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- Ryan Dehoff
- Adam M Guss
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- Yukinori Yamamoto

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.

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.

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

High strength, oxidation resistant refractory alloys are difficult to fabricate for commercial use in extreme environments.

ORNL has developed bacterial strains that can utilize a common plastic co-monomer as a feedstock. This will help enable modern, petroleum-derived plastics to be converted into value-added chemicals.