Results 141 to 150 of about 8,744,702 (255)

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

Phase Engineering of Nanomaterials (PEN): Evolution, Current Challenges, and Future Opportunities

Advanced Materials, EarlyView.
This review summarizes the synthesis, phase transition, advanced characterization spanning ex situ to in situ and operando techniques, and diverse applications of phase engineering of nanomaterials (PEN). It further outlines key challenges and future opportunities, such as phase stability, architecture control, and artificial intelligence (AI)‐driven ...
Ye Chen, Zhanxi Fan, Jingjie Ge, Qiyuan He, Zhuangchai Lai, Jiawei Liu, Chaoliang Tan, Hua Zhang   +7 more
wiley   +1 more source

Radiative Thermal Management for Extreme Environments: Mechanisms and Design Strategies

Advanced Materials, EarlyView.
In this review, we discuss the fundamental mechanisms of radiative cooling and solar heating, material and structural design strategies, hybrid approaches integrating additional heat transfer pathways, and durability‐oriented designs addressing environmental stresses.
Hyung Rae Kim, Haeseong Kim, Joo Hwan Ko, Gil Ju Lee, Dae‐Hyeong Kim, Young Min Song   +5 more
wiley   +1 more source

Inverse Design of Nanoparticulate Materials

Advanced Materials, EarlyView.
Inverse design shifts nanomaterial development from empirical trial‐and‐error to predictive model‐driven strategies. It can rely on knowledge‐based, data‐based, or hybrid process and property functions. This perspective article provides a practical framework for applying inverse design based on instructive examples. It discusses which modeling approach
Nabi Etienne Traoré, Annika Mauch, Michelle Berthold, Lukas Pflug, Wolfgang Peukert, Nicolas Vogel   +5 more
wiley   +1 more source

Perspective of artificial intelligence (AI) and machine learning (ML) in fisheries science [PDF]

‬‭Majallah-i ̒Ilmī-i Shīlāt-i Īrān
Introduction The integration of artificial intelligence and emerging technologies into fisheries science has fundamentally transformed marine resource management approaches (Bradley et al., 2019; Ebrahimi et al., 2021).
Azin Ahmadi, Ali Haghi Vayghan
doaj  

Accelerated Materials Discovery Through In Situ X‐ray Diffraction: Solvothermal Formation of PdxMy (M═Si, Ge, Sn, Pb) Intermetallic Nanoparticles

Advanced Materials, EarlyView.
In situ PXRD data on solvothermal reactions accelerate materials discovery while simultaneously providing fundamental insights into complex crystal formation processes. Using PdxMy (M = Si, Ge, Sn, Pb) as an example, a general formation mechanism is identified, and specific synthesis strategies for ex situ preparation of SnPd2, Sn13Pd20, and SnPd ...
Anders Bæk Borup, Bo Brummerstedt Iversen   +1 more
wiley   +1 more source

TF-Slim: A Lightweight Library for Defining, Training and Evaluating Complex Models in TensorFlow

, 2017
Presented at CS 7643 Deep Learning on September 7, 2017 from 4:30 p.m. – 5:45 p.m. in the Clough Undergraduate Learning Commons (CULC), Room 144, Georgia Tech.Nathan Silberman is the Lead Deep Learning Scientist at 4Catalyzer where he works on a variety
Silberman, Nathan
core  

The Institute for Ethics and Machine Learning

, 2020
The Institute for Ethical AI & Machine Learning is a UK-based research centre that carries out highly-technical research into processes and frameworks that support the responsible development, deployment and operation of machine learning ...
The Institute for Ethics and Machine Learning
core  

Demagnetization‐Driven Nanoscale Chirality‐Selective Phonon Transport

Advanced Materials, EarlyView.
Chiral heat flow is switched in a ferromagnet/chiral α‐SiO2 heterostructure by controlling the angular momentum of demagnetization‐driven chiral phonons. When phonon handedness matches the crystal chirality, nanoscale thermal transport is enhanced; the opposite handedness suppresses transport, establishing a magnetization‐tunable chiral phonon diode ...
In Hyeok Choi, Daeheon Kim, Yeon Jong Jin, Seungmo Yang, Tae‐Seong Ju, Changsoo Kim, Chanyong Hwang, Dongbin Shin, Jong Seok Lee   +8 more
wiley   +1 more source

Machine Learning in Microwave Medical Imaging and Lesion Detection

Machine learning (ML) techniques have attracted many microwave researchers and engineers for their potential to improve performance in microwave- and millimeter-wave-based medical applications. This paper reviews ML algorithms, data acquisition, training
Wenyi Shao
core   +1 more source