Award Data

Redox flow batteries (RFBs) are considered one of the most promising electrochemical technologies for the large-scale storage of renewable electrical energy. They can store large amount of energy up to megawatt-hours (MWh). Despite of the tremendous success, however, RFBs employing aqueous electrolytes are fundamentally limited by the narrow electrochemical window of water leading to low cell volt ...

The bimetallic structure concept consisting of a corrosion resistant surface layer joined on top of an ASME code-approved substrate becomes a promising solution to address the corrosion issue of ASME substrate materials in molten salt environment. Specifically, refractory materials such as molybdenum, tungsten, and alloys containing them are found to be most resistant in molten salt environment an ...

Large, diffraction grade single crystal diamond plates are needed for high power synchrotron and Free- Electron Laser (FEL) sources to enable the next generation of x-ray sources and experimentation. The current materials used cannot handle the heat loads and radiation intensity anticipated. Currently, there are no manufacturers of such material in the US. We propose the growth of high-quality sin ...

Nuclear physics (NP) research has a need for devices to detect, analyze, and track photons, charged particles, and neutral particles such as neutrons, neutrinos, and single atoms. Particle Identification (PID) subsystems, often operating in magnetic fields >1.5 Tesla, require highly segmented (2-3 mm pixel) photodetectors with high gain, low intrinsic background, and high photocathode efficiency t ...

While machine learning is showing great promise for discovering knowledge and patterns in data, it remains very hard to apply its techniques to the complex data which is at the core of DOE mission science, and which is prevalent in many industrial and commercial data science domains. Data complexity results in significant “dark data” that eludes analysis by researchers and business analysts, r ...

High-quality and functionalized material surfaces are essential for next-generation particle accelerators supporting nuclear physics research, i.e. LCLS-II-HE, EIC, CEBAF. Traditionally coatings and surface functionalization are performed with wet chemistry/electroplating; however, process irreproducibility, contamination and ever decreasing supplier base as environmentally-unfriendly wet chemistr ...

High performance computing (HPC) plays a key role in materials science, climate research, en- ergy technology and others. Artificial intelligence (AI) and machine learning (ML) algorithms are becoming a way of rapidly predicting materials properties. However, recent surveys have shown an under-representation by companies that could leverage HPC technologies and AI/ML meth- ods. One reason is that ...

We are developing a machine intelligence (MI) that will infer vertical soil water flux from changes in vertical moisture distribution measured using available moisture sensors. This innovation addresses a serious information deficit that limits water management and conservation efforts, and will have immediate societal impact in high value agricultural regions such as California’s Central Valley ...

Congestion control is at the heart of communication networks since the early days of the Internet. The primary goal of congestion control is to avoid congestion overload on the network while effectively utilizing the available transmission capacity for reliable end-to-end (e2e) transport. Congestion control in today’s Internet is overwhelmingly based on Transmission Control Protocol (TCP) at the ...

The next generation of photonics projects will require the ability to design ever larger devices, and yet not even the present-day devices can be modeled as needed by the innovators, and therefore designed using computation. Modeling capability exists, but it is not cost-competitive due to the amount of computing time needed and the lack of computing facilities by the many small companies who are ...