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- Adam M Guss
- Singanallur Venkatakrishnan
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- Andrzej Nycz
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ORNL researchers have developed a deep learning-based approach to rapidly perform high-quality reconstructions from sparse X-ray computed tomography measurements.

By engineering the Serine Integrase Assisted Genome Engineering (SAGE) genetic toolkit in an industrial strain of Aspergillus niger, we have established its proof of principle for applicability in Eukaryotes.

We have been working to adapt background oriented schlieren (BOS) imaging to directly visualize building leakage, which is fast and easy.

Among the methods for point source carbon capture, the absorption of CO2 using aqueous amines (namely MEA) from the post-combustion gas stream is currently considered the most promising.

We present a comprehensive muti-technique approach for systematic investigation of enzymes generated by wastewater Comamonas species with hitherto unknown functionality to wards the depolymerization of plastics into bioaccessible products for bacterial metabolism.

We present the design, assembly and demonstration of functionality for a new custom integrated robotics-based automated soil sampling technology as part of a larger vision for future edge computing- and AI- enabled bioenergy field monitoring and management technologies called

Detection of gene expression in plants is critical for understanding the molecular basis of plant physiology and plant responses to drought, stress, climate change, microbes, insects and other factors.

This technology identifies enzymatic routes to synthesize amide oligomers with defined sequence to improve polymerization of existing materials or enable polymerization of new materials. Polymers are generally composed of one (e.g. Nylon 6) or two (e.g.

The technologies described provides for the upcycling of mixed plastics to muonic acid and 3-hydroxyacids.

This invention is for bacterial strains that can utilize lignocellulose sugars. This will improve the efficiency of bioproduct formation in these strains and reduce the greenhouse-gas emission of an industrial bi