2D material property characterizations by machine-learning-assisted microscopies (Record no. 54705)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 02109nam a2200253Ia 4500 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | MX-MdCICY |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20250625162452.0 |
| 040 ## - CATALOGING SOURCE | |
| Transcribing agency | CICY |
| 090 ## - LOCALLY ASSIGNED LC-TYPE CALL NUMBER (OCLC); LOCAL CALL NUMBER (RLIN) | |
| Classification number (OCLC) (R) ; Classification number, CALL (RLIN) (NR) | B-20619 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 250602s9999 xx |||||s2 |||| ||und|d |
| 245 10 - TITLE STATEMENT | |
| Title | 2D material property characterizations by machine-learning-assisted microscopies |
| 490 0# - SERIES STATEMENT | |
| Volume/sequential designation | Applied Physics A, 129(4), p.248, 2023 |
| 520 3# - SUMMARY, ETC. | |
| Summary, etc. | Microscopy characterization techniques can provide intuitive images of 2D materials with certain spatial resolutions. At the same time, machine-learning algorithms, which have experienced tremendous advancement in image processing over passed decades, are able to extract comprehensive information directly from a large scale of the images. Combining microscopy characterization techniques with machine-learning algorithms can offer insight into the structures and properties of 2D materials with the advantages of high automation, high accuracy, and high throughput. Herein, we will give a review of this interdisciplinary area, from foundations and progress to challenges and potential opportunities. The developments in this field are first overviewed according to its characterization techniques. Then, this review focuses on the theoretical and practical foundations of machine-learning-assisted microscopies for 2D material property characterizations, followed by two case studies to illustrate the implementation details. Finally, challenges and opportunities are addressed for future research and industrialized applications. We hope this review article can provide a clear guideline for both the academic society and general readers and inspire researchers for further explorations of this promising area. |
| 650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | 2D MATERIALS |
| 650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | MICROSCOPY |
| 650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | PROPERTY CHARACTERIZATION |
| 650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | MACHINE LEARNING |
| 700 12 - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Si, Z. |
| 700 12 - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Zhou, D. |
| 700 12 - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Yang, J. |
| 700 12 - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Lin, X. |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | <a href="https://drive.google.com/file/d/1vn-WAaFNuSv3exFOJIKAD_sGLPky4kOg/view?usp=drivesdk">https://drive.google.com/file/d/1vn-WAaFNuSv3exFOJIKAD_sGLPky4kOg/view?usp=drivesdk</a> |
| Public note | Para ver el documento ingresa a Google con tu cuenta: @cicy.edu.mx |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Source of classification or shelving scheme | Clasificación local |
| Koha item type | Documentos solicitados |
| Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Collection | Home library | Current library | Shelving location | Date acquired | Total checkouts | Full call number | Date last seen | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Clasificación local | Ref1 | CICY | CICY | Documento préstamo interbibliotecario | 25.06.2025 | B-20619 | 25.06.2025 | 25.06.2025 | Documentos solicitados |