Results 121 to 130 of about 1,801,177 (317)
Dynamics of total extracellular water of the body during the modification of ultrafiltration after artificial circulation [PDF]
, 2018 Nurlan Bayzhigitov +3 more
openalex +1 more source
Artificial Image Data of 2-D Shapes with Different Orientations
, 2021 Florian Pfaff
openalex +1 more source
Advanced Functional Materials, EarlyView.This study examines how pore shape and manufacturing‐induced deviations affect the mechanical properties of 3D‐printed lattice materials with constant porosity. Combining µ‐CT analysis, FEM, and compression testing, the authors show that structural imperfections reduce stiffness and strength, while bulk material inhomogeneities probably enhance ...
Oliver Walker +5 more
wiley +1 more source
Advanced Functional Materials, EarlyView.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
ARTIFICIAL ALTERATION OF A COMMON HORNBLENDE INTO CLAY MINERALS BY HYDROTHERMAL CONDITIONS
, 1972 Hiroshi Tateyama +2 more
openalex +2 more sources
MOFs and COFs in Electronics: Bridging the Gap between Intrinsic Properties and Measured Performance
Advanced Functional Materials, EarlyView.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
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
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