Results 131 to 140 of about 219,965 (278)

Halide Perovskite Radiation Detectors: Conventional Imaging Applications and New Opportunities

Advanced Functional Materials, EarlyView.
Organic–inorganic hybrid halide perovskite (OIHP) semiconductors, owing to their exceptional optoelectronic properties, are emerging as promising next‐generation integrated radiation detectors for applications in medical radiodiagnosis and healthcare monitoring.
Dou Zhao, Yeon‐Woo Choi, Tomoyuki Yokota, Takao Someya, Nam‐Gyu Park   +4 more
wiley   +1 more source

Functional Materials for Environmental Energy Harvesting in Smart Agriculture via Triboelectric Nanogenerators

Advanced Functional Materials, EarlyView.
This review explores functional and responsive materials for triboelectric nanogenerators (TENGs) in sustainable smart agriculture. It examines how particulate contamination and dirt affect charge transfer and efficiency. Environmental challenges and strategies to enhance durability and responsiveness are outlined, including active functional layers ...
Rafael R. A. Silva, Giulio Fatti, Emanuel Carlos, Guilherme Ferreira, Sumita Goswami, Suman Nandy, Luiz H. C. Mattoso, Elvira Fortunato, Caio G. Otoni, Rodrigo Martins   +9 more
wiley   +1 more source

Unifying machine learning and interpolation theory via interpolating neural networks. [PDF]

Nat Commun
Park C, Saha S, Guo J, Zhang H, Xie X, Bessa MA, Qian D, Chen W, Wanger GJ, Cao J, Hughes TJR, Liu WK.   +11 more
europepmc   +1 more source

Defects Dynamic in Photo‐Excited CeO2 and their Influence on CO2 Photoreduction

Advanced Functional Materials, EarlyView.
X‐ray photoelectron spectroscopy study under light excitation is presented to track the defect dynamic (Ce4+ to Ce3+) in CeO2. Surface enhanced Raman spectroscopy confirmed the key role of Ce3+ states in controlling charge and energy transfer across the CeO2‐dye molecule interface.
Rambabu Yalavarthi, Shashi B. Mishra, Olivier Henrotte, Emiliano Cortes   +3 more
wiley   +1 more source

Numerical simulation of velocity gradient scattering waves in visco-acoustic smooth media based on F-K domain integration method. [PDF]

Sci Rep
Ou T, Chen G, Yang Y, Ren C, Wang Z, Lan P, Wu J, Liu H, Rongjie H.   +8 more
europepmc   +1 more source

Liquid Metals as Initiators of Free‐Radical Polymerization of Hydrogels: A Perspective

Advanced Functional Materials, EarlyView.
Gallium‐based liquid metals initiate free radical polymerization to form hydrogels without the use of toxic molecular initiators. In addition to initiating polymerization, they can act as crosslinkers, yielding softer, more extensible, and tougher hydrogels than those formed with conventional initiators.
Syed Ahmed Jaseem, Pooria Rahmani, Tushar Sakorikar, Jinwoo Ma, Omar Almutairi, Maxim A. Voinov, Alex I. Smirnov, Baihang Chen, Michael D. Dickey   +8 more
wiley   +1 more source

Computationally Efficient DFT-Based Sampling of Ion Diffusion in Crystalline Solids. [PDF]

J Chem Theory Comput
Gustafsson H, Schwarz F, Smolders T, Barthel S, Mace A.   +4 more
europepmc   +1 more source

Phase‐Stable Palladium Hydride Derived from PdCoO2 for Sustainable Hydrogen Evolution Reaction

Advanced Functional Materials, EarlyView.
The exceptionally active β‐PdHx is demonstrated for the hydrogen evolution reaction in acidic media. The fast activation kinetics from the PdCoO2 template are resolved by operando spectroscopy, and isotope‐labeled atom probe tomography quantifies the H content in β‐PdHx. The outstanding stability of the electrocatalyst is attributed to the retention of
Luca Camuti, Se‐Ho Kim, Filip Podjaski, Miquel Vega‐Paredes, Andrea M. Mingers, Tolga Acartürk, Ulrich Starke, Bettina V. Lotsch, Christina Scheu, Baptiste Gault, Siyuan Zhang   +10 more
wiley   +1 more source

Linear and Nonlinear Optical Properties of Molecules from Real-Time Propagation Based on the Bethe-Salpeter Equation. [PDF]

J Chem Theory Comput
Marek Š, Wilhelm J.
europepmc   +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, Cristiano Pesce, Antonietta Greco, Claudia Pisante, Greta Avancini, Valentina Di Francesco, Yosi Shamay, Paolo Decuzzi   +7 more
wiley   +1 more source