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Quantum-Enabled Bioimaging and Sensing Approaches for Bioenergy

Sector: Biomass • Location: United States of America

Source: Grants.gov

Project
Archived

BER seeks to advance our understanding of bioimaging by using new quantum science-enabled areas that could resolve limitations of classical optics including resolution and detection limits, signal-to-noise ratio, limitations on temporal dynamics, long term signal stability, sample photodamage and limited penetration, or selective biomolecule sensing. Fundamental research concepts and use-inspired,

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The project “Quantum-Enabled Bioimaging and Sensing Approaches for Bioenergy” is an infrastructure initiative in the Biomass sector, located in United States of America. Taiyo aggregates data on it from Grants.gov.

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Description

Description

BER seeks to advance our understanding of bioimaging by using new quantum science-enabled areas that could resolve limitations of classical optics including resolution and detection limits, signal-to-noise ratio, limitations on temporal dynamics, long term signal stability, sample photodamage and limited penetration, or selective biomolecule sensing. Fundamental research concepts and use-inspired, early prototype research are needed to realize quantum-enabled bioimaging and sensing. Promising approaches could employ photon entanglement, tunneling, quantum correlation, or other quantum phenomena to production and detection of photons or electrons for bioimaging. Applications must enable in situ imaging of live or preserved plant and microbial systems relevant to bioenergy research supported by BER. Current bioimaging techniques measure structure and dynamics to complement biomolecule identification and reactions in plant-microbe biosystems. This information is often crucial for validating hypotheses of cellular metabolism or synthetically engineered pathways. Biological macromolecules that catalyze metabolic and transport reactions exist in spatially defined or membrane-bound regions in the cell often deep within the living organism. Spatial and temporal information characterize the dynamic, sequential context for biochemical steps and substrates, metabolites, enzymes, and regulatory molecules within a biological process or metabolic pathway of interest. A major challenge is to understand how metabolic pathways are organized within topological constraints at the subcellular scale deep within living systems. Techniques to understand the dynamic organismal function, and location of macromolecules involved in these pathways is key towards developing a better understanding of the spatiotemporal dependence of metabolic processes in biological systems at cellular and subcellular levels.

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High

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100%

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