Innovations in spectroscopy and microscopy have long been the major driving force behind numerous major scientific discoveries. Recent advancements in laser technologies, detectors, automation, 3D printing, big data and artificial intelligence, have led to new waves of innovations in chemical imaging for mapping of chemical composition in space and time. We have witnessed new experiments that reveal a mechanistic description of chemical processes that exhibit both dynamic and static heterogeneity, thereby addressing a major challenge in fundamental chemistry and materials engineering. The volume of data potentially accessible in hyperspectral chemical imaging provides both challenges and opportunities for compositional and functional analysis. This special issue is in resonance with the inaugural Gordon Research Conference (GRC) on Chemical Imaging, which was originally planned for 2021 but has been postponed to 2023 (Chemical Imaging Conference GRC).
In this Special Issue, we wish to highlight the rapid experimental and theoretical advances of this burgeoning interdisciplinary field at the crossroads of chemistry, physics, materials, and biology, as well as to provide an account of its peculiar challenges and future prospects.
Topics covered include, but are not limited to:
- Coherent anti-Stokes Raman spectroscopy (CARS) and stimulated Raman Scattering (SRS) microscopy
- Pump-probe microscopy
- Photothermal microscopy
- 2D IR spectroscopy and microscopy
- Near-field scanning optical microscopy
- Mapping catalytic reactions on single nanocatalysts
- Imaging single molecular dynamics in chromatographic and electrophoretic separation systems
- Electrochemical imaging: imaging single entity catalysis; biological interfaces; fundamental studies of electron transfer at surfaces
- Mass spectroscopic imaging
- Big Data/AI for Chemical Imaging
Ning Fang, Georgia State University
Bert Weckhuysen, Utrecht University
Ji-Xin Cheng, Boston University
Amber Krummel, Colorado State University
Katsumasa Fujita, Osaka University
Jennifer Ogilvie, University of Michigan
Emily A. Weiss, Northwestern University
Tim Lian, Emory University
Please note that papers will be published as normal when they are ready in a regular issue of the journal and will populate on a virtual collection page within a few days of publication. Inclusion in the collection will not cause delay in publication.