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Subsurface chemical nanoidentification by nano-FTIR spectroscopy.

ABSTRACT: Nano-FTIR spectroscopy based on Fourier transform infrared near-field spectroscopy allows for label-free chemical nanocharacterization of organic and inorganic composite surfaces. The potential capability for subsurface material analysis, however, is largely unexplored terrain. Here, we demonstrate nano-FTIR spectroscopy of subsurface organic layers, revealing that nano-FTIR spectra from thin surface layers differ from that of subsurface layers of the same organic material. Further, we study the correlation of various nano-FTIR peak characteristics and establish a simple and robust method for distinguishing surface from subsurface layers without the need of theoretical modeling or simulations (provided that chemically induced spectral modifications are not present). Our experimental findings are confirmed and explained by a semi-analytical model for calculating nano-FTIR spectra of multilayered organic samples. Our results are critically important for the interpretation of nano-FTIR spectra of multilayer samples, particularly to avoid that geometry-induced spectral peak shifts are explained by chemical effects.

SUBMITTER: Mester L

PROVIDER: S-EPMC7335173 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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Subsurface chemical nanoidentification by nano-FTIR spectroscopy.

Mester Lars L Govyadinov Alexander A AA Chen Shu S Goikoetxea Monika M Hillenbrand Rainer R

Nature communications 20200703 1

Nano-FTIR spectroscopy based on Fourier transform infrared near-field spectroscopy allows for label-free chemical nanocharacterization of organic and inorganic composite surfaces. The potential capability for subsurface material analysis, however, is largely unexplored terrain. Here, we demonstrate nano-FTIR spectroscopy of subsurface organic layers, revealing that nano-FTIR spectra from thin surface layers differ from that of subsurface layers of the same organic material. Further, we study the ...[more]

PMID: 32620874

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Project description:The two factors defining male reproductive success in plants are pollen quantity and quality, but our knowledge about the importance of pollen quality is limited due to methodological constraints. Pollen quality in terms of chemical composition may be either genetically fixed for high performance independent of environmental conditions, or it may be plastic to maximize reproductive output under different environmental conditions. In this study, we validated a new approach for studying the role of chemical composition of pollen in adaptation to local climate. The approach is based on high-throughput Fourier infrared (FTIR) characterization and biochemical interpretation of pollen chemical composition in response to environmental conditions. The study covered three grass species, Poa alpina, Anthoxanthum odoratum, and Festuca ovina. For each species, plants were grown from seeds of three populations with wide geographic and climate variation. Each individual plant was divided into four genetically identical clones which were grown in different controlled environments (high and low levels of temperature and nutrients). In total, 389 samples were measured using a high-throughput FTIR spectrometer. The biochemical fingerprints of pollen were species and population specific, and plastic in response to different environmental conditions. The response was most pronounced for temperature, influencing the levels of proteins, lipids, and carbohydrates in pollen of all species. Furthermore, there is considerable variation in plasticity of the chemical composition of pollen among species and populations. The use of high-throughput FTIR spectroscopy provides fast, cheap, and simple assessment of the chemical composition of pollen. In combination with controlled-condition growth experiments and multivariate analyses, FTIR spectroscopy opens up for studies of the adaptive role of pollen that until now has been difficult with available methodology. The approach can easily be extended to other species and environmental conditions and has the potential to significantly increase our understanding of plant male function.

Dataset Information

Subsurface chemical nanoidentification by nano-FTIR spectroscopy.

Publications

Subsurface chemical nanoidentification by nano-FTIR spectroscopy.

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