WeChat Mini Program
Old Version Features

AgGaS2 and Derivatives: Design, Synthesis, and Optical Properties

Nanomaterials (Basel, Switzerland)(2025)

Cited 0|Views5
Abstract
Silver gallium sulfide (AgGaS2) is a ternary A(I)B(III)X(VI)2-type semiconductor featuring a direct bandgap and high chemical stability. Structurally resembling diamond, AgGaS2 has gained considerable attention as a highly promising material for nonlinear optical applications such as second harmonic generation and optical parametric oscillation. In attempts to expand the research scope, on the one hand, AgGaS2-derived bulk materials with similar diamond-like configurations have been investigated for the enhancement of nonlinear optics performance, especially the improvement of laser-induced damage thresholds and/or nonlinear coefficients; on the other hand, nanoscale AgGaS2 and its derivatives have been synthesized with sizes as low as the exciton Bohr radius for the realization of potential applications in the fields of optoelectronics and lighting. This review article focuses on recent advancements and future opportunities in the design of both bulk and nanocrystalline AgGaS2 and its derivatives, covering structural, electronic, and chemical aspects. By delving into the properties of AgGaS2 in bulk and nanocrystalline states, this review aims to deepen the understanding of chalcopyrite materials and maximize their utilization in photon conversion and beyond.
More
Translated text
Key words
AgGaS,chalcopyrite,nanocrystals,nonlinear optics,optoelectronics
求助PDF
上传PDF
Bibtex
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
  • Pretraining has recently greatly promoted the development of natural language processing (NLP)
  • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
  • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
  • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
  • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined