Results 241 to 250 of about 227,714 (275)
AI‐Enhanced Surface‐Enhanced Raman Scattering for Accurate and Sensitive Biomedical Sensing
AI‐SERS advances spectral interpretation with greater precision and speed, enhancing molecular detection, biomedical analysis, and imaging. This review explores its essential contributions to biofluid analysis, disease identification, therapeutic agent evaluation, and high‐resolution biomedical imaging, aiding diagnostic decision‐making.
Seungki Lee, Rowoon Park, Ho Sang Jung
wiley +1 more source
Fully Sequential and Distributed Dynamic Algorithms for Minimum Spanning Trees
P. Mohapatra
openalex +2 more sources
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley +1 more source
Square numbers, spanning trees and invariants of achiral knots
A. Stoimenow
openalex +2 more sources
Machine learning predicts activation energies for key steps in the water‐gas shift reaction on 92 MXenes. Random Forest is identified as the most accurate model. Reaction energy and reactant LogP emerge as key descriptors. The approach provides a predictive framework for catalyst design, grounded in density functional theory data and validated through ...
Kais Iben Nassar+3 more
wiley +1 more source
Tree Graphs and Orthogonal Spanning Tree Decompositions
James Mahoney
openalex +2 more sources
Multistable Composite Laminate Grids as a Design Tool for Soft Reconfigurable Multirotors
Flexible, lightweight, stable: the reconfigurable multirotor combines stable flight in multiple shapes with low‐energy reconfiguration. Utilizing optimized multistable composites, it achieves self‐locking in open and folded configurations, cutting width‐span by 48% and allowing for safe gap traversal.
Luca Girardi+4 more
wiley +1 more source
Robot‐Assisted Measurement of the Critical Micelle Concentration
The study introduces (SIMO) smart integrator for manual operations, a robotic platform for precise, repeatable determination of (CMC) critical micelle concentration in surfactants. SIMO reduces standard deviation by 80% compared to manual methods. Surfactant, dye, and diluent selection, robotic protocols, and data handling are detailed.
Vincenzo Scamarcio+3 more
wiley +1 more source
Advancements in Machine Learning for Microrobotics in Biomedicine
Microrobotics is an innovative technology with great potential for noninvasive medical interventions. However, controlling and imaging microrobots pose significant challenges in complex environments and in living organisms. This review explores how machine learning algorithms can address these issues, offering solutions for adaptive motion control and ...
Amar Salehi+6 more
wiley +1 more source
Predicting Performance of Hall Effect Ion Source Using Machine Learning
This study introduces HallNN, a machine learning tool for predicting Hall effect ion source performance using a neural network ensemble trained on data generated from numerical simulations. HallNN provides faster and more accurate predictions than numerical methods and traditional scaling laws, making it valuable for designing and optimizing Hall ...
Jaehong Park+8 more
wiley +1 more source