Results 121 to 130 of about 689,445 (290)

Band Alignment in In‐Oxo Metal Porphyrin SURMOF Heterojunctions

Advanced Functional Materials, EarlyView.
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

Quantum chemical study of molecular properties of small branched-chain amino acids in water

Amino Acids
Four aliphatic amino acids—α-aminobutyric acid (AABA), β-aminobutyric acid (BABA), α-aminoisobutyric acid (AAIBA) and β-aminoisobutyric acid (BAIBA) were investigated in water as a solvent by two quantum chemical methods.
Roman Boča, Žofia Rádiková, Juraj Štofko, Beata Vranovičová, Cyril Rajnák   +4 more
doaj   +1 more source

Photoswitching Conduction in Framework Materials

Advanced Functional Materials, EarlyView.
This mini‐review summarizes recent advances in state‐of‐the‐art proton and electron conduction in framework materials that can be remotely and reversibly switched on and off by light. It discusses the various photoswitching conduction mechanisms and the strategies employed to enhance photoswitched conductivity.
Helmy Pacheco Hernandez, Stefan Hecht, Wolfgang Wenzel, Lars Heinke, Mariana Kozlowska   +4 more
wiley   +1 more source

Mechanical Properties of Architected Polymer Lattice Materials: A Comparative Study of Additive Manufacturing and CAD Using FEM and µ‐CT

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, Thierry Roland, Damien Favier, Antoine Egele, Michael Heymann, Cosima Stubenrauch   +5 more
wiley   +1 more source

Dependency of slab geometry on absolute velocities and conditions for cyclicity: insights from numerical modelling [PDF]

, 2012
Gaël Gibert, Muriel Gerbault, Riad Hassani, E. Tric   +3 more
openalex   +1 more source

At‐Home Early Diagnosis of Mastitis: Calibration‐Free Analysis of Sodium to Potassium Ratio in Breast Milk

Advanced Functional Materials, EarlyView.
MAMAWEL is introduced as the first calibration‐free potentiometric sensor for at‐home mastitis diagnosis. By measuring the sodium‐to‐potassium ratio in breast milk, the device reliably differentiates between healthy and mastitis‐affected samples with less than 10% error.
Ali Soleimani, Farbod Amirghasemi, Melissa Banks, Abdulrahman Al‐Shami, Sina Khazaee Nejad, Abdalrhman Sheer, Clare Dominique Sanchez, Haozheng Ma, Daniel Vargas Ramos, Maral P.S. Mousavi   +9 more
wiley   +1 more source

Absolute Geometry Calibration of Distributed Microphone Arrays in an Audio-Visual Sensor Network [PDF]

, 2015
Florian Jacob, Reinhold Haeb‐Umbach
openalex   +2 more sources

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

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

Evaluation of cerebellar aging in MRI images: Fractal analysis compared to Euclidean geometry-based morphometry

Meta-Radiology
Objectives: This study aimed to identify age-related changes in the fractal dimensions of the cerebellum and compare the sensitivity of fractal analysis and conventional Euclidean geometry-based morphometry to cerebellar aging.
Nataliia Maryenko, Oleksandr Stepanenko
doaj   +1 more source