Application of Materials Informatics Tools to the Analysis of Combinatorial Libraries of All Metal-Oxides Photovoltaic Cells

Hanoch Senderowitz; Abraham Yosipof; Omer Kaspi

doi:https://doi.org/10.1007/978-3-030-30493-5_70

Application of Materials Informatics Tools to the Analysis of Combinatorial Libraries of All Metal-Oxides Photovoltaic Cells

Hanoch Senderowitz, Abraham Yosipof, Omer Kaspi

Department of Chemistry

Bar-Ilan University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Material informatics is engaged with the application of informatics tools, frequently in the form of machine learning algorithms, to gain insight into structure properties relationships of materials and to design new materials with desired properties. Here we describe the application of such algorithms to the analysis of solar cell (i.e., photovoltaic; PV) libraries made entirely from metal oxides (MOs). MOs-based solar cells hold the potential to provide clean and affordable energy if their power conversion efficiencies are improved. We demonstrate the power of dimensionality reduction methods to visualize the MOs-based solar cell space and the power of several algorithms to develop predictive models for key PV properties. We stress the importance of conducting such studies in collaboration with experimentalists.

Original language	English
Title of host publication	Artificial Neural Networks and Machine Learning – ICANN 2019
Subtitle of host publication	Workshop and Special Sessions - 28th International Conference on Artificial Neural Networks, Proceedings
Editors	Vera Kurková, Igor V. Tetko, Pavel Karpov, Fabian Theis
Publisher	Springer Verlag
Pages	758-763
Number of pages	6
ISBN (Print)	9783030304928
DOIs	https://doi.org/10.1007/978-3-030-30493-5_70
State	Published - 2019
Event	28th International Conference on Artificial Neural Networks, ICANN 2019 - Munich, Germany Duration: 17 Sep 2019 → 19 Sep 2019

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11731 LNCS

Conference

Conference	28th International Conference on Artificial Neural Networks, ICANN 2019
Country/Territory	Germany
City	Munich
Period	17/09/19 → 19/09/19

Keywords

Dimensionality reduction
Genetic programming
Materials informatics
QSAR
RANSAC
Solar cells
kNN

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
General Computer Science

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

https://doi.org/10.1007/978-3-030-30493-5_70

Cite this

Senderowitz, H., Yosipof, A., & Kaspi, O. (2019). Application of Materials Informatics Tools to the Analysis of Combinatorial Libraries of All Metal-Oxides Photovoltaic Cells. In V. Kurková, I. V. Tetko, P. Karpov, & F. Theis (Eds.), Artificial Neural Networks and Machine Learning – ICANN 2019: Workshop and Special Sessions - 28th International Conference on Artificial Neural Networks, Proceedings (pp. 758-763). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11731 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-030-30493-5_70

Senderowitz, Hanoch ; Yosipof, Abraham ; Kaspi, Omer. / Application of Materials Informatics Tools to the Analysis of Combinatorial Libraries of All Metal-Oxides Photovoltaic Cells. Artificial Neural Networks and Machine Learning – ICANN 2019: Workshop and Special Sessions - 28th International Conference on Artificial Neural Networks, Proceedings. editor / Vera Kurková ; Igor V. Tetko ; Pavel Karpov ; Fabian Theis. Springer Verlag, 2019. pp. 758-763 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "Material informatics is engaged with the application of informatics tools, frequently in the form of machine learning algorithms, to gain insight into structure properties relationships of materials and to design new materials with desired properties. Here we describe the application of such algorithms to the analysis of solar cell (i.e., photovoltaic; PV) libraries made entirely from metal oxides (MOs). MOs-based solar cells hold the potential to provide clean and affordable energy if their power conversion efficiencies are improved. We demonstrate the power of dimensionality reduction methods to visualize the MOs-based solar cell space and the power of several algorithms to develop predictive models for key PV properties. We stress the importance of conducting such studies in collaboration with experimentalists.",

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author = "Hanoch Senderowitz and Abraham Yosipof and Omer Kaspi",

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Senderowitz, H, Yosipof, A & Kaspi, O 2019, Application of Materials Informatics Tools to the Analysis of Combinatorial Libraries of All Metal-Oxides Photovoltaic Cells. in V Kurková, IV Tetko, P Karpov & F Theis (eds), Artificial Neural Networks and Machine Learning – ICANN 2019: Workshop and Special Sessions - 28th International Conference on Artificial Neural Networks, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11731 LNCS, Springer Verlag, pp. 758-763, 28th International Conference on Artificial Neural Networks, ICANN 2019, Munich, Germany, 17/09/19. https://doi.org/10.1007/978-3-030-30493-5_70

Application of Materials Informatics Tools to the Analysis of Combinatorial Libraries of All Metal-Oxides Photovoltaic Cells. / Senderowitz, Hanoch; Yosipof, Abraham; Kaspi, Omer.
Artificial Neural Networks and Machine Learning – ICANN 2019: Workshop and Special Sessions - 28th International Conference on Artificial Neural Networks, Proceedings. ed. / Vera Kurková; Igor V. Tetko; Pavel Karpov; Fabian Theis. Springer Verlag, 2019. p. 758-763 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11731 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Application of Materials Informatics Tools to the Analysis of Combinatorial Libraries of All Metal-Oxides Photovoltaic Cells

AU - Senderowitz, Hanoch

AU - Yosipof, Abraham

AU - Kaspi, Omer

N1 - Publisher Copyright: © The Author(s) 2019.

PY - 2019

Y1 - 2019

N2 - Material informatics is engaged with the application of informatics tools, frequently in the form of machine learning algorithms, to gain insight into structure properties relationships of materials and to design new materials with desired properties. Here we describe the application of such algorithms to the analysis of solar cell (i.e., photovoltaic; PV) libraries made entirely from metal oxides (MOs). MOs-based solar cells hold the potential to provide clean and affordable energy if their power conversion efficiencies are improved. We demonstrate the power of dimensionality reduction methods to visualize the MOs-based solar cell space and the power of several algorithms to develop predictive models for key PV properties. We stress the importance of conducting such studies in collaboration with experimentalists.

AB - Material informatics is engaged with the application of informatics tools, frequently in the form of machine learning algorithms, to gain insight into structure properties relationships of materials and to design new materials with desired properties. Here we describe the application of such algorithms to the analysis of solar cell (i.e., photovoltaic; PV) libraries made entirely from metal oxides (MOs). MOs-based solar cells hold the potential to provide clean and affordable energy if their power conversion efficiencies are improved. We demonstrate the power of dimensionality reduction methods to visualize the MOs-based solar cell space and the power of several algorithms to develop predictive models for key PV properties. We stress the importance of conducting such studies in collaboration with experimentalists.

KW - Dimensionality reduction

KW - Genetic programming

KW - Materials informatics

KW - QSAR

KW - RANSAC

KW - Solar cells

KW - kNN

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U2 - https://doi.org/10.1007/978-3-030-30493-5_70

DO - https://doi.org/10.1007/978-3-030-30493-5_70

M3 - منشور من مؤتمر

SN - 9783030304928

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 758

EP - 763

BT - Artificial Neural Networks and Machine Learning – ICANN 2019

A2 - Kurková, Vera

A2 - Tetko, Igor V.

A2 - Karpov, Pavel

A2 - Theis, Fabian

PB - Springer Verlag

T2 - 28th International Conference on Artificial Neural Networks, ICANN 2019

Y2 - 17 September 2019 through 19 September 2019

ER -

Senderowitz H, Yosipof A, Kaspi O. Application of Materials Informatics Tools to the Analysis of Combinatorial Libraries of All Metal-Oxides Photovoltaic Cells. In Kurková V, Tetko IV, Karpov P, Theis F, editors, Artificial Neural Networks and Machine Learning – ICANN 2019: Workshop and Special Sessions - 28th International Conference on Artificial Neural Networks, Proceedings. Springer Verlag. 2019. p. 758-763. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: https://doi.org/10.1007/978-3-030-30493-5_70

Application of Materials Informatics Tools to the Analysis of Combinatorial Libraries of All Metal-Oxides Photovoltaic Cells

Abstract

Publication series

Conference

Keywords

All Science Journal Classification (ASJC) codes

UN SDGs

Access to Document

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