Organic Materials of Tomorrow: Horizons of Artificial Intelligence
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena +3 more
wiley +1 more source
Stability Prediction for UGV Based on Drone-Borne LiDAR Terrain Mapping. [PDF]
Körmöczi D +4 more
europepmc +1 more source
Measuring the Hall Effect in Hysteretic Materials
The authors highlight common pitfalls in measuring the Hall effect: in hysteretic magnets, improper data processing can create signals that look exotic but are not real. This Perspective explains the origin of these artifacts and presents practical measurement strategies that help researchers identify reliable Hall responses in complex magnetic ...
Jaime M. Moya +6 more
wiley +1 more source
3D geometry and mechanics of a single apical stem cell ensure helically symmetric plant body in multicellular models. [PDF]
Kamamoto N, Fujimoto K.
europepmc +1 more source
Multifunctional plasmonic optical nanosensor based on ring resonator supercells for early pregnancy diagnosis using urine samples. [PDF]
Khodaie A, Heidarzadeh H, Moghtader MS.
europepmc +1 more source
Surface Topography and Tolerance Quality Evaluation of Polymer Gears Using Non-Contact 3D Scanning Method. [PDF]
Muratović E +7 more
europepmc +1 more source
Machine learning-based prediction of cross-immunity. [PDF]
Resch VE +4 more
europepmc +1 more source
Finite element analysis in foot and ankle arthrodesis. [PDF]
Mangwani J, Zhang H, Li S.
europepmc +1 more source
Trueness of Intraoral Scanners for Edentulous Mandibular Arches With and Without Landmarks. [PDF]
Dessborn FR, Braian M.
europepmc +1 more source
Geometric Accuracy of Workpieces in Grinding
openaire +1 more source

