Results 71 to 80 of about 196 (182)

Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories

Advanced Energy Materials, EarlyView.
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen, Zheyu Zhang, Kelvian T. Mularso, Bonghyun Jo, Hyun Suk Jung   +4 more
wiley   +1 more source

A Large Scale Multi‐Modal Workflow for Battery Characterization: From Concept to Implementation

Advanced Energy Materials, EarlyView.
Isolated characterization techniques produce independent datasets and single‐property insights. However, progressively more holistic interpretations of battery‐material behavior is needed in the future. Here we demonstrate a coordinated multimodal workflow enabling the correlation of heterogeneous datasets and the construction of multidimensional ...
François Cadiou, Cinthya Herrera, Duncan Atkins, Elixabete Ayerbe, Giorgio Baraldi, Stéphanie Belin, Anass Benayad, Didier Blanchard, Federico Capone, Ennio Capria, Isidora Cekic‐Laskovic, Robert Dominko, Kristina Edström, Ajay Gautam, Lukas Helfen, Antonella Iadecola, Quentin Jacquet, Gregor Kapun, Xinyu Li, Aleksandar Matic, Nataliia Mozhzhukhina, Andrew J. Naylor, Poul Norby, Chris O'Keefe, Alexandre Ponrouch, Jean‐Pascal Rueff, Elena Tchernykova, Deyana Tchitchekova, Israel Temprano, Nikita Vostrov, Marnix Wagemaker, Martin Winter, Christian Wölke, Tejs Vegge, Sandrine Lyonnard   +34 more
wiley   +1 more source

Nanocrystalline LCO/LLZO Composite Cathode Films for Solid State Batteries

Advanced Energy Materials, EarlyView.
A single precursor solution is solution‐deposited and calcined at only 750°C to yield a dense, nanograined LiCoO2/LLZO composite cathode, in which both phases crystallize independently with minimal interdiffusion. Assembled into all‐solid‐state Li‐metal batteries, the composite delivers 111.7 mAh g−1 initial discharge capacity and retains 93% after 100
Lucie Quincke, Steffen Weinmann, Jesse J. Hinricher, Matteo Galasso, Chiara Althammer, Fran Kurnia, Kun Joong Kim, Wolff‐Ragnar Kiebach, Jennifer L. M. Rupp   +8 more
wiley   +1 more source

To criticism of communicative reason: reasons of return of a civilization of images to a starting point / К критике коммуникативного разума: причины возвращения цивилизации изображений к исходной точке

Наука телевидения, 2017
The article is about the nature of communication in modern society and about processes of interaction of civilization and culture. The author considers these questions from different points of view: • as communicative explosion of the XX century as the ...
HRENOV N.A. / ХРЕНОВ Н.А.
doaj  

An Autonomous Large Language Model‐Agent Framework for Transparent and Local Time Series Forecasting

Advanced Intelligent Discovery, EarlyView.
Architecture of the proposed large language model (LLM)‐based agent framework for autonomous time series forecasting in thermal power generation systems. The framework operates through a vertical pipeline initiated by natural language queries from users, which are processed by the LLM Agent Core powered by Llama.cpp and a ReAct loop with persistent ...
William Gouvêa Buratto, Gabriel Villarrubia Gonzalez, Ademir Nied, Laio Oriel Seman, Anne Carolina Rodrigues Klaar, Stefano Frizzo Stefenon   +5 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

Interpretable Machine Learning for Bandgap Prediction and Descriptor‐Guided Design Rules of Phosphates

Advanced Intelligent Discovery, EarlyView.
An explainable CatBoost model was trained to predict the bandgaps of 474 phosphate crystals based on composition and density descriptors. SHAP analysis identified two key variables—d‐electron‐count dispersion and atomic‐density dispersion—as the primary drivers of the model's predictions.
Wenhu Wang, Abudukadi Tudi, Ran An, Zhihua Yang   +3 more
wiley   +1 more source

Data‐Efficient Cycle‐Level Capacity Prediction Using 1D Deep Convolutional Network

Advanced Intelligent Discovery, EarlyView.
We introduce DeepBat, a deep learning framework featuring a 1D convolutional backbone designed to extract latent degradation patterns from a microstructurally diverse electrode dataset. By learning complex formulation–performance relationships, the model accurately predicts long‐term specific discharge capacity using limited early‐cycle data, providing
Tao Huang, Bing Sun, Zhigang Chen, Chenyu Zhao, Eugene Bakker, Yaojie Lei, Lingfei Zhao, Shijian Wang, Chao Liu, Virginia Xiaojun He, Bahram Shirzadi, Hao Liu, Xin Xi, Ruiliu Liu, Dongqing Wu, Guodong Long, Guoxiu Wang   +16 more
wiley   +1 more source

3D Liquid Crystal Framework Enclosing Dual Compartments

Angewandte Chemie, EarlyView.
A new type of liquid crystal phase is reported, having the conjugated rod‐like molecular cores form a 3D framework of elongated octahedral cages filled alternatively with alkyl and fluoroalkyl pendant chains. The cages are held together by flexible H‐bonding hinges, making them adaptable to thermal expansion and stable in a wide temperature range.
Yang‐yang Zhao, Huan‐jun Lu, Helgard Ebert, Xiang‐bing Zeng, Chunlan Ma, Feng Liu, Carsten Tschierske, Goran Ungar   +7 more
wiley   +2 more sources

Machine Learning‐Based Estimation of Experimental Artifacts and Image Quality in Fluorescence Microscopy

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
The use of image quality metrics in combination with machine learning enables automatic image quality assessment for fluorescence microscopy images. The method can be integrated into the experimental pipeline for optical microscopy and utilized to classify artifacts in experimental images and to build quality rankings with a reference‐free approach ...
Elena Corbetta, Thomas Bocklitz
wiley   +1 more source