Abstract
Based on historical developments and the current state of the art in gas-phase transmission electron microscopy (GP-TEM), we provide a perspective covering exciting new technologies and methodologies of relevance for chemical and surface sciences. Considering thermal and photochemical reaction environments, we emphasize the benefit of implementing gas cells, quantitative TEM approaches using sensitive detection for structured electron illumination (in space and time) and data denoising, optical excitation, and data mining using autonomous machine learning techniques. These emerging advances open new ways to accelerate discoveries in chemical and surface sciences. Graphical abstract: (Figure presented.)
Original language | English |
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Pages (from-to) | 174-183 |
Number of pages | 10 |
Journal | MRS Bulletin |
Volume | 49 |
Issue number | 2 |
DOIs | |
State | Published - Feb 2024 |
Funding
J.R.J. acknowledges support from DTU Nanolab (starting grant) and from the Novo Nordisk Foundation (Grant No. 110114). S.H. acknowledges support from the Danish National Research Foundation (Grant No. DNRF146). L.F.A. acknowledges support by the US Department of Energy, Office of Energy Efficiency and Renewable Energy, Vehicle Technologies Office, Propulsion Materials Program. J.A.D. acknowledges support from the DOE Office of Science (Grant No. DE-SC0021984). Y.Z. acknowledges support from US NSF Grant No. CBET 2238213. P.A.C. acknowledges support from US NSF Grant Nos. OAC 1940263, 2104105, CBET 1604971, and DMR 184084.
Keywords
- Beam effects
- Catalysis
- Data analysis
- Denoising
- Electron energy-loss spectroscopy (EELS)
- Environmental transmission electron microscopy (ETEM)
- Gas phase
- In situ
- Low dose
- Machine learning
- Nanoreactor
- Operando
- Surface
- Transmission electron microscopy (TEM)