Results 211 to 220 of about 1,787,073 (298)
Photoswitchable Conductive Metal–Organic Frameworks
A conductive material where the conductivity can be modulated remotely by irradiation with light is presented. It is based on films of conductive metal–organic framework type Cu3(HHTP)2 with embedded photochromic molecules such as azobenzene, diarylethene, spiropyran, and hexaarylbiimidazole in the pores.
Yidong Liu +5 more
wiley +1 more source
Biofabrication aims at providing innovative technologies and tools for the fabrication of tissue‐like constructs for tissue engineering and regenerative medicine applications. By integrating multiple biofabrication technologies, such as 3D (bio) printing with fiber fabrication methods, it would be more realistic to reconstruct native tissue's ...
Waseem Kitana +2 more
wiley +1 more source
Lipid nanoparticles (LNPs) are optimized to co‐deliver Cas9‐encoding messenger RNA (mRNA), a single guide RNA (sgRNA) targeting the endogenous cystic fibrosis transmembrane conductance regulator (CFTR) gene, and homologous linear double‐stranded donor DNA (ldsDNA) templates encoding CFTR.
Ruth A. Foley +12 more
wiley +1 more source
Laser‐Induced Graphene from Waste Almond Shells
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
Study on Machine Tool Positioning Uncertainty Due to Volumetric Verification. [PDF]
Aguado S +4 more
europepmc +1 more source
Exploring the photocatalytic reverse water–gas shift (RWGS) reaction on doped SrTiO3 nanoparticle films, reveals that normalizing catalytic rates by the catalyst's specific surface area (SSA) disentangled surface area effects from the catalyst's intrinsic material properties.
Dikshita Bhattacharyya +6 more
wiley +1 more source
Thermal-Feature System Identification for a Machine Tool Spindle. [PDF]
Hu YC, Chen PJ, Chang PZ.
europepmc +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
A microphysiological lung fibrosis model recapitulates myofibroblast–vascular interactions. Induced myofibroblasts and patient‐derived IPF fibroblasts impair angiogenesis and increase vascular permeability via TGF‐β1–driven signaling. Pharmacological interventions with SB 431542 and VEGF supplementation restore vascular morphology and barrier function.
Elena Cambria +7 more
wiley +1 more source
Identification of machine tool squareness errors via inertial measurements. [PDF]
Szipka K +3 more
europepmc +1 more source

