Results 181 to 190 of about 4,772,239 (326)

Generative and Experimental Validation of High Refractive Index Polymers via Domain Knowledge Approach with Small Data

Advanced Intelligent Discovery, EarlyView.
This research demonstrates that the combination of domain knowledge–based multiple regression, multi‐objective Bayesian optimization, and generative models is a suitable prediction tool for candidates of high refractive index polymers, even with the constraints in the model trained on limited data. The experimental validation can reproduce the proposed
Takuya Yokoo, Seigo Watanabe, Hana Matsunaga, Kenichi Oyaizu   +3 more
wiley   +1 more source

Catalyst‐Specialized Chemical Language Model Based on Transformer Variational Autoencoder for Catalyst Design and Discovery

Advanced Intelligent Discovery, EarlyView.
We present CatTransVAE, a catalyst‐specialized chemical language model (CLM) built on a transformer variational autoencoder (VAE), developed through pretraining on general compounds followed by fine‐tuning on diverse catalyst databases. A template‐guided generation framework is introduced to enable controlled catalyst design under structural ...
Apakorn Kengkanna, Masahito Ohue
wiley   +1 more source

Crystal Structure Prediction of Inorganic Materials: A Benchmark and Modern Evaluation

Advanced Intelligent Discovery, EarlyView.
Predicting a crystal’s structure from composition alone is a long‐standing challenge in materials discovery. The CSP180 benchmark of 180 inorganic crystals evaluates thirteen crystal structure prediction algorithms requiring no density functional theory (DFT) against DFT‐based baselines across twelve metrics.
Lai Wei, Sadman Sadeed Omee, Rongzhi Dong, Nihang Fu, Yuqi Song, Edirisuriya M. Dilanga Siriwardane, Meiling Xu, Ming Hu, Chris Wolverton, Jianjun Hu   +9 more
wiley   +1 more source

A NEAT Approach to Evolving Neural‐Network‐Based Optimization of Chiral Photonic Metasurfaces: Application of a NeuroEvolution‐of‐Augmenting‐Topologies Pipeline

Advanced Intelligent Systems, EarlyView.
Neuro‐evolution can boost machine‐learning optimization of chiral metasurfaces. By integrating the NEAT algorithm into a deep‐learning framework, we enable the efficient design of visible‐spectrum chiroptical responses. NEAT autonomously evolves neural‐network architectures and weights, reducing manual tuning.
Davide Filippozzi, Arash Rahimi‐Iman
wiley   +1 more source

Ultralow‐Power Floating‐Gate InGaZnO Content‐Addressable Memory for Wearable Electrocardiogram Anomaly Detection

Advanced Intelligent Systems, EarlyView.
This study introduces a subthreshold in‐memory anomaly detection architecture for wearable ECG monitoring using floating‐gate IGZO content‐addressable memories on a flexible substrate. Area‐engineered coupling provides a high subthreshold slope, while subthreshold operation realizes intrinsic exponential distance evaluation and linear voltage sensing ...
Hyung‐Jun Noh, Sunyeol Bae, Yumin Yun, Junhyeong Park, Soo‐Yeon Lee   +4 more
wiley   +1 more source

Accelerating Materials Discovery: A Review of Machine Learning in X‐Ray Absorption Spectroscopy

Advanced Intelligent Systems, EarlyView.
This review systematically details how machine learning transforms X‐ray absorption spectroscopy (XAS) analysis. It covers advanced deep learning architectures for structure‐spectra mapping and inverse tasks, while discussing key challenges like the simulation‐to‐reality gap.
Melaku Lake Tegegne, Haodong Yao, Liyuan Wu, Yihe Pang, Fazhi Qi, Lina Zhao   +5 more
wiley   +1 more source

Dual‐View Representation Learning for Deployable Humanoid Whole‐Body Control

Advanced Intelligent Systems, EarlyView.
Humanoid robots must learn control from limited onboard sensing, although simulation provides richer training‐only states. DVP learning pairs these views of each simulated motion and aligns their latent control features inside the policy‐learning loop. This direct, deployment‐aware supervision accelerates learning while the deployed policy relies only ...
Haolin Song, Wengang Zhou, Mingxiao Feng, Houqiang Li   +3 more
wiley   +1 more source

Advancing Environmental Sustainability: The Role of Artificial Intelligence in Monitoring, Predicting, and Controlling Sulfur Dioxide Emissions

Asia-Pacific Journal of Chemical Engineering, EarlyView.
ABSTRACT Air pollution from sulfur dioxide (SO2) emissions poses significant threats to environmental sustainability, public health, and climate change efforts. Despite advances in monitoring and regulatory frameworks, traditional methods often fall short in accuracy, scalability, and efficiency.
Turkan Kopac
wiley   +1 more source

Enzymatic Electrosynthesis for Sustainable CO2 Conversion: Advancing Circular Carbon Economy

Carbon Energy, EarlyView.
Enzymatic electrosynthesis (EES) offers molecular precision in synthesizing value‐added products from CO2. We highlight its distinct edge over alternative enzyme‐hybrid systems and analyze electron transfer pathways. Key strategies to overcome electron transfer bottlenecks and expand product diversity are addressed, and also data‐driven approaches for ...
Yan Xie, Jia Ouyang, Manu Suvarna, Xiangzhou Yuan, Matthew R. Hill, Uwe Bornscheuer, Huiyan Zhang, Yong Sik Ok   +7 more
wiley   +1 more source

AI‐Enabled Precision Dosing in Pediatrics: Enhancing Model‐Informed Decision Making

Clinical Pharmacology &Therapeutics, EarlyView.
Ensuring safe and effective pharmacotherapy for children remains a central challenge in clinical pharmacology, yet rapid advances in AI have not translated into clinical practice. This Perspective highlights how AI‐enabled approaches can enhance model‐informed decision making for precision dosing.
Kei Irie, Tomoyuki Mizuno
wiley   +1 more source