Advances in Low-Dimensional Materials: Synthesis, Characterization and Device Application, 2nd Edition

A special issue of Micromachines (ISSN 2072-666X). This special issue belongs to the section "D:Materials and Processing".

Deadline for manuscript submissions: closed (30 September 2025) | Viewed by 770

Special Issue Editors


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Guest Editor
Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
Interests: 2D materials; chemical vapor deposition; optical spectroscopy
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Guest Editor
School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
Interests: synthesis; nanomaterials; 2D materials; physics; surface characterization
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In recent decades, the rapid development of nanotechnology has enabled the innovative design and precise control of thin film synthesis, characterization, and device applications. As a result, researchers have discovered and studied a number of novel material systems that possess fundamentally new structures and physical properties. In particular, low-dimensional materials exhibit unique properties due to quantum confinement and large surface area. These classes of materials include quantum dots, nanowires, nanotubes, and recently emerging two-dimensional (2D) materials such as graphene, transition metal dichalcogenides, boron nitride, MXenes, and perovskite semiconductors. A plethora of electronic properties and quasiparticles in 2D materials, including plasmons, polaritons, trions, and excitons, can all be controlled and modulated. In addition, these materials exhibit novel physical properties such as spin and valley polarization, magnetism, superconductivity, and piezoelectricity that depend on composition, crystal structure, twist angle, layer number, and phases. These features have further given rise to many device applications.

Therefore, this Special Issue seeks to showcase research papers, communications, and review articles that focus on (1) discussions on the synthesis of low-dimensional materials for emerging physics and functional device fabrication; (2) characterization approaches for defining low-dimensional materials on an atomic scale and probing their novel structure and physical properties; and (3) device applications of low-dimensional materials in field-effect transistors, sensors, photodetectors, nonvolatile memories, energy conversion, and beyond.

Building on the success of the first volume, which received a positive response and significant contributions, we are excited to open the second volume of this Special Issue. This volume will continue to focus on the latest advancements in the synthesis, characterization, and device applications of low-dimensional materials.

We warmly invite researchers and scholars from all fields to submit their work, including original research papers, communications, and review articles, to contribute to this exciting and rapidly evolving area of research.

Dr. Tianyi Zhang
Dr. Xiaotian Zhang
Guest Editors

Manuscript Submission Information

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Keywords

  • low-dimensional materials: quantum dots, nanowires, nanotubes, 2D materials, graphene, transition metal dichalcogenides, boron nitride, MXenes, perovskite
  • physical and structural characterization: atomic-scale characterization, electron microscopy, spectroscopy, X-ray diffraction, raman spectroscopy, scanning tunneling microscopy (STM), atomic force microscopy (AFM)
  • device applications: field-effect transistors (FETs), sensors, memristors, nonvolatile memories, energy conversion devices, flexible electronics, optoelectronics, photodetectors, energy storage

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Published Papers (1 paper)

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Research

11 pages, 6412 KB  
Article
High-Throughput Evaluation of Mechanical Exfoliation Using Optical Classification of Two-Dimensional Materials
by Anthony Gasbarro, Yong-Sung D. Masuda and Victor M. Lubecke
Micromachines 2025, 16(10), 1084; https://doi.org/10.3390/mi16101084 - 25 Sep 2025
Viewed by 395
Abstract
Mechanical exfoliation remains the most common method for producing high-quality two-dimensional (2D) materials, but its inherently low yield requires screening large numbers of samples to identify usable flakes. Efficient optimization of the exfoliation process demands scalable methods to analyze deposited material across extensive [...] Read more.
Mechanical exfoliation remains the most common method for producing high-quality two-dimensional (2D) materials, but its inherently low yield requires screening large numbers of samples to identify usable flakes. Efficient optimization of the exfoliation process demands scalable methods to analyze deposited material across extensive datasets. While machine learning clustering techniques have demonstrated ~95% accuracy in classifying 2D material thicknesses from optical microscopy images, current tools are limited by slow processing speeds and heavy reliance on manual user input. This work presents an open-source, GPU-accelerated software platform that builds upon existing classification methods to enable high-throughput analysis of 2D material samples. By leveraging parallel computation, optimizing core algorithms, and automating preprocessing steps, the software can quantify flake coverage and thickness across uncompressed optical images at scale. Benchmark comparisons show that this implementation processes over 200× more pixel data with a 60× reduction in processing time relative to the original software. Specifically, a full dataset of2916 uncompressed images can be classified in 35 min, compared to an estimated 32 h required by the baseline method using compressed images. This platform enables rapid evaluation of exfoliation results across multiple trials, providing a practical tool for optimizing deposition techniques and improving the yield of high-quality 2D materials. Full article
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