Dalla Porta   +9 more
wiley   +1 more source