Results 191 to 200 of about 36,481,271 (303)

Accelerating the Discovery of Proton Conducting Electrolytes via Machine Learning‐Enabled Literature Mining

open access: yesAdvanced Intelligent Discovery, EarlyView.
An end‐to‐end knowledge discovery framework is established to automate high‐precision property extraction from small, specialized literature corpora. Utilizing a domain‐specific bidirectional encoder representation from a transformer model and data augmentation, the system accurately extracts and structures electrolyte performance data, ultimately ...
Gaheun Shin   +4 more
wiley   +1 more source

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

open access: yesAdvanced 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   +16 more
wiley   +1 more source

Functionalized TiO2 Catalysts: Revolutionary Candidate for Low‐Temperature MgH2 and Prospects for Intelligent Integration

open access: yesAdvanced Intelligent Discovery, EarlyView.
Recent advances in TiO2 modification strategies: structure regulation and composite engineering for improved activity and functionality. TiO2 has emerged as a pivotal catalyst for enhancing MgH2, a high‐capacity solid‐state hydrogen storage material, owing to its structural versatility.
Xiaopeng Chu   +10 more
wiley   +1 more source

Retracted: Time Series Symbolization Method for the Data Mining K-Means Algorithm

open access: yesDiscrete Dynamics in Nature and Society
Discrete Dynamics in Nature and Society
doaj   +1 more source

From Word2Vec to Transformers: Text‐Derived Composition Embeddings for Filtering Combinatorial Electrocatalysts

open access: yesAdvanced Intelligent Discovery, EarlyView.
With the downstream filter held fixed, text‐derived composition representations produce distinct screening outcomes across 14 electrocatalyst libraries. Embedding model and composition encoding control the trade‐off between candidate reduction and preservation of the best measured current.
Lei Zhang, Markus Stricker
wiley   +1 more source

A Multistrategy AI‐Assisted Consensus Screening Pipeline for Discovery of Candidate p53 Monomer Binders

open access: yesAdvanced Intelligent Discovery, EarlyView.
An ultra‐fast small‐sample AI consensus pipeline combines co‐folding and docking to target structure‐lacking p53 monomers. Its optimal mini‐protein binder shows robust interfacial affinity and promising druggability, supplying unprecedented antitumor p53 templates.
Ningyao Li   +9 more
wiley   +1 more source

Investigation of fin model using RNN intelligent computing associated to physical parameters and hybrid nanomaterials. [PDF]

open access: yesDiscov Nano
Shahbaz M   +7 more
europepmc   +1 more source

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