Award Data

We propose to develop a theoretical understanding of the relationship between intrinsic geometric structure in both training and latent data and characteristics of functions learned from that data for deep neural network (DNN) architectures. Along the way we propose to also understand the structure of the neural networks that are best trained on a given data set. Both of these theories will lead t ...

The multidisciplinary area of GEOINT is changing and becoming more complex. A major driver of innovation in GEOINT collection and processing is artificial intelligence (AI). AI is being leveraged to help accomplish spatial analysis, change detection, and image or video triage tasks where filtering objects of interest from large volumes of data is critical. NGA is confronting the changing GEOINT l ...

Solar fuels production is necessary for the future of the global economy New highly conductive and stable polymer-electrolytes with low light absorption are required for efficient and cost- effective solar fuels generation Opus 12 will work with Prof Chulsung Bae at Rensselaer Polytechnic Institute (RPI) to further develop the existing polymer-electrolyte chemistry to meet the demands of this chal ...

Solar fuels production is necessary for the future of the global economy. To produce solar fuels from CO2, a highly conductive and stable polymer-electrolyte is needed for this demanding application. A promising class of polymer-electrolytes for electrochemical energy applications has been developed, and this project’s goal is to scale-up production, add quality controls, and reduce waste. The n ...

The goal of the research is to provide pixelated diamond x-ray detectors with the required readout electronics for transmission imaging of hard and soft x-ray beams to facilitate the use of dynamic focusing at advanced light source facilities. This program investigates the use of diamond detectors and the associated readout electronics for x-ray imaging. The present technology, developed by Stony ...

Intense short pulse lasers are playing increasingly important role in high-energy physics research. Laser based electron accelerators are innovative tools to obtain GeV to TeV electron energies for high-energy particle physics experiments. The development of such lasers puts stringent challenges on the very limits of the laser materials themselves. The goal of this project is to develop Ho:sesquio ...

On this effort Toyon Research Corp. and The Pennsylvania State University are developing deep learning-based algorithms for object recognition and new class discovery in look-down infrared (IR) imagery. Our approach involves the development of a hybrid classifier that exploits both transfer learning and semi-supervised paradigms in order to maintain good generalization accuracy, especially when li ...

Society at large and DOE in particular have an interest in the continued development and refinement of a smart grid infrastructure that more efficiently and reliably matches electrical resources to demands. While technological advances in recent years have improved the smart grid, these advances have been limited by a lack of granularity of data (e.g. environmental conditions at multiple locations ...

Near-field scanning optical microscopy (NSOM) is a powerful and unique approach to characterize the chemical, physical and potentially biochemical properties of materials with the nanometer scale resolution in real-time. A key element for NSOM systems that combine optical spectroscopy with scanning probe microscopy, is the actual probe itself. While many commercial vendors offer off-the-shelf meta ...

One of grand challenges in nanoscience and nanotechnology is to achieve fundamental under- standing of the dynamic evolution of materials in actual operating environment, non-equilibrium conditions, or undergoing chemical reactions at the nanoscale. This requires forefront advances in imaging and analysis techniques that combine nanometer-scale spatial resolution, optical excitation and spectrosco ...