Award Data

Commercial buildings use 35% of the entire US energy output, and up to a third of that energy is wasted. Rapidly rising fuel costs, increasing concern about climate change, and policy directives from the Biden Administration are all driving the need for increased energy efficiency and the elimination of waste. At the same time, the COVID-19 pandemic has dramatically increased public awareness of t ...

The promise of personalized medicine can be realized in part via point-of-care 3D drug printing, but only if there are reliable quality measures available. Children and seniors may need custom or easy-to-swallow doses, a need now addressed only in a limited way by ad-hoc in-pharmacy compounding. Compliance-targeted enhancements such as flavor and shape choices are particularly important for childr ...

InfraTrac aims to demonstrate the viability of spectroscopy as an effective and practical mechanism for assessing the quality of in-pharmacy 3D drug printing, thereby enabling custom compounding by bringing necessary patient safety controls to this new realm. InfraTrac’s research strategy uses state-of-the-art 3D printing of solid dose forms to create test candidates, comparing the results of ha ...

Early in the covid pandemic, decentralized and democratized AM of PPE was activated to alleviate supply chain failures that prevented normal suppliers of devices like face shields to meet the demands of the domestic health care system. Quality control testing, while critical to reducing risk by ensuring appropriate, safe, and reliable parts, is a time intensive and equipment intensive process. As ...

Additive manufacturing is a growing area of advanced manufacturing (AM) and is comprised of joining multiple layers of materials to build up an object. There are various AM processes but many of them have risks of ensuring that the interfacial bonds between layers are sufficient. A material can potentially be insufficiently bonded at the layer interface creating a threat of delamination and materi ...

In order for manufacturers to unlock the promise of AI for data-driven decision making, they need visibility into large volumes of unstructured knowledge trapped in technical language like work order notes. The process of annotation and knowledge extraction from unstructured technical language data is currently a time consuming and challenging bottleneck to adopting machine learning at scale. In N ...

The proposed innovation uses a model-based approach to streamline understanding and application of standards. NIST standards addressing cybersecurity, presented in the form of documents, spreadsheets, and database tools, provide thousands of complimentary and overlapping items for users to track. Significant effort is expended understanding the standards before attention can be focused on the syst ...

Parman Tech will build a first prototype embodying the NIST-owned technology ‘Optical Particle Sorter.’ The prototype will demonstrate feasibility of a commercial implementation of this technology. The prototype will also serve as the model for subsequent production of several beta-units to be used for obtaining customer feedback and eventually validation of the product.

The proposed innovation will use a model-based approach to streamline understanding and application of standards. NIST standards addressing cybersecurity, presented in the form of documents, spreadsheets, and database tools, provide thousands of complimentary and overlapping items for users to track. Significant effort is expended understanding the standards before attention can be focused on the ...

In order for manufacturers to adopt data-driven decision making, they must tap into unstructured data that sits unused. The process of annotation and knowledge extraction from unstructured text data is a time consuming and challenging bottleneck to adopting machine learning at scale.  This Phase I SBIR proposes implementation of an enhanced cloud-based platform enabling maintenance and other orga ...