Results 231 to 240 of about 1,478,126 (315)
Thermal transport in Ru and W thin films is studied using steady‐state thermoreflectance, ultrafast pump–probe spectroscopy, infrared‐visible spectroscopy, and computations. Significant Lorenz number deviations reveal strong phonon contributions, reaching 45% in Ru and 62% in W.
Md. Rafiqul Islam +14 more
wiley +1 more source
Dynamics of the DNA Viral Community in Korean Coastal Waters. [PDF]
Kim YJ +7 more
europepmc +1 more source
Band Alignment in In‐Oxo Metal Porphyrin SURMOF Heterojunctions
Porphyrin core metalation in indium‑oxo SURMOFs enables systematic tuning of band edge positions without altering the crystal structure. First‑principles calculations reveal type‑I and type‑II heterostructures as well as multi‑junction energy cascades, establishing a modular strategy for exciton funneling and charge separation in optoelectronic ...
Puja Singhvi, Nina Vankova, Thomas Heine
wiley +1 more source
WHO Pandemic Agreement: The need for scientific implementation. [PDF]
Wang H, Yue M.
europepmc +1 more source
Shellular materials form spontaneously by dip coating the primitive triply periodic minimal surface (TPMS) wireframe in an aqueous solution of lyotropic liquid crystalline graphene oxide (GO) nanosheets mixed with polymers. Regulated by surface tension, GO nanosheets align on the polymer soap film as the stress builds up during drying.
Yinding Chi +9 more
wiley +1 more source
Scalable inference and identifiability of kinetic parameters for transcriptional bursting from single cell data. [PDF]
Gu J +5 more
europepmc +1 more source
There is a significant need for biomaterials with well‐defined stability and bioactivity to support tissue regeneration. In this study, we developed a tunable microgel platform that enables the decoupling of stiffness from porosity, thereby promoting bone regeneration.
Silvia Pravato +9 more
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
Protocol for RNA-seq library preparation from low-volume total RNA by RNA/cDNA hybrid tagmentation. [PDF]
Chen Y, Hu Y, Chen X, Xu W.
europepmc +1 more source

