Results 231 to 240 of about 2,018,706 (306)

A Critical Assessment of Bonding Descriptors for Predicting Materials Properties

Advanced Intelligent Discovery, EarlyView.
The impact of new bonding descriptors in machine learning models for predicting material properties is assessed. Improvements are validated using significance tests, and new, intuitive descriptors for screening lattice thermal conductivity and projected force constants are introduced.
Aakash Ashok Naik, Nidal Dhamrait, Katharina Ueltzen, Christina Ertural, Philipp Benner, Gian‐Marco Rignanese, Janine George   +6 more
wiley   +1 more source

Rapid rice seed vigor assessment: A machine learning and deep learning framework with multi-time-point image analysis. [PDF]

MethodsX
Kaewbundit V, Onwimol D, Wongchaisuwat P.   +2 more
europepmc   +1 more source

Fluorescent Hydrogel‐Based Strain Sensor With Machine Learning‐Augmented Performance

Advanced Intelligent Discovery, EarlyView.
Fluorescent hydrogel strain sensor based on carbon quantum dots enabling optical readout of deformation through strain‐dependent emission changes, coupled with Random Forest analysis to capture nonlinear fluorescence‐concentration relationships and identify optimal sensing conditions. Hydrogels are ideal matrices for bio‐integrated wearable sensors due
Tailai Chen, Tianlong Liu, Chao Lu, Rimsha Malik, Jin Zhang   +4 more
wiley   +1 more source

Higher plant seed container germination success predicted by smart farming optical RGB approach. [PDF]

Sci Rep
Novikova TP, Tylek P, Petrishchev EP, Novikov AI.   +3 more
europepmc   +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

Cookies, Chips, and Seeds: How Human Food Leftovers Influence Ant-Mediated Seed Removal. [PDF]

Biology (Basel)
Morris B, Iturralde D, Almanza A, Henriquez A, Morales M, Rodríguez D, Santos H, Yángüez J, Castillo R, Gómez CA, González P, Rodríguez C, Acosta S, Alba A, Dominguez L, Marple E, Gálvez D.   +16 more
europepmc   +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

Endangered and Protected Medicinal Plants in Forest Ecosystems: Diversity, Conservation Status, Therapeutic Potential, and Management Strategies. [PDF]

Plants (Basel)
Budau R, Bei MF, Dejeu DA, Gitea MA, Dinca L, Constandache C, Murariu G, Timofte AI, Gitea D.   +8 more
europepmc   +1 more source

Smart Bioinspired Material‐Based Actuators: Current Challenges and Prospects

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
This work gathers, in a review style, an extensive and comprehensive literature overview on the development of autonomous actuators based on synthetic materials, bringing together valuable knowledge from several studies. Furthermore, the article identifies the fundamental principles of actuation mechanisms and defines key parameters to address the size
Alejandro Palacios, Léon Chiriatti, Simon Poppinga, Thomas Speck, Vincent Le Houérou   +4 more
wiley   +1 more source

Recent high-severity wildfires in a dry-conifer landscape are unprecedented over five centuries and foretell future forest loss. [PDF]

Proc Natl Acad Sci U S A
Wion AP, Stevens JT, Coop JD, Farris CA, Parks SA, Allen CD, Margolis EQ.   +6 more
europepmc   +1 more source