Results 231 to 240 of about 451,390 (293)
Fundamentals of Transport in Polymers and Membranes-Honorary Issue for Professor Giulio C. Sarti. [PDF]
De Angelis MG, Minelli M.
europepmc +1 more source
This work introduces photo‐crosslinkable tyraminated poly(vinyl alcohol)‐gelatin (PVA‐GT) hydrogels as tunable injectable platforms for tissue engineering and growth factor delivery applications. This schematic illustrates the two developed hydrogel formulations and the experimental workflow used to evaluate their physico‐chemical properties in vitro ...
Alessia Longoni +15 more
wiley +1 more source
Recent Advances in Advanced Membrane Materials for Natural Gas Purification: A Review of Material Design and Separation Mechanisms. [PDF]
Fan Q +5 more
europepmc +1 more source
Machine learning–guided engineering of a plectasin‐derived peptide yields DC05, a potent antimycobacterial candidate. Encapsulation into tuftsin‐functionalized mesoporous silica nanoparticles enhances intracellular delivery, stability, and activity against Mycobacterium tuberculosis while maintaining low cytotoxicity and minimal hemolysis. The combined
Christian S. Carnero Canales +12 more
wiley +1 more source
Structural Insights Into CO<sub>2</sub> Transport Pathways in a W-Formate Dehydrogenase: Structural Basis for CO<sub>2</sub> Reduction. [PDF]
Vilela-Alves G +8 more
europepmc +1 more source
A paracrine factor local gradient (PFLG)‐generating system enables microvessel penetration across 3D hepatocyte tissues. The resulting vascularized constructs recapitulate hepatic sinusoidal hepatocyte—endothelial contact architecture and enhance hepatic functions in vitro.
Yen‐Hsiang Huang +2 more
wiley +1 more source
Gas separation with binary-cooperative heterogeneous membranes. [PDF]
Wang B +8 more
europepmc +1 more source
Asymmetrical covalent organic framework mixed matrix membranes for highly efficient gas separation. [PDF]
Qi LH +6 more
europepmc +1 more source
Transport of Carbon Dioxide, Methane, Oxygen and Nitrogen in a Glassy Polyimide Membrane. [PDF]
Tańczyk M +4 more
europepmc +1 more source
Physics-Informed Machine Learning for Carbonation Depth Prediction in Concrete. [PDF]
Abbas MM, Bărbulescu A.
europepmc +1 more source

