Results 161 to 170 of about 2,392,377 (346)

Unveiling Phonon Contributions to Thermal Conductivity and the Applicability of the Wiedemann—Franz Law in Ruthenium and Tungsten Thin Films

Advanced Functional Materials, EarlyView.
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, Pravin Karna, Niraj Bhatt, Sandip Thakur, Helge Heinrich, Daniel M. Hirt, Saman Zare, Christopher Jezewski, Rinus T.P. Lee, Kandabara Tapily, John T. Gaskins, Colin D. Landon, Sean W. King, Ashutosh Giri, Patrick E. Hopkins   +14 more
wiley   +1 more source

Decoupling Size and Electronic Effects in Doped SrTiO3 Photocatalysts Through Surface Area–Normalized CO2 Hydrogenation Rates

Advanced Functional Materials, EarlyView.
Exploring the photocatalytic reverse water–gas shift (RWGS) reaction on doped SrTiO3 nanoparticle films, reveals that normalizing catalytic rates by the catalyst's specific surface area (SSA) disentangled surface area effects from the catalyst's intrinsic material properties.
Dikshita Bhattacharyya, Baliana Shani, Isaac Holmes‐Gentle, Gerardo T Martinez, Martyn McLachlan, Nicola Seriani, Ludmilla Steier   +6 more
wiley   +1 more source

Soil Temperature and Moisture Forecasting Using Exponential Smoothing Method Based on Mean Absolute Percentage Error [PDF]

Muhamad Nur Azmi Wahyudi, Cucuk Wawan Budiyanto, Mohd Shafie Bakar   +2 more
openalex   +1 more source

Electroactive Metal–Organic Frameworks for Electrocatalysis

Advanced Functional Materials, EarlyView.
Electrocatalysis is crucial in sustainable energy conversion as it enables efficient chemical transformations. The review discusses how metal–organic frameworks can revolutionize this field by offering tailorable structures and active site tunability, enabling efficient and selective electrocatalytic processes.
Irena Senkovska, Yutong Luo, Ruyan Zhao, Jianjun Zhang, Mingchao Wang, Xinliang Feng, Eike Brunner, Stefan Kaskel   +7 more
wiley   +1 more source

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

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

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

Mean Absolute Error (MAE) with time for gender groups.

Joel Jaskari (13165410), Chandreyee Roy (21492676), Fumiko Ogushi (6296846), Mikko Saukkoriipi (22822171), Jaakko Sahlsten (13165413), Kimmo Kaski (74278)   +5 more
openalex   +1 more source

SpaiNN: equivariant message passing for excited-state nonadiabatic molecular dynamics. [PDF]

Chem Sci
Mausenberger S, Müller C, Tkatchenko A, Marquetand P, González L, Westermayr J.   +5 more
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