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Artificial Intelligence‐Assisted Workflow for Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling

Advanced Materials, EarlyView.
AI‐Assisted Workflow for (Scanning) Transmission Electron Microscopy: From Data Analysis Automation to Materials Knowledge Unveiling. Abstract (Scanning) transmission electron microscopy ((S)TEM) has significantly advanced materials science but faces challenges in correlating precise atomic structure information with the functional properties of ...
Marc Botifoll +19 more
wiley +1 more source

Modeling chaotic diabetes systems using fully recurrent neural networks enhanced by fractional-order learning. [PDF]

Sci Rep
Mostafa E, Mahmoud TA, El-Brawany MA.
europepmc +1 more source

Beyond Presumptions: Toward Mechanistic Clarity in Metal‐Free Carbon Catalysts for Electrochemical H2O2 Production via Data Science

Advanced Materials, EarlyView.
Metal‐free carbon catalysts enable the sustainable synthesis of hydrogen peroxide via two‐electron oxygen reduction; however, active site complexity continues to hinder reliable interpretation. This review critiques correlation‐based approaches and highlights the importance of orthogonal experimental designs, standardized catalyst passports ...
Dayu Zhu, Hsi‐wen Wu, Xiao Wang, Jie Zhang +3 more
wiley +1 more source

Population coding and self-organized ring attractors in recurrent neural networks for continuous variable integration. [PDF]

Front Netw Physiol
Kononov R, Tiselko V, Maslennikov O, Nekorkin V. +3 more
europepmc +1 more source

Mesoporous Silica Nanoparticles in Biomedicine: Advances and Prospects

Advanced Materials, EarlyView.
Mesoporous silica nanoparticles offer unique properties like high surface area, tunable pores, and functionalization. They excel in drug delivery, tissue engineering, and stimuli‐responsive therapies, enabling targeted and controlled treatments. With roles in cancer therapy and diagnostics, their clinical translation requires addressing challenges in ...
Miguel Manzano, María Vallet‐Regí
wiley +1 more source

Recurrent neural networks as neuro-computational models of human speech recognition. [PDF]

PLoS Comput Biol
Brodbeck C, Hannagan T, Magnuson JS.
europepmc +1 more source

LEAD: Literature Enhanced Ab Initio Discovery of Nitride Dusting Layers for Enhanced Tunnel Magnetoresistance and Lower Resistance Magnetic Tunnel Junctions

Advanced Materials, EarlyView.
Magnetic tunnel junctions (MTJs) using MgO tunnel barriers face challenges of high resistance‐area product and low tunnel magnetoresistance (TMR). To discover alternative materials, Literature Enhanced Ab initio Discovery (LEAD) is developed. The LEAD‐predicted materials are theoretically evaluated, showing that MTJs with dusting of ScN or TiN on ...
Sabiq Islam +6 more
wiley +1 more source

Training Recurrent Neural Networks for BrdU Detection with Oxford Nanopore Sequencing: Guidance and Lessons Learned. [PDF]

Genes (Basel)
Liu H, Flavahan W, Zhu LJ.
europepmc +1 more source

Topology and Material Optimization in Ultra‐Soft Magneto‐Active Structures: Making Advantage of Residual Anisotropies

Advanced Materials, EarlyView.
Residual magnetization induces pronounced mechanical anisotropy in ultra‐soft magnetorheological elastomers, shaping deformation and actuation even without external magnetic fields. This study introduces a computational‐experimental framework integrating magneto‐mechanical coupling into topology optimization for designing soft magnetic actuators with ...
Carlos Perez‐Garcia +3 more
wiley +1 more source

Addressing the Problem of Lysine Glycation Prediction in Proteins via Recurrent Neural Networks. [PDF]

Biomed Res Int
Que-Salinas U +5 more
europepmc +1 more source

deep learning
neural networks
recurrent neural network

science
gru
lstm

rnn
convolutional neural network