Synthesizability indexing of machine learning algorithm suggested novel compounds
The creation of new materials is a critical aspect of scientific research and development, as it plays a significant role in improving the quality of life for people all over the world. From advanced medical technologies to the development of sustainable energy sources, new materials have a va...
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sg-ntu-dr.10356-1669282023-05-20T16:46:11Z Synthesizability indexing of machine learning algorithm suggested novel compounds Koh, Joel Bo Jun Kedar Hippalgaonkar School of Materials Science and Engineering kedar@ntu.edu.sg Engineering::Materials The creation of new materials is a critical aspect of scientific research and development, as it plays a significant role in improving the quality of life for people all over the world. From advanced medical technologies to the development of sustainable energy sources, new materials have a vast range of applications that have the potential to revolutionize multiple industries. New materials are essential for technological advancements, as they are often designed to be stronger, more durable, and more versatile than existing materials. For example, carbon fiber composites have replaced metal alloys in the construction of high-performance sports cars and aerospace components, resulting in lighter and more fuel-efficient vehicles [1]. Similarly, the development of new materials such as perovskite solar cells has led to significant improvements in solar panel efficiency, making renewable energy more cost-effective and accessible. Furthermore, the creation of new materials can also address specific challenges facing society, such as climate change and disease prevention. For example, researchers are currently developing nanomaterials that can selectively remove carbon dioxide from the atmosphere, potentially mitigating the effects of global warming [2]. In the field of medicine, researchers are exploring the use of biomaterials to develop advanced drug delivery systems that can more effectively target specific diseases and reduce the risk of side effects [3]. While significant progress has been made in the development of new materials, there is a need for continuous innovation to address emerging challenges and improve existing technologies. As technologies evolve and become more complex, the materials used to create them must also become more advanced to meet the demands of these new applications. For example, the emergence of electric vehicles has created a need for new materials with high energy storage capacities to develop better and more efficient batteries (Zhang et al., 2020). 3 Furthermore, materials science is a rapidly evolving field, with new discoveries and advancements being made all the time. Continuously creating new materials allows researchers to explore new possibilities and overcome limitations that may have previously hindered progress. Additionally, advancements in materials science can often have significant economic benefits, as new materials can open up new markets and create new job opportunities [4]. The purpose of this report is to document the research, development, and evaluation of a machine learning-based synthesizability indexing system for 3-element compounds. The project aims to explore the correlation between the physical and chemical properties of the constituent elements in 3-element compounds and their ability to be synthesized. The report will discuss the use of machine learning techniques and formulas to create a model that accurately predicts the synthesizability of 3-element compounds based on the properties of the constituent elements Bachelor of Engineering (Materials Engineering) 2023-05-18T12:42:19Z 2023-05-18T12:42:19Z 2023 Final Year Project (FYP) Koh, J. B. J. (2023). Synthesizability indexing of machine learning algorithm suggested novel compounds. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/166928 https://hdl.handle.net/10356/166928 en application/pdf Nanyang Technological University |
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Engineering::Materials Koh, Joel Bo Jun Synthesizability indexing of machine learning algorithm suggested novel compounds |
description |
The creation of new materials is a critical aspect of scientific research and development, as it
plays a significant role in improving the quality of life for people all over the world. From
advanced medical technologies to the development of sustainable energy sources, new
materials have a vast range of applications that have the potential to revolutionize multiple
industries.
New materials are essential for technological advancements, as they are often designed to be
stronger, more durable, and more versatile than existing materials. For example, carbon fiber
composites have replaced metal alloys in the construction of high-performance sports cars
and aerospace components, resulting in lighter and more fuel-efficient vehicles [1]. Similarly,
the development of new materials such as perovskite solar cells has led to significant
improvements in solar panel efficiency, making renewable energy more cost-effective and
accessible.
Furthermore, the creation of new materials can also address specific challenges facing
society, such as climate change and disease prevention. For example, researchers are
currently developing nanomaterials that can selectively remove carbon dioxide from the
atmosphere, potentially mitigating the effects of global warming [2]. In the field of medicine,
researchers are exploring the use of biomaterials to develop advanced drug delivery systems
that can more effectively target specific diseases and reduce the risk of side effects [3].
While significant progress has been made in the development of new materials, there is a
need for continuous innovation to address emerging challenges and improve existing
technologies. As technologies evolve and become more complex, the materials used to create
them must also become more advanced to meet the demands of these new applications. For
example, the emergence of electric vehicles has created a need for new materials with high
energy storage capacities to develop better and more efficient batteries (Zhang et al., 2020).
3
Furthermore, materials science is a rapidly evolving field, with new discoveries and
advancements being made all the time. Continuously creating new materials allows
researchers to explore new possibilities and overcome limitations that may have previously
hindered progress. Additionally, advancements in materials science can often have significant
economic benefits, as new materials can open up new markets and create new job
opportunities [4].
The purpose of this report is to document the research, development, and evaluation of a
machine learning-based synthesizability indexing system for 3-element compounds. The
project aims to explore the correlation between the physical and chemical properties of the
constituent elements in 3-element compounds and their ability to be synthesized. The report
will discuss the use of machine learning techniques and formulas to create a model that
accurately predicts the synthesizability of 3-element compounds based on the properties of
the constituent elements |
author2 |
Kedar Hippalgaonkar |
author_facet |
Kedar Hippalgaonkar Koh, Joel Bo Jun |
format |
Final Year Project |
author |
Koh, Joel Bo Jun |
author_sort |
Koh, Joel Bo Jun |
title |
Synthesizability indexing of machine learning algorithm suggested novel compounds |
title_short |
Synthesizability indexing of machine learning algorithm suggested novel compounds |
title_full |
Synthesizability indexing of machine learning algorithm suggested novel compounds |
title_fullStr |
Synthesizability indexing of machine learning algorithm suggested novel compounds |
title_full_unstemmed |
Synthesizability indexing of machine learning algorithm suggested novel compounds |
title_sort |
synthesizability indexing of machine learning algorithm suggested novel compounds |
publisher |
Nanyang Technological University |
publishDate |
2023 |
url |
https://hdl.handle.net/10356/166928 |
_version_ |
1772827422252597248 |