Result Number | Material Type | Add to My Shelf Action | Record Details and Options |
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1 |
Material Type: Dissertação de Mestrado
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Computadores no ensino médio : análise da compreensão de alunos roteiristasBoaretto, RogérioBiblioteca Digital de Teses e Dissertações da USP; Universidade de São Paulo; Ensino de Ciências (Física, Química e Biologia) 2004-06-08Acesso online. A biblioteca também possui exemplares impressos. |
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Material Type: Artigo
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Exergy model of the human heartMady, Carlos Eduardo Keutenedjian, 1984- Universidade Estadual de Campinas (Unicamp); Universidade Estadual De CampinasMADY, Carlos Eduardo Keutenedjian. Exergy model of the human heart. Energy. London : Elsevier, 2016.. Vol. 117 (Dec., 2016), p. 612-619. Disponível em: https://hdl.handle.net/20.500.12733/1653771. Acesso em: 14 jun. 2024.2016Acesso online |
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Material Type: Artigo
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How to represent crystal structures for machine learning: Towards fast prediction of electronic propertiesSchütt, K. T. ; Glawe, H. ; Brockherde, F. ; Sanna, A. ; Müller, K. R. ; Gross, E. K. U.Physical review. B, Condensed matter and materials physics, 2014-05, Vol.89 (20), Article 205118 [Periódico revisado por pares]Texto completo disponível |
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Material Type: Artigo
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Learning scheme to predict atomic forces and accelerate materials simulationsBotu, V. ; Ramprasad, R.Physical review. B, Condensed matter and materials physics, 2015-09, Vol.92 (9), Article 094306 [Periódico revisado por pares]Texto completo disponível |
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Material Type: Artigo
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Accelerated materials property predictions and design using motif-based fingerprintsHuan, Tran Doan ; Mannodi-Kanakkithodi, Arun ; Ramprasad, RampiPhysical review. B, Condensed matter and materials physics, 2015-07, Vol.92 (1), Article 014106 [Periódico revisado por pares]Texto completo disponível |
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Material Type: Artigo
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PDE-Net 2.0: Learning PDEs from data with a numeric-symbolic hybrid deep networkLong, Zichao ; Lu, Yiping ; Dong, BinJournal of computational physics, 2019-12, Vol.399, p.108925, Article 108925 [Periódico revisado por pares]Cambridge: Elsevier IncTexto completo disponível |
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Material Type: Artigo
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Recent Progress in Three‐Terminal Artificial Synapses: From Device to SystemHan, Hong ; Yu, Haiyang ; Wei, Huanhuan ; Gong, Jiangdong ; Xu, WentaoSmall (Weinheim an der Bergstrasse, Germany), 2019-08, Vol.15 (32), p.e1900695-n/a [Periódico revisado por pares]Germany: Wiley Subscription Services, IncTexto completo disponível |
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Material Type: Artigo
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First‐Principles Multiscale Modeling of Mechanical Properties in Graphene/Borophene Heterostructures Empowered by Machine‐Learning Interatomic PotentialsMortazavi, Bohayra ; Silani, Mohammad ; Podryabinkin, Evgeny V. ; Rabczuk, Timon ; Zhuang, Xiaoying ; Shapeev, Alexander V.Advanced materials (Weinheim), 2021-09, Vol.33 (35), p.e2102807-n/a [Periódico revisado por pares]Weinheim: Wiley Subscription Services, IncTexto completo disponível |
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Material Type: Artigo
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A synaptic device based on the optoelectronic properties of ZnO thin film transistorsNobre, José Henrique Ferreira ; Safade, Amer Samir ; Urbano, Alexandre ; Laureto, EdsonApplied physics. A, Materials science & processing, 2023-03, Vol.129 (3), Article 203 [Periódico revisado por pares]Berlin/Heidelberg: Springer Berlin HeidelbergTexto completo disponível |
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Material Type: Artigo
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Photonic Organolead Halide Perovskite Artificial Synapse Capable of Accelerated Learning at Low Power Inspired by Dopamine‐Facilitated Synaptic ActivityHam, Seonggil ; Choi, Sanghyeon ; Cho, Haein ; Na, Seok‐In ; Wang, GunukAdvanced functional materials, 2019-02, Vol.29 (5), p.n/a [Periódico revisado por pares]Hoboken: Wiley Subscription Services, IncTexto completo disponível |