Results 191 to 200 of about 37,594 (263)

Characterization of Mineral Dissolution in Fracture-Pore Type Rocks Using the Lattice Boltzmann Method. [PDF]

ACS Omega
Zhao Z, Zhang Y, Jiang Y, Wu Y, Qin N, He Y.   +5 more
europepmc   +1 more source

Toward a Rational Design of Conjugated Copolymers with Oxygenated Side Chains for Boosting Thermoelectric Properties

Advanced Energy Materials, EarlyView.
The molecular design strategy that integrates both side chain and backbone engineering in diketopyrrolopyrrole‐based conjugated polymers to identify the optimal balance between doping efficiency and microstructural order is demonstrated. Comprehensive spectroscopic, electrochemical, morphological, and structural characterizations reveal that the ...
Taewoong Han, Suhui Sim, Hoimin Kim, Taewoong Yoon, Hyungju Ahn, Seungjoo Chang, Namgyu Park, Hajeong Kim, Shabaz Alam, Dongki Lee, Sungjun Park, Sungjoo Lee, Jaewon Lee, Boseok Kang   +13 more
wiley   +1 more source

Comparison of Kinetic and Fluid Simulation Models for RF Capacitively Coupled Plasmas in Semiconductor Processing. [PDF]

Materials (Basel)
Kim H, Lee MU, Lee HJ.
europepmc   +1 more source

Sulfide‐Based Electrolytes for All‐Solid‐State Sodium Batteries

Advanced Energy Materials, EarlyView.
This review covers the structural features and synthesis strategies of sulfide‐based solid electrolytes, as well as critical challenges related to conductivity, interfacial and moisture stability, and scaling‐up for practical application in Sodium‐based All Solid‐State Batteries.
Han Yang, Luca Weckelmann, Baolin Wu, Chih‐Long Tsai, Luc Raijmakers, Rüdiger‐A. Eichel, Anna Windmüller   +6 more
wiley   +1 more source

Comprehensive Modeling of Acetone Clusters: QTAIM Analysis and QCE Study. [PDF]

J Comput Chem
Baikété J, Malloum A, Conradie J.
europepmc   +1 more source

Prediction of Structural Stability of Layered Oxide Cathode Materials: Combination of Machine Learning and Ab Initio Thermodynamics

Advanced Energy Materials, EarlyView.
In this work, we developed a phase‐stability predictor by combining machine learning and ab initio thermodynamics approaches, and identified the key factors determining the favorable phase for a given composition. Specifically, a lower TM ionic potential, higher Na content, and higher mixing entropy favor the O3 phase.
Liang‐Ting Wu, Milica Zdravković, Dijana Milosavljević, Konstantin Köster, Olivier Guillon, Jyh‐Chiang Jiang, Payam Kaghazchi   +6 more
wiley   +1 more source

The Boltzmann Entropy and Randomness Tests. [PDF]

Entropy (Basel)
Gács P.
europepmc   +1 more source

Active Particles in Tunable Compressible Environments. [PDF]

Small Sci
Tanuku VMSG, Malhotra I, Caprini L, Löwen H, Palberg T, Buttinoni I.   +5 more
europepmc   +1 more source

A Non-Stationary Model for Analysis of Impedance Spectra of Biological Samples. [PDF]

Entropy (Basel)
Janik G, Kamińska U, Kasprzyk M, Niedzicki L, Buchner T.   +4 more
europepmc   +1 more source