Screening of environmentally friendly quantum-nanocrystals for energy and bioimaging applications by combining experiment and theory with machine learning
| Project/Area Number |
20H02579
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Review Section |
Basic Section 28030:Nanomaterials-related
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| Research Institution | National Institute of Advanced Industrial Science and Technology |
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Principal Investigator |
Buerkle Marius 国立研究開発法人産業技術総合研究所, 材料・化学領域, 主任研究員 (00756661)
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| Co-Investigator(Kenkyū-buntansha) |
Svrcek Vladimir 国立研究開発法人産業技術総合研究所, エネルギー・環境領域, 主任研究員 (80462828)
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| Project Period (FY) |
2020-04-01 – 2025-03-31
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| Project Status |
Granted (Fiscal Year 2021)
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| Budget Amount *help |
¥13,260,000 (Direct Cost: ¥10,200,000、Indirect Cost: ¥3,060,000)
Fiscal Year 2022: ¥2,600,000 (Direct Cost: ¥2,000,000、Indirect Cost: ¥600,000)
Fiscal Year 2021: ¥2,600,000 (Direct Cost: ¥2,000,000、Indirect Cost: ¥600,000)
Fiscal Year 2020: ¥2,860,000 (Direct Cost: ¥2,200,000、Indirect Cost: ¥660,000)
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| Keywords | Nanocrystals / machine learning / AI / DFT / solarcells / nanopartilces / luminasence / Machine learning / Deep learning / Materials informatiocs / bioimaging |
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| Outline of Research at the Start |
Nanocrystals (NC) can be designed to emit and absorb light of a specific wavelength (color) very efficiently, thus the can be used in many applications ( displays, touchscreens, solarcells). Moreover, in our work we focus on environmental friendly and nontoxic materials. Nontoxic NCs provide new means for bioimaging (diagnostics) and drug delivery (treatment).
While NCs have a huge potential, designe and synthesis is very challenging. Therefore our goal is to combine state-of-the-art experiments, computer simulations and machine learning techniques to enhance the development of novel NCs.
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| Outline of Annual Research Achievements |
We research nanoparticles for various applications; next generation solar cells, optical applications, and bioimaging. In this project focus on environmental friendly materials, suchs as silicon, carbon, tin, as well as abundantly available metallic particles such as nickel. We combine theory with experiment. Namely high-throughput first-principles calculations and novel machine learning techniques. These efforts are combined with experiment, synthesizing, characterizing, and for most promising systems device fabrication. In the last fiscal year we established our methodology for both computational efforts as well as experimental studies. We have produced novel carbon-nanodot particles and magnetic nickel nanoparticles. Which are currently studied by means of first-principles calculations.
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| Current Status of Research Progress |
Current Status of Research Progress
2: Research has progressed on the whole more than it was originally planned.
Reason
We established our computational method this FY and provided first results which are in good agreement with our experimental efforts. This essentially concludes the initial phase of the project with aimed to establish and validate our combined theory and experiment approach.
While due to Corona-related restrictions we were not able to exchange research results and provide on-site training and research with our international projects, we were able to provide our international research partners with valuable first-principles results as well as provide characterization of nanoparticles using local facilities.
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| Strategy for Future Research Activity |
After establishing and validating our combined theory and experimental scheme, we are moving now into the "production phase", targeting in the coming fiscal year, carbon-based nanoparticles as well as magnetic nanoparticles. The next step includes (i) extensive first-principle studies of electronic and optical properties, (ii) stability predictions using machine learning, (iii) synthesize of the nanoparticles, and (iv) optical and electronic characterization. Additionally we plan to intensive the collaboration with our international partners in the next fiscal year.
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Report
(1 results)
Research Products
(4 results)
