Results 101 to 110 of about 53,196 (246)

Synergetic Lattice and Surface Engineering: Stable High‐Voltage Cycle Performance in P3‐Type Layered Manganese Oxide

Advanced Energy Materials, EarlyView.
A dual lattice‐surface strategy employing NaTi2(PO4)3 is adopted to enhance the performance of P3‐type Na0.67[Zn0.3Mn0.7]O2, whereby Ti stabilizes the bulk lattice and surface P species mitigate degradation, collectively improving high‐voltage cycling stability, Na+ diffusion, and oxygen redox reversibility through synergistic structural and ...
Natalia Voronina, Konstantin Köster, Jun Ho Yu, Sungkyu Kim, A‐Yeon Kim, Hun‐Gi Jung, Kyuwook Ihm, Koji Yazawa, Hitoshi Yashiro, Aishuak Konarov, Mark Huijben, Olivier Guillon, Payam Kaghazchi, Seung‐Taek Myung   +13 more
wiley   +1 more source

Validating large-scale quantum machine learning: efficient simulation of quantum support vector machines using tensor networks

Machine Learning: Science and Technology
We present an efficient tensor-network-based approach for simulating large-scale quantum circuits exemplified by quantum support vector machines (QSVMs).
Kuan-Cheng Chen, Tai-Yue Li, Yun-Yuan Wang, Simon See, Chun-Chieh Wang, Robert Wille, Nan-Yow Chen, An-Cheng Yang, Chun-Yu Lin   +8 more
doaj   +1 more source

Heterogeneous Resource Selection for Arbitrary HPC Applications in the Cloud

, 2015
Anca Iordache, Eliya Buyukkaya, Guillaume Pierre   +2 more
openalex   +2 more sources

Practical Resource Usage Prediction Method for Large Memory Jobs in HPC Clusters [PDF]

, 2019
Xiuqiao Li, N. D. Qi, Yuanyuan He, Bill Mcmillan   +3 more
openalex   +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

Encapsulating HPC System Level Complexities via Software Framework

, 2015
Saurav Das
openalex   +2 more sources

Breaking the Durability–Power Trade‐Off: Boron‐Directed Faceted O3 Cathodes for High‐Rate Sodium‐Ion Batteries

Advanced Energy Materials, EarlyView.
Boron‐oxide‐assisted particle engineering stabilizes O3‐type layered cathodes for sodium‐ion batteries by mitigating phase transitions and lattice strain. Acting as flux and structural modifier, boron forms submicron hexagonal platelets with (003) facets and expanded Na‐layer spacing, enabling rapid Na⁺ diffusion and mechanical resilience.
Tengfei Song, Alexis Manche, Dongrui Xie, Bowen Liu, Chenglong Wu, Bo Dong, Reda Malakauskaite, Manoj Ovhal, David O. Scanlon, Emma Kendrick   +9 more
wiley   +1 more source

Towards Cloud-based Asynchronous Elasticity for Iterative HPC Applications [PDF]

, 2015
Rodrigo da Rosa Righi, Vinicius Facco Rodrigues, Cristiano André da Costa, Diego Kreutz, Hans-Ulrich Heiß   +4 more
openalex   +1 more source

Advancing Direct Alcohol Fuel Cells: Innovations in Composite‐Based Electrocatalysts and Polymer Support Materials for Enhanced Efficiency

Advanced Energy and Sustainability Research, EarlyView.
This graphical abstract emphasizes the working principle and the various essential factors of the direct methanol fuel cell (DMFCs). Additionally, various parameters, such as the nanoparticle's size and shape, the nature of the electrolyte, the type of support materials, and their fabrication process, also play essential roles in the functioning of the
Kirti Mishra, Samarjeet Singh Siwal, Phil Hart, Vijay Kumar Thakur   +3 more
wiley   +1 more source

1st Workshop HPC-TRES Book of Abstracts

, 2018
Stefano Salon
openalex   +1 more source