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������������������������������������������������������������������������������ ��� ���������������������National Institute for Materials Science, NIMS��������������������������������������������������������������������� 2017 ������������������2020������������������������ DICE ������������������������������������������������������������������������������������������������������������������������������������������DICE2.0���������������������������������������������������������������������������������������������MatVoc������������������������������������������������������������������������������������������������������������������������

To promote data-driven research in the materials science field, the National Institute for Materials Science has been developing a materials data platform system since 2017, and started operating it as "DICE" in 2020. In this presentation, we will describe its functionalities, some of the developments so far, and potential avenues for future cooperation and collaboration.

NIMSでは材料データリポジトリ (MDR) を2020年より運用し、研究データセットの登録・公開を推進している。各データセットが有効に利活用・引用されるように検討しながら登録方法やメタデータを定め、DataCite DOIを付与している。ある研究コミュニティによる1700件以上のデータセット登録・DOI付与事例の紹介も交え、運用の現状と課題について報告する。

データ駆動型研究の進展に伴い，効率的かつ実用的なデータ収集の仕組みが求められている．物質・材料研究機構では，主に計測・プロセスデータを対象としたデータ収集システムを構築し運用を行っている．本システムでは非ネットワーク環境に置かれている実験装置の制御 PC 等に対して通信セキュリティを施したデバイスを装着させて，制御 PC を IoT 化させている．この PC からアップロードされたファイルは，XML スキーマに基づいて計測パラメータのメタデータが抽出され，データサーバで自動的にデータベース化される．本稿では主に材料科学分野での IoT 技術を活用したデータ集積の設計指針（データアーキテクチャー）について論じる．, With the development of data-driven research, an efficient and practical data collection system is required. National Institute for Materials Science (NIMS) has been constructing and operating a data collection system mainly for measurement and process data. In this system, even if a control PC of a laboratory equipment are placed in a non-network environment, the PC is able to converted to IoT by attaching with a communication security device. The files uploaded from the PC are automatically converted into a database via extracting the metadata of the measurement arameters based on the XML schema. This paper discusses the “data architecture” and data collecting system mainly used in the field of materials science by applying the IoT technology., 情報処理学会論文誌デジタルプラクティス, Vol.2 No.2, p.80–89, (Apr. 2021)

材料研究は物理学・化学・工学に基づいた応用寄りの学問であり、研究者のディスカバリーサービスに対する期待もその特徴を反映する。材料データは産業的応用との兼ね合いや知的財産的な事情により制限公開・制限共有であることが多く、データの即時入手ができなくてもその存在は発見でき次のステップに進めるようなワンストップのサービスが理想像である。また最近はデータ駆動型のアプローチが広まっており、このとき材料学特有のメタデータの取り扱いが課題になる。NIMSが材料データプラットフォームDICEを構築する際に共通メタデータをデザインしたが、研究者の興味対象になるメタデータほど標準化・共通化が難しいことがわかった。共通スキーマに含めきれないメタデータを収める方策は、Schema.orgを拡張したフォーマットによるファイル管理を含め検討が続いており、学際的なつながりを志向する機関・サービスと各専門家・専門機関との連携が重要になる。

Metadata for a research dataset can be about the dataset's bibliographic properties as well as their scientific properties. The scientific metadata are bound to be domain-specific. In materials science, it may describe what measurements were performed on which specimen using which instrument in what kind of environment. We defined an original schema to describe these, along with other methods which are covered later. Materials science is a syncretic field of study, and creating a widely-accepted standard to describe the materials-science metadata is challenging. Our JSON Schema is designed primarily for messaging and data relaying among the systems in our materials data platform (data collection, management, repository, etc.). It features a hierarchical structure to describe several different types of resources (instruments, specimen, processes, properties, and computation) or combinations thereof. It is partially inspired by the Materials Data Vocabulary, which was one of the outputs of the RDA International Materials Resource Registries WG. We have been developing the platform systems to generate/interpret this format. However, the complexity of the hierarchical structure has caused difficulties in implementing the model to some systems. Also, user feedback indicated that for some researchers, the complex form mirroring the structure of the schema could feel burdensome. We also found out that datasets may contain multiple parts where different metadata apply, which cannot be accurately described as long as only one metadata is attached per dataset. The second method is the directory-based metadata collection. In cases where the structure of the metadata can be stably defined beforehand, we can design a system where the researchers are requested to save their data in a pre-defined file hierarchy, which can then be interpreted by another system. A simplified version of this idea was tried out as part of a semi-automated data collection system in our institute and has received generally positive feedback from researchers. We are expanding the same principle to one of our closed repositories, currently in development under the codename "MDR-X" (Materials Data Repository-X), which will deal with even greater variety of materials data. This approach has the benefits of being easy to operate for the researchers and that it can be used in an environment with limited network connectivity, a common situation in materials laboratories. Relative lack of flexibility could be a weak point of this approach. Meanwhile, it is becoming increasingly popular to describe metadata using files in a data package, typically using JSON or other lightweight formats. In particular, RO-Crate is a data packaging approach based on Schema.org, where metadata is written in JSON-LD. (Schema.org focuses on structured data for web resources, but RO-Crate has extended the use cases for more general-purpose metadata description.) We anticipate that this approach can potentially provide a solution to the problem where parts of the datasets require different metadata. The life sciences community has been actively developing Bioschemas as an extension to Schema.org. For materials science, NIST has recently published a pre-alpha version of Material Schema on their website. We believe RDA is a great place to concert these kinds of domain-specific schema developments. This poster aims to share the issues we have encountered in implementing materials metadata and promote discussion on scientific metadata efforts.

We are developing a new data repository to support data-driven developments in materials science, and it became necessary to build an open vocabulary set to describe metadata such as chemical substances, characterization methods, instruments, units, etc. There have been efforts to build a standard vocabulary or an ontology for materials science, but what should be considered as the essential concepts and how to structure them can be quite domain-specific, varying from one researcher to another, as materials science is an interdisciplinary field that encompasses chemistry, physics, and biology. To address this, we are developing a wiki-powered vocabulary management service, not only to apply aforementioned earlier efforts, but also to allow building on top of them by 'crowd-sourcing' among the researchers, thereby realizing appropriate metadata description for a highly-usable materials data repository.

This presentation will report on the development of a cutting-edge "Next Generation Data Repository" (NGDR), which is currently being developed by Antleaf and Cottage Labs for the National Institute of Materials Science (Japan), and which is scheduled to be launched at the end of March 2019. The NGDR has been developed to adopt several of the "behaviours" defined by COAR's Next Generation Repositories Working Group and, as such, implements technologies such as ResourceSync. We will also focus on the complex metadata requirements for a data repository in the domain of materials science, and will describe the approaches to managing and exploiting sophisticated metadata from a variety of sources including automated generation from laboratory equipment, crowd-sourced vocabularies, and standard SKOS-based controlled vocabularies. Finally, the challenge of integrating the repository with a number of other systems in the research 'pipeline' will be described.

プラズマプロセス中に形成される物理的Si基板ダメージを電流電圧特性及び電気容量特性により評価した. 大気暴露による表面酸化層/ダメージ層/Si基板の擬似的Mos構造における電気容量特性変動に基づいた欠陥密度定量化手法を提案する. 本手法を用いて, Arプラズマ処理によるSi基板中の欠陥密度とプラズマ処理条件との関係, 及びAr系へのO_2添加の影響について考察した結果を報告する. またArプラズマとHeプラズマとのダメージ層構造の違いについても議論する. 本解析手法はプラズマプロセス開発におけるダメージ評価手法として有効であると考えられる., We present analysis techniques for plasma process-induced damage in the Si substrate. The techniques are based on the electrical characterizations (current-voltage and capacitance-voltage measurements) of damaged structure - the surface-/interfacial-damaged layer/Si substrate. Using the techniques, the defect density created in the Si substrate was estimated for various plasma conditions with Ar gas in an inductively coupled plasma reactor. The effect of O_2 addition into Ar-plasma was also discussed. In addition, the damage creation mechanism by He-plasma and that by Ar-plasma was compared. The presented electrical characterization techniques were useful for the low-damage plasma process design., 本文データは学協会の許諾に基づきCiNiiから複製したものである

プロセスプラズマからのイオン衝撃による物理的プラズマダメージが, デバイス特性に及ぼす影響について詳細に考察した.イオンの入射エネルギー(E_), シリコン基板表面に形成されるダメージ層構造, ダメージ層除去に伴うシリコンロス, シリコンロスに伴うデバイス特性変動(ΔV_), の定量的相関を示すプラズマダメージモデルを報告する.さらに, 本モデルに基づいたデバイス特性バラツキを予測するためのモデルを示すとともに, 典型的な例に対しての計算結果を議論する.プラズマダメージによるデバイス特性バラツキは, 将来のデバイス設計では無視できない要素になると予測される., We investigated the effects of plasma process-induced physical damage (bombardment of ions) on MOSFET performance degradation. We focus on "Si recess" in the source/drain extension region-Si loss by a subsequent wet-etch of the damaged-layer formed during plasma etch processes. We present a model describing the relationship between the energy of incident ion, Si recess depth d_R, and the threshold voltage shift ΔV_ of MOSFET. Based on the analytic model, we then propose a unified framework for predicting the MOSFET parameter fluctuation induced by the plasma process damage. The model prediction suggests an increase in ΔV_-variation by Si recess structure (d_R). We also estimate an enhancement of the subthreshold leakage-current fluctuation by the Si recess structure., 本文データは学協会の許諾に基づきCiNiiから複製したものである

We present analysis techniques for plasma process-induced damage in the Si substrate. The techniques are based on the electrical characterizations (current-voltage and capacitance-voltage measurements) of damaged structure - the surface-/interfacial-damaged layer/Si substrate. Using the techniques, the defect density created in the Si substrate was estimated for various plasma conditions with Ar gas in an inductively coupled plasma reactor. The effect of O_2 addition into Ar-plasma was also discussed. In addition, the damage creation mechanism by He-plasma and that by Ar-plasma was compared. The presented electrical characterization techniques were useful for the low-damage plasma process design.

Silicon substrate damage caused by HBr/O2 plasma exposure was investigated by spectroscopic ellipsometry (SE), high-resolution Rutherford backscattering spectroscopy, and transmission electron microscopy. The damage caused by H2, Ar, and O2 plasma exposure was also compared to clarify the ion-species dependence. Although the damage basically consists of a surface oxidized layer and underlying dislocated Si, the damage structure strongly depends on the incident ion species, ion energy, and oxidation during air and plasma exposure. In the case of HBr/O2 plasma exposure, hydrogen generated the deep damaged layer (～10 nm), whereas ion-enhanced diffusion of oxygen, supplied simultaneously by the plasma, caused the thick surface oxidation. In-line monitoring of damage thicknesses by SE, developed with an optimized optical model, showed that the SE can be used to precisely monitor damage thicknesses in mass production. Capacitance-voltage (C-V) characteristics of a damaged layer were studied before and after diluted-HF (DHF) treatment. Results showed that a positive charge is generated at the surface oxide-dislocated Si interface and/or in the bulk oxide after plasma exposure. After DHF treatment, most of the positive charges were removed, while the thickness of the “Si recess” was increased by removing the thick surface oxidized layer. As both the Si recess and remaining dislocated Si, including positive charges, cause the degradation of electrical performance, precise monitoring of the surface structure and understanding its effect on device performance is indispensable for creating advanced devices.