Results 91 to 100 of about 16,552 (267)
Electroactive Metal–Organic Frameworks for Electrocatalysis
Electrocatalysis is crucial in sustainable energy conversion as it enables efficient chemical transformations. The review discusses how metal–organic frameworks can revolutionize this field by offering tailorable structures and active site tunability, enabling efficient and selective electrocatalytic processes.
Irena Senkovska +7 more
wiley +1 more source
Bio‐based and (semi‐)synthetic zwitterion‐modified novel materials and fully synthetic next‐generation alternatives show the importance of material design for different biomedical applications. The zwitterionic character affects the physiochemical behavior of the material and deepens the understanding of chemical interaction mechanisms within the ...
Theresa M. Lutz +3 more
wiley +1 more source
The manufacturing industry encounters numerous optimization problems, one of which is the optimization of storage location assignment (OSLA) problem in logistics. OSLA is a combinatorial optimization problem focused on improving the efficiency of picking
Hiromitsu Kigure +3 more
doaj +1 more source
Approximation algorithms for combinatorial multicriteria optimization problems [PDF]
AbstractThe computational complexity of combinatorial multiple objective programming problems is investigated. NP‐completeness and #P‐completeness results are presented. Using two definitions of approximability, general results are presented, which outline limits for approximation algorithms.
openaire +2 more sources
MOFs and COFs in Electronics: Bridging the Gap between Intrinsic Properties and Measured Performance
Metal‐organic frameworks (MOFs) and covalent organic frameworks (COFs) hold promise for advanced electronics. However, discrepancies in reported electrical conductivities highlight the importance of measurement methodologies. This review explores intrinsic charge transport mechanisms and extrinsic factors influencing performance, and critically ...
Jonas F. Pöhls, R. Thomas Weitz
wiley +1 more source
Unleashing the Power of Machine Learning in Nanomedicine Formulation Development
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore +7 more
wiley +1 more source
Inapproximability of Combinatorial Optimization Problems
We survey results on the hardness of approximating combinatorial optimization problems.
openaire +2 more sources
This study investigates electromechanical PUFs that improve on traditional electric PUFs. The electron transport materials are coated randomly through selective ligand exchange. It produces multiple keys and a key with motion dependent on percolation and strain, and approaches almost ideal inter‐ and intra‐hamming distances.
Seungshin Lim +7 more
wiley +1 more source
Photonic Engineering Enables All‐Passive Upconversion Imaging with Low‐Intensity Near‐Infrared Light
A passive upconversion imaging system enables the observation of scenes illuminated by low‐intensity incoherent near‐infrared light from 750 to 930 nm, by converting it into the visible without the use of external power. The upconverter is enabled by triplet–triplet annihilation in a bulk heterojunction, with absorption enhanced by plasmonic resonators
Rabeeya Hamid +13 more
wiley +1 more source
This research presents a novel implantable bio‐battery, GF‐OsG, tailored for diabetic bone repair. GF‐OsG generates microcurrents in high‐glucose conditions to enhance vascularization, shift macrophages to the M2 phenotype, and regulate immune responses.
Nanning Lv +10 more
wiley +1 more source

