Results 171 to 180 of about 884,004 (326)
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
Reevaluating the Activity of ZIF‐8 Based FeNCs for Electrochemical Ammonia Production
Though receiving much attention, the field of electrochemical nitrogen reduction reaction (eNRR) to ammonia is marked by doubts about whether this reaction is possible in aqueous media. This work sheds light on this question for iron single‐atom on N‐doped carbon (FeNC) catalysts—a class of well‐known catalysts that is also worth testing for the sister
Caroline Schneider +6 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
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
3D porous carbons with tunable density are crucial for energy storage, separations, and load‐bearing applications; however, their fabrication is often constrained by shrinkage during pyrolysis. This study optimizes and demonstrates the versatility of a template–coating pair strategy, producing materials that largely retain their shape and hierarchical ...
Adarsh Suresh +7 more
wiley +1 more source
Thermoelectric temperature sensors are developed that directly measure heat changes during optical‐based neural stimulation with millisecond precision. The sensors reveal the temperature windows for safe reversible neural modulation: 1.4–4.5 °C enables reversible neural inhibition, while temperatures above 6.1 °C cause permanent thermal damage.
Junhee Lee +9 more
wiley +1 more source
In this research, it is demonstrated that dual nitrogen and sulfur doping in hollow carbon spheres creates a tunable coordination environment that stabilizes cationic Pd single atoms as robust organometallic complexes, enabling high selectivity and stability for electrochemical hydrogen peroxide production under harsh acidic and peroxide‐rich ...
Guilherme V. Fortunato +16 more
wiley +1 more source
Microsphere Autolithography—A Scalable Approach for Arbitrary Patterning of Dielectric Spheres
MicroSphere Autolithography (µSAL) enables scalable fabrication of patchy particles with customizable surface motifs. Focusing light through dielectric microspheres creates well defined, tunable patches via a conformal poly(dopamine) photoresist. Nearly arbitrary surface patterns can be achieved, with the resolution set by the index contrast between ...
Elliott D. Kunkel +3 more
wiley +1 more source
Quantile Regression in Epidemiology: Capturing Heterogeneity Beyond the Mean. [PDF]
Gnardellis C.
europepmc +1 more source
Emergent Spin‐Glass Behavior in an Iron(II)‐Based Metal–Organic Framework Glass
A one‐pot, solvent‐free synthesis yields an Fe2+‐based metal‐organic framework (MOF) glass featuring a continuous random network structure. The material exhibits spin‐glass freezing at 14 K, driven by topological‐disorder and short‐range magnetic frustration, showcasing the potential of MOF glasses as a plattform for cooperative magnetic phenomena in ...
Chinmoy Das +8 more
wiley +1 more source

