Results 121 to 130 of about 70,439 (268)
Phase Diagrams and Piezoelectric Properties of Wurtzite Al1−x−yScxGdyN Heterostructural Alloys
This study demonstrates ferroelectricity and piezoelectric properties improvement of quaternary wurtzite Al1−x−yScxGdyN${\rm Al}_{1-x-y}{\rm Sc}_x{\rm Gd}_y{\rm N}$ films, guided by density functional theory calculations. Wurtzite Al1−x−yScxGdyN${\rm Al}_{1-x-y}{\rm Sc}_x{\rm Gd}_y{\rm N}$ films have a high optical bandgap, enhanced piezoelectric ...
Julia L. Martin +11 more
wiley +1 more source
This review comprehensively summarizes the atomic defects in TMDs for their applications in sustainable energy storage devices, along with the latest progress in ML methodologies for high‐throughput TEM data analysis, offering insights on how ML‐empowered microscopy facilitates bridging structure–property correlation and inspires knowledge for precise ...
Zheng Luo +6 more
wiley +1 more source
Longitudinal Morphomolecular Monitoring of Head and Neck Carcinogenesis
A miniaturized endoscopic probe that integrates Raman spectroscopy and optical coherence tomography, enabling simultaneous molecular and structural imaging of living tissue, was developed. Applied longitudinally in a mouse model of head and neck cancer, the system tracks disease progression from precancerous lesions to invasive cancer.
Jianrong Qiu +7 more
wiley +1 more source
The crystalline structure, the atomic numbers of the constituent elementsand the size of MOF crystals each influence their photoluminescence and scintillation properties in distinct ways. Together, these factors provide valuable guidelines for designing systems with optimized performance and tunable timing characteristics, arising from the synergistic ...
Francesca Cova +8 more
wiley +1 more source
A Generative Neuro‐Symbolic AI for Protein Sequence Design
We introduce EffieDes, a neuro‐symbolic framework coupling deep learning‐based fitness landscape parameterization with exact automated reasoning. Unlike greedy sampling, EffieDes identifies sequences that globally optimize fitness while satisfying intricate design constraints.
Marianne Defresne +12 more
wiley +1 more source
Integrability problems for two classes of polynomial differential systems
This paper,using pseudo-division algorithm,introduces a method for computing singular point values of a class of complex polynomial differential systems,establishes the necessary and sufficient conditions for integrability of two classes of complex ...
SANG Bo
doaj
To accelerate the inverse design of heterostructured metal matrix composites, a closed‐loop scientific machine learning framework integrates continual learning prediction with NSGA‐II‐PMCP optimization. The framework maps microstructural descriptors to strength, toughness, and modulus, expands high‐quality Pareto solutions, and guides experimentally ...
Zhiyan Zhong +11 more
wiley +1 more source
Automation and Active Learning for the Multi‐Objective Optimization of Antibody Formulations
Successful antibody formulation necessitates balancing factors such as thermal stability, colloidal stability, and viscosity across a vast excipient design space. This work integrates robotic liquid handling, high‐throughput biophysical characterization, and multi‐objective Bayesian optimization in an iterative closed‐loop Design‐Build‐Test‐Learn cycle.
D. Christopher Radford +3 more
wiley +1 more source
A Unifying Thermodynamic Model for Phase Separation and Aging of Biopolymers
Phase separation and aging of intrinsically disordered proteins are placed in a unifying framework. A thermodynamically consistent time‐dependent version of associating‐polymer theory shows how the processes are intricately coupled. Assuming aging to occur through interacting sites resulting from reversible conformational transitions, the model ...
Jasper J. Michels +2 more
wiley +1 more source

