Results 211 to 220 of about 292,062 (298)

Triplet state homoaromaticity: concept, computational validation and experimental relevance. [PDF]

Chem Sci, 2018
Jorner K, Jahn BO, Bultinck P, Ottosson H.   +3 more
europepmc   +1 more source

A Comprehensive Assessment and Benchmark Study of Large Atomistic Foundation Models for Phonons

Advanced Intelligent Discovery, EarlyView.
We benchmark six large atomistic foundation models on 2429 crystalline materials for phonon transport properties. The rapid development of universal machine learning potentials (uMLPs) has enabled efficient, accurate predictions of diverse material properties across broad chemical spaces.
Md Zaibul Anam, Ogheneyoma Aghoghovbia, Mohammed Al‐Fahdi, Lingyu Kong, Victor Fung, Ming Hu   +5 more
wiley   +1 more source

Bacteriopheophytin triplet state in Rhodobacter sphaeroides reaction centers. [PDF]

Photosynth Res, 2016
Białek R, Burdziński G, Jones MR, Gibasiewicz K.   +3 more
europepmc   +1 more source

Interpretability and Representability of Commutative Algebra, Algebraic Topology, and Topological Spectral Theory for Real‐World Data

Advanced Intelligent Discovery, EarlyView.
This article investigates how persistent homology, persistent Laplacians, and persistent commutative algebra reveal complementary geometric, topological, and algebraic invariants or signatures of real‐world data. By analyzing shapes, synthetic complexes, fullerenes, and biomolecules, the article shows how these mathematical frameworks enhance ...
Yiming Ren, Guo‐Wei Wei
wiley   +1 more source

Delayed Blue Fluorescence via Upper-Triplet State Crossing from C-C Bonded Donor-Acceptor Charge Transfer Molecules with Azatriangulene Cores. [PDF]

Chem Mater, 2019
Ward JS, Kukhta NA, Dos Santos PL, Congrave DG, Batsanov AS, Monkman AP, Bryce MR.   +6 more
europepmc   +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

The origin of efficient triplet state population in sulfur-substituted nucleobases. [PDF]

Nat Commun, 2016
Mai S, Pollum M, Martínez-Fernández L, Dunn N, Marquetand P, Corral I, Crespo-Hernández CE, González L.   +7 more
europepmc   +1 more source

When Biology Meets Medicine: A Perspective on Foundation Models

Advanced Intelligent Discovery, EarlyView.
Artificial intelligence, and foundation models in particular, are transforming life sciences and medicine. This perspective reviews biological and medical foundation models across scales, highlighting key challenges in data availability, model evaluation, and architectural design.
Kunying Niu, Yuxing Wang, Limin Zou, Jing Huang   +3 more
wiley   +1 more source

AI‐Driven Cancer Multi‐Omics: A Review From the Data Pipeline Perspective

Advanced Intelligent Discovery, EarlyView.
The exponential growth of cancer multi‐omics data brings opportunities and challenges for precision oncology. This review systematically examines AI's role in addressing these challenges, covering generative models, integration architectures, Explainable AI for clinical trust, clinical applications, and key directions for clinical translation.
Shilong Liu, Shunxiang Li, Kun Qian
wiley   +1 more source

Economy of Touch : Task‐Driven Information Selection in Electrical Impedance Tomography‐based Tactile Robotic Sensing

Advanced Intelligent Systems, EarlyView.
Electrical impedance tomography (EIT) tactile skins enable multiplexed measurements that trade sensing speed against information richness. This work introduces an economy‐of‐touch framework that treats tactile sensing as an information‐budgeting problem.
Xiaoxian Xu, David Hardman, Fumiya Iida
wiley   +1 more source