Results 91 to 100 of about 2,574 (191)

Recent advances in data‐driven and artificial intelligence‐integrated perovskite solar cells: From design to self‐driving laboratories

InfoMat, EarlyView.
To address the limitations of conventional trial‐and‐error approaches, perovskite solar cell research is shifting toward a new paradigm that utilizes datasets and AI. This review examines the fundamental elements of data‐driven and AI‐integrated research: data platforms, AI methodologies, and self‐driving laboratories, demonstrating how their ...
Jaehee Lee, Juhwan Noh, Hyunjun Lee, Yea‐Lee Lee, Jino Im, Jangwon Seo   +5 more
wiley   +1 more source

From Latent Manifolds to Targeted Molecular Probes: An Interpretable, Kinome-Scale Generative Machine Learning Framework for Family-Based Kinase Ligand Design. [PDF]

Biomolecules
Verkhivker G, Kassab R, Krishnan K.
europepmc   +1 more source

Biochar‐Induced Shifts in Fungal Community Structure and Their Association With Soil Physical Properties in Degraded Soil From the Brazilian Semiarid

Land Degradation &Development, EarlyView.
ABSTRACT Soil degradation compromises ecosystem functioning. Biochar, a carbon‐rich amendment, has gained attention as a promising strategy to enhance soil structure and restore microbial balance. This study investigated the effects of two biochars, cashew bagasse biochar (CBB) and a co‐pyrolyzed biochar produced from sewage sludge and cashew pruning ...
João Marcos Rodrigues dos Santos, Arthur Prudêncio de Araujo Pereira, Kaio Gráculo Vieira Garcia, Ícaro Vasconcelos do Nascimento, Francisco Luan Almeida Barbosa, Tiago da Costa Dantas Moniz, Gilvanete da Silva Henrique, Murilo de Sousa Almeida, Vania Maria Maciel Melo, Mirian Cristina Gomes Costa, Helon Hébano de Freitas Sousa, Adriana Guirado Artur, Christiana de Fátima Bruce da Silva, Odair Pastor Ferreira, Antônio Gomes de Souza Filho, Erika Valente de Medeiros, Ademir Sergio Ferreira Araujo, Rafael Santiago da Costa, Jaedson Cláudio Anunciato Mota   +18 more
wiley   +1 more source

The topology of representational geometry. [PDF]

Front Neurosci
Brown S, Farivar R.
europepmc   +1 more source

Long‐Range Exciton Energy Transfer in Two‐Dimensional Materials

Laser &Photonics Reviews, EarlyView.
This review highlights recent advances in long‐range exciton energy transfer within planar 2D‐material architectures. It emphasizes the emergence of self‐hybridized excitonpolaritons, exciton coupling to surface plasmon polaritons and plasmonic lattices, and the role of dipoledipole transfer pathways in enabling efficient nanoscale energy transport ...
Paul H. Bittorf, Maximilian Black, Hebrew Crispin, Prabhdeep Singh, Parsa Darman, Sara Darbari, Fatemeh Chahshouri, Masoud Taleb, Nahid Talebi   +8 more
wiley   +1 more source

Transitivity, contextuality and decision making. [PDF]

Philos Trans A Math Phys Eng Sci
Sulis WH.
europepmc   +1 more source

Breaking the Exponential: Decoherence‐Driven Power‐Law Spontaneous Emission in Waveguide Quantum Electrodynamics

Laser &Photonics Reviews, EarlyView.
Introducing dynamical dephasing into the photon modes of a waveguide causes spontaneous emission to switch from conventional exponential decay to a robust power‐law behavior visible at short times. The power law arises from photon diffusion in a dynamically disordered environment, uncovering a previously unexplored, decoherence‐induced pathway to ...
Stefano Longhi
wiley   +1 more source

A cohomology-based Gromov-Hausdorff metric approach for quantifying molecular similarity. [PDF]

Sci Rep
Wee J, Gong X, Tuschmann W, Xia K.
europepmc   +1 more source

Tailoring Spatial Correlations With Quantum Interference

Laser &Photonics Reviews, EarlyView.
Imposing spatial structure on interfering photons fundamentally reshapes their correlations. By controlling the mutual distinguishability of two photons, we write and edit these correlations, encoding information that is invisible to conventional intensity measurements and revealed only through their joint behavior.
Carlo Schiano, Bereneice Sephton, Elnaz Darsheshdar, Lorenzo Marrucci, Corrado de Lisio, Vincenzo D'Ambrosio   +5 more
wiley   +1 more source

Structure‐Aware Machine Learning for Polymers: A Hierarchical Graph Network for Predicting Properties From Statistical Ensembles

Macromolecular Rapid Communications, EarlyView.
This work presents a structure‐aware graph convolutional network that models polymers as statistical ensembles to predict macroscopic properties. By combining topologically realistic graphs generated via kinetic Monte Carlo simulations with explicit molar mass distributions, the framework achieves high accuracy in classifying architectures and ...
Julian Kimmig, Yannik Köster, Timo Koswig, Punith Raviswamy, Subhash V. S. Ganti, Stefan Zechel, Christopher Kuenneth, Ulrich S. Schubert   +7 more
wiley   +1 more source