A new data‐efficient framework combining DFT calculations, a neural network model, and automated graph analysis of catalytic reaction networks is proposed and applied to CO2 hydrogenation on transition metal nanoparticles. The analysis shows how efficient C2 oxygenate production requires a balance between CHx formation, C–C coupling, protonation, and ...
Mikhail V. Polynski, Sergey M. Kozlov
wiley +1 more source
A Combined Transcriptomic and Machine Learning Study Reveals PAX8 as a Promising Diagnostic Biomarker in Endometriosis. [PDF]
Zhu X +5 more
europepmc +1 more source
Electromagnetic Radiation Stimulated Learning in Perovskite Nickelates
ABSTRACT Biological plasticity refers to the ability of synapses to strengthen or weaken over time. These adaptive properties play a fundamental role in learning and memory, spanning many orders of magnitude in timescales. Short‐term plasticity (STP) arises from rapid correlative activity, while long‐term plasticity (LTP) is governed by slower ...
Ranjan Kumar Patel +8 more
wiley +1 more source
Machine Learning Accelerated Global Search for Adsorption Geometries of Merocyanine Molecule on Hexagonal Boron Nitride. [PDF]
Tomar R, Bredow T.
europepmc +1 more source
Mechanistic Understanding of Protein–MOF Integration Through Surfactant‐Driven Interfacial Design
This study reveals how surfactant‐driven interfacial design governs the assembly and stability of protein@MOF composites. Using lipid‐based nonionic surfactants, we modulate protein–MOF interactions to improve encapsulation efficiency, MOF crystallization, and catalytic performance.
Ehsan Rashidniyaghi +4 more
wiley +1 more source
Ultrasound-Clinical Machine Learning Models for Differentiating Early Cervical Cancer from Myoma: A Retrospective Exploratory Study. [PDF]
Yin L, Lv F.
europepmc +1 more source
Multiferroic order parameters – polarization, magnetization, and ferroelastic strain – are positioned as dynamic design variables for batteries. Their mechanistic roles, practical tuning through fabrication and external fields, and ferroic‐resolved characterization routes are unified into a closed‐loop framework, revealing how coupled ferroic responses
Jiaqi Su +13 more
wiley +1 more source
Modelling the impact of dietary diversity on child nutrition in Pakistan: a machine learning analysis with Shapley Additive exPlanations and Boruta interpretability. [PDF]
Shahid M +6 more
europepmc +1 more source
AI‐Physics‐Experiment Trinity for Integrated Protein Dynamics Modeling
This review unites experiments, physics‐based simulations, and AI as a synergistic triad for protein dynamics modeling. It highlights integrative strategies, resolves sampling and forcefield bottlenecks, and outlines challenges and future directions for accurate, interpretable conformational ensemble prediction.
Chen Shi +4 more
wiley +1 more source
Synthesis and machine learning techniques to enable data-driven investigation of supramolecular host-guest interactions. [PDF]
Shaurya A +4 more
europepmc +1 more source

