Results 131 to 140 of about 866,547 (282)
Advanced Functional Materials, EarlyView.This study investigates H4TBAPy‐based metal–organic frameworks (MOFs) ‐ NU‐1000, NU‐901, SrTBAPy, and BaTBAPy ‐ for multiphoton absorption (MPA) performance. It observes topology‐dependent variations in the 2PA cross‐section, with BaTBAPy exhibiting the highest activity.
Simon N. Deger +10 more
wiley +1 more source
Laser‐Induced Graphene from Waste Almond Shells
Advanced Functional Materials, EarlyView.Almond shells, an abundant agricultural by‐product, are repurposed to create a fully bioderived almond shell/chitosan composite (ASC) degradable in soil. ASC is converted into laser‐induced graphene (LIG) by laser scribing and proposed as a substrate for transient electronics.
Yulia Steksova +9 more
wiley +1 more source
Defect Analysis of the β– to γ–Ga2O3 Phase Transition
Advanced Functional Materials, EarlyView.The role of defects at all the relevant stages of the β$\beta$‐ to γ$\gamma$‐Ga2O3 polymorph transition is investigated using a multi method approach. The positron annihilation spectroscopy based results show that the defect density decreases after the transition, and that changes in defect configuration within the γ phase occur with increasing ...
Umutcan Bektas +9 more
wiley +1 more source
Advanced Functional Materials, EarlyView.The first cryo‐EM visualization and quantification of oriented Photosystem I (PSI) on single‐layer graphene is reported. Domain‐specific covalent anchoring of PSI, with the reducing side of the biophotocatalyst toward graphene, promotes three‐fold higher anodic photocurrent generation compared to a randomly physisorbed counterpart. This approach allows
Miriam Izzo +6 more
wiley +1 more source
Unleashing the Power of Machine Learning in Nanomedicine Formulation Development
Advanced Functional Materials, EarlyView.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
Clustering Algorithms I: Sequential Algorithms
, 2009 Theodoridis, Sergios +1 more
openaire +2 more sources
Advanced Functional Materials, EarlyView.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
Clustering Algorithms II: Hierarchical Algorithms
, 2009 Theodoridis, Sergios +1 more
openaire +2 more sources
Advanced Functional Materials, EarlyView.We introduce a nucleic acid nanoparticle (NANP) platform designed to be rrecognized by the human innate immune system in a regulated manner. By changing chemical composition while maintaining constant architectural parameters, we identify key determinants of immunorecognition enabling the rational design of NANPs with tunable immune activation profiles
Martin Panigaj +21 more
wiley +1 more source