Results 141 to 150 of about 151,958 (281)

Organic Materials of Tomorrow: Horizons of Artificial Intelligence

Advanced Materials, EarlyView.
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena, J. Terence Blaskovits, Kun‐Han Lin, Denis Andrienko   +3 more
wiley   +1 more source

Artificial intelligence in nursing: advancing clinical judgment and decision-making. [PDF]

Rev Bras Enferm
Vitorino LM, Yoshinari Júnior GH, Lopes-Júnior LC.   +2 more
europepmc   +1 more source

Effectiveness of a theoretically-based judgment and decision making intervention for adolescents. [PDF]

J Youth Adolesc, 2015
Knight DK, Dansereau DF, Becan JE, Rowan GA, Flynn PM.   +4 more
europepmc   +1 more source

Large‐Scale Determination of Frontier Orbital Energies of Disordered Small‐Molecule Organic Semiconductors Using Exciplex Emission Spectra

Advanced Materials, EarlyView.
ABSTRACT Accurately knowing the frontier orbital energies of the structurally disordered small‐molecule organic semiconductors that are used in optoelectronic devices such as organic light‐emitting diodes is required to rationally improve their performance. Here, we show that these energies can be deduced with a large accuracy from the peak energies of
Christian B. McDonald, Hiroki Tomita, Giacomo Cotelli, Louka L. Brüll, Nanno G. de Rooij, Lucas R.L. Norg, Milo Clément, Reinder Coehoorn   +7 more
wiley   +1 more source

Data‐Driven Materials Science for Energy‐Sustainable Applications

Advanced Materials, EarlyView.
Data‐driven approaches powered by artificial intelligence are transforming materials discovery for energy sustainability. This review examines how auto‐generated high‐quality materials databases and domain‐specific language models accelerate research in photovoltaics, thermoelectrics, batteries and magnetic materials. Applications involve extraction of
Jacqueline M. Cole
wiley   +1 more source

Spatial‐Compatibility‐Assisted Molecular Intercalation in MXenes

Advanced Materials, EarlyView.
This work demonstrates a solvent–free NH4F–mediated route for simultaneous Al removal and molecular intercalation in MXenes. Intercalants are selected by comparing their crystallographic X, Y, and Z dimensions with the MXene interlayer spacing, establishing a spatial‐compatibility criterion that rationalizes guest–host matching and enables predictive ...
Minhao Sheng, Xiaoqing Bin, Xiangyang Liu, Yingji Zhao, Wenxiu Que, Yusuke Asakura, Yusuke Yamauchi   +6 more
wiley   +1 more source

Descriptors to Dynamics: A Materials and Device Perspective on in‐Materio Physical Reservoir Computing for Neuromorphic Edge Intelligence

Advanced Materials, EarlyView.
Intrinsic material dynamics are harnessed as computational resources for neuromorphic in‐materio physical reservoir computing. Defects, ionic motion, interfaces, percolation, geometry, and biasing shape transient states that provide fading memory, nonlinearity, and high‐dimensional projection for simple readout. A descriptor‐to‐dynamics framework links
Kshitij RB Singh, Alif Syafiq Kamarol Zaman, Muzhen Xu, Yuki Usami, Saptarshi Das, Hirofumi Tanaka   +5 more
wiley   +1 more source

How “Green” is Your Functional Material? Assessing Environmental Impacts of Multi‐Step Synthetic Protocols in Material Sciences at Various Technology Levels

Advanced Materials, EarlyView.
Environmental Synthesis Radar (ESR) evaluates the environmental impact of (early‐stage) multi‐step chemical syntheses, providing a holistic view by using 18 midpoint impact categories. Unlike conventional life‐cycle assessment (LCA) approaches, ESR reveals three complementary metrics: overall impact Vtotal, environmental hotspots VEF, and critical ...
Laura Plein, Alexander Schommer, Florian Dietrich, Moritz Gutsch, Heike Klesper, Kevin Schuller, Lars Jahnke, Jens Leker, Klaus Meerholz   +8 more
wiley   +1 more source

Breaking Bottlenecks in Solid Electrolyte Discovery With Large Artificial Intelligence Models

Advanced Materials, EarlyView.
Large AI models are presented as a route to break key bottlenecks in solid electrolyte discovery by linking materials databases, machine‐learning interatomic potentials, large language models, and autonomous experiments. This perspective highlights how AI can accelerate the identification of solid electrolytes with fast ion transport, stable interfaces,
Eric Jianfeng Cheng, Min Hong, Zhiquan Zeng, Chuanyu Liu, Qian Wang, Melissa Jane Meadowcroft, Vlad Badilita, Carlos Miguel Costa, Senentxu Lanceros‐Méndez, Ying Li, Chenyao Ma, Weibo Gong, Surendra Kumar Martha, Aloysius Soon, Piao Ma, Di Zhang, Teguh Ariyanto, Sudaryanto, Hiroshi Kakinuma, Jie Zhao, Jiayu Peng, Pengfei Ou, Jun Lu, Shin‐ichi Orimo, Hao Li   +24 more
wiley   +1 more source

Resenha: Intuition in judgment and decision making

Psicologia: Reflexão e Crítica, 2010
Álvaro Machado Dias, Avelino Luiz Rodrigues   +1 more
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