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The Concentrating Solar Power: Efficiently Leveraging Equilibrium Mechanisms for Engineering New Thermochemical Storage (CSP: ELEMENTS) Funding Opportunity Announcement (FOA) that is being issued by the U.S. Department of Energy (DOE) is seeking applications that integrate Thermochemical Energy Storage (TCES) systems with a minimum of 6 hours of thermal storage to be used in ≥1 Megawatt-electric (≥1 MWe) scale CSP electricity generation that have promise to achieve a cost target of ≤$15 per kilowatt-hour-thermal (≤$15/kWhth) are the focus of this FOA. Successful projects will culminate in an on-sun demonstration of the thermochemical reactor along with reliable projections of the full scale performance of the integrated storage system through the utilization of validated performance models developed as part of the research and development effort.

This Funding Opportunity Announcement (FOA) solicits grant applications in two related but distinct areas.The first area is in the development and testing of novel tools and methods of neuromodulation that go beyond the existing variations on magnetic or electrical stimulation, and that represent more than an incremental advance over existing electromagnetic approaches. The second distinct area that this FOA seeks to encourage is the optimization of existing electrical and magnetic stimulation methods.

Although invention and proof-of-concept testing of new technologies are a key component of the BRAIN Initiative, to achieve their potential these technologies must also be optimized through feedback from end-users in the context of the intended experimental use. This seeks applications for the optimization of existing and emerging technologies and approaches that have potential to address major challenges associated with recording and manipulating neural activity, at or near cellular resolution, at multiple spatial and temporal scales, in any region and throughout the entire depth of the brain. This FOA is intended for the iterative refinement of emergent technologies and approaches that have already demonstrated their transformative potential through initial proof-of-concept testing, and are appropriate for accelerated development of hardware and software while scaling manufacturing techniques towards sustainable, broad dissemination and user-friendly incorporation into regular neuroscience practice. Proposed technologies should be compatible with experiments in behaving animals, and should include advancements that enable or reduce major barriers to hypothesis-driven experiments. Technologies may engage diverse types of signaling beyond neuronal electrical activity for large-scale analysis, and may utilize any modality such as optical, electrical, magnetic, acoustic or genetic recording/manipulation. Applications that seek to integrate multiple approaches are encouraged. Applications are expected to integrate appropriate domains of expertise, including where appropriate biological, chemical and physical sciences, engineering, computational modeling and statistical analysis.

Understanding the dynamic activity of neural circuits is central to the NIH BRAIN Initiative. This FOA seeks applications for proof-of-concept testing and development of new technologies and novel approaches for largescale recording and manipulation of neural activity to enable transformative understanding of dynamic signaling in the nervous system. In particular, we seek exceptionally creative approaches to address major challenges associated with recording and manipulating neural activity, at or near cellular resolution, at multiple spatial and/or temporal scales, in any region and throughout the entire depth of the brain. It is expected that the proposed research may be high-risk, but if successful could profoundly change the course of neuroscience research. Proposed technologies should be compatible with experiments in behaving animals, and should include advancements that enable or reduce major barriers to hypothesis-driven experiments. Technologies may engage diverse types of signaling beyond neuronal electrical activity for large-scale analysis, and may utilize any modality such as optical, electrical, magnetic, acoustic or genetic recording/manipulation. Applications that seek to integrate multiple approaches are encouraged. Where appropriate, applications are expected to integrate appropriate domains of expertise, including biological, chemical and physical sciences, engineering, computational modeling and statistical analysis.

The Energy, Power, Control, and Networks (EPCN) Program supports innovative research in modeling, optimization, learning, adaptation, and control of networked multi-agent systems, higher-level decision making, and dynamic resource allocation, as well as risk management in the presence of uncertainty, sub-system failures, and stochastic disturbances. EPCN also invests in novel machine learning algorithms and analysis, adaptive dynamic programming, brain-like networked architectures performing real-time learning, and neuromorphic engineering. EPCN's goal is to encourage research on emerging technologies and applications including energy, transportation, robotics, and biomedical devices & systems. EPCN also emphasizes electric power systems, including generation, transmission, storage, and integration of renewable energy sources into the grid; power electronics and drives; battery management systems; hybrid and electric vehicles; and understanding of the interplay of power systems with associated regulatory & economic structures and with consumer behavior.

The Energy, Power, Control, andNetworks (EPCN) Program supports innovative research in modeling, optimization, learning, adaptation, and control of networked multi-agent systems, higher-level decision making, and dynamic resource allocation, as well as risk management in the presence of uncertainty, sub-system failures, and stochastic disturbances. EPCN also invests in novel machine learning algorithms and analysis, adaptive dynamic programming, brain-like networked architectures performing real-time learning, and neuromorphic engineering. EPCN’s goal is to encourage research on emerging technologies and applications including energy, transportation, robotics, and biomedical devices & systems. EPCN also emphasizes electric power systems, including generation, transmission, storage, and integration of renewable energy sources into the grid; power electronics and drives; battery management systems; hybrid and electric vehicles; and understanding of the interplay of power systems with associated regulatory & economic structures and with consumer behavior.

This is a special BAA in support of the Air Force Research Laboratory's (AFRL) University Center of Excellence for High Critical Electric Field Strength Materials. A University Center of Excellence (COE) is defined as a joint effort among Air Force Office of Scientific Research (AFOSR), Air Force Research Laboratory Technology Directorates (AFRL TDs), and an outstanding university or team of universities to perform high priority collaborative research. This center is a joint project between the AFRL's Air Force Office of Scientific Research and the Materials and Manufacturing Directorate (AFRL/RX), and Sensors Directorate (AFRL/RY).

The Geophysics Program supports basic research in the physics of the solid earth to explore its composition, structure, and processes from the Earth's surface to it's deepest interior. Laboratory, field, theoretical, and computational studies are supported. Topics include seismicity, seismic wave propagation, and the nature and occurrence of geophysical hazards; the Earth's magnetic, gravity, and electrical fields; the Earth's thermal structure; and geodynamics. Supported research also includes geophysical studies of active deformation, including geodesy, and theoretical and experimental studies of the properties and behavior of Earth materials.

The Geophysics Program supports basic research in the physics of the solid earth to explore its composition, structure, and processes from the Earth's surface to its' deepest interior. Laboratory, field, theoretical, and computational studies are supported. Topics include (but are not limited to) seismicity, seismic wave propagation, and the nature and occurrence of geophysical hazards; the Earth's magnetic, gravity, and electrical fields; the Earth's thermal structure; and geodynamics. Supported research also includes geophysical studies of active deformation, including geodesy, and theoretical and experimental studies of the properties and behavior of Earth materials.

The Geophysics Program supports basic research in the physics of the solid earth to explore its composition, structure, and processes from the Earth's surface to its' deepest interior. Laboratory, field, theoretical, and computational studies are supported. Topics include (but are not limited to) seismicity, seismic wave propagation, and the nature and occurrence of geophysical hazards; the Earth's magnetic, gravity, and electrical fields; the Earth's thermal structure; and geodynamics. Supported research also includes geophysical studies of active deformation, including geodesy, and theoretical and experimental studies of the properties and behavior of Earth materials.

The Interfacial Processes and Thermodynamics (IPT) program supports fundamental research in engineering areas related to: Interfacial phenomena Mass transport phenomena Molecular thermodynamics Currently, emphasis is placed on molecular engineering approaches at interfaces, especially as applied to the nano-processing of soft materials.  Molecules at interfaces with functional interfacial properties are of special interest and have uses in many new technologies, based on nano-fabrication.  These interfacial molecules may have biomolecular functions at the micro- and nano-scale.  Interfacial materials are generally formed through molecular self-directed, -templated, and/or -assembly, and they are driven primarily by thermodynamic intermolecular forces, although may be influenced by flow and electrical forces.  In some cases, these interfacial processes may also be supplemented by weak chemical reactions.

DARPA is soliciting innovative research proposals in the field of UV laser technology that will enable enhanced detection and discrimination of specific biological and chemical compounds using Raman spectroscopy. The goal of the Laser UV Sources for Tactical Efficient Raman (LUSTER) program is to develop compact, efficient, high-power ultraviolet lasers capable of achieving output power >1 W, wall-plug efficiency >10%, linewidth < 0.01 nm and all at wavelengths between 220-240 nm. Various methods such as direct electrical injection, electron beam pumping, second harmonic generation or other alternatives will be considered as long as all of the metrics can be met or exceeded. See the full DARPA-BAA-14-20 document attached.

The Geospace Section of the Division of Atmospheric and Geospace Sciences, to ensure the health and vitality of solar and space sciences on university teaching faculties, is pleased to offer awards for the creation of new tenure-track faculty positions within the intellectual disciplines which comprise the space sciences. The aim of these awards is to integrate research topics in solar and space physics into basic physics, astronomy, electrical engineering, geoscience, meteorology, computer science, and applied mathematics programs, and to develop space physics graduate programs capable of training the next generation of leaders in this field. Space Science is interdisciplinary in nature and the Faculty Development in the Space Sciences awardees will be expected to establish partnerships within the university community.

The Division of Materials Research (DMR), the Division of Mathematical Sciences (DMS), the Division of Electrical, Communications and Cyber Systems (ECCS), and the Office of Advanced Cyberinfrastructure (OAC) seek to rapidly accelerate quantum materials design, synthesis, characterization, and translation of fundamental materials engineering and information research for quantum devices, systems, and networks. The new program of Enabling Quantum Leap: Convergent Accelerated Discovery Foundries for Quantum Materials Science, Engineering, and Information (Q-AMASE-i) aims to support these goals by establishing Foundries with mid-scale infrastructure for rapid prototyping and development of quantum materials and devices. The new materials, devices, tools and methods developed by Q-AMASE-i will be shared with the science and engineering communities through a Foundry-operated network. Technology transfer of Foundry activities will be enabled by close cooperation with industrial partners.

The aim of this Special Notice under the BAA is to address the current limitations of conventional packaging and support the recent advancements in silicon carbide (SiC) power device technology for military and commercial applications. Wide bandgap power semiconductors, such as SiC, have emerged with properties that allow them to far surpass the performance of conventional silicon (Si) power technology and make them prime candidates for next-generation high-power switching devices for military, as well as commercial, applications. SiC power devices have demonstrated greater than twice the power density of Si power devices and at greater efficiency. Traditional power packaging approaches are now the limiting factor in fully realizing the performance benefits offered by SiC power device technology. Conventional power packaging has a number of opportunities for improvement including, but not limited to, parasitic inductance, heat removal capability, reliability (wirebonds, DBC, large area contacts), transient thermal mitigation, planar packaging, and standard subtractive manufacturing. Solutions are sought for the development of holistic, multiphysics approaches to power module development that address electrical, thermal and thermomechanical issues in a coupled manner to realize the full performance of SiC semiconductor devices. SiC is being explored and/or implemented for low voltage (600 V to 3.3 kV), medium voltage (3.3 kV - 10 kV), and high voltage (10 kV - 24 kV) military and/or commercial applications.

roposals are solicited that show a path for increased current density (at high-efficiency), die size, switching frequency, and blocking voltage (>10 kV) for both low- and high-duty-cycle switches. SiC is an emerging power semiconductor material that has electrical, thermal, and mechanical properties that allow it to far surpass the performance of conventional silicon (Si) power technology, and makes it the prime candidate for next-generation high-voltage switching devices for military, as well as commercial, applications. SiC power devices have been demonstrated to provide greater than twice the power density of Si power devices and at greater efficiency. This program, which endeavors to advance the United States' capability to provide SiC high-voltage high-power semiconductor switches and to identify limitations that must be overcome, builds on the success of previous high-voltage high-power SiC device programs supported by ARL, including HEPS and HVPT, which advanced the previous state-of-the-art and demonstrated performance and robustness at 10-kV and above. Technology limitations/gaps identified by this program may in turn be the focus of more sustained development efforts in the future. Solutions are sought for the development of SiC HV (> 10 kV) semiconductor power switches and diodes.

The Geospace Section of the Division of Atmospheric and Geospace Sciences is pleased to offer awards for the creation of new tenure-track faculty positions within the intellectual disciplines which comprise the space sciences to ensure the health and vitality of solar and space sciences on university teaching faculties. The aim of these awards is to integrate research topics in solar and space physics into basic physics, astronomy, electrical engineering, geoscience, meteorology, computer science, and applied mathematics programs, and to develop space physics graduate programs capable of training the next generation of leaders in this field. Space Science is interdisciplinary in nature and the Faculty Development in the Space Sciences awardees will be expected to establish partnerships within the university community.  NSF funding will support the entire academic year salary and benefits of the newly recruited tenure-track faculty member for a duration of up to five years with a total award amount not to exceed $1,500,000.

The National Science Foundation Directorates for Mathematical and Physical Sciences (MPS), Computer and Information Science and Engineering (CISE), Engineering (ENG), and the Simons Foundation Division of Mathematics and Physical Sciences will jointly sponsor up to two new research collaborations consisting of mathematicians, statisticians, electrical engineers, and theoretical computer scientists. Research activities will be focused on explicit topics involving some of the most challenging questions in the general area of Mathematical and Scientific Foundations of Deep Learning. Each collaboration will conduct training through research involvement of recent doctoral degree recipients, graduate students, and/or undergraduate students from across this multi-disciplinary spectrum. Annual meetings of the Principal Investigators ("PIs") and other principal researchers involved in the collaborations will be held at the Simons Foundation in New York City. This program complements NSF's National Artificial Intelligence Research Institutes program by supporting collaborative research focused on the mathematical and scientific foundations of Deep Learning through a different modality and at a different scale.

The National Science Foundation Directorates for Mathematical and Physical Sciences (MPS), Computer and Information Science and Engineering (CISE), Engineering (ENG), and the Simons Foundation Division of Mathematics and Physical Sciences will jointly sponsor up to two new research collaborations consisting of mathematicians, statisticians, electrical engineers, and theoretical computer scientists. Research activities will be focused on explicit topics involving some of the most challenging questions in the general area of Mathematical and Scientific Foundations of Deep Learning. Each collaboration will conduct training through research involvement of recent doctoral degree recipients, graduate students, and/or undergraduate students from across this multi-disciplinary spectrum. Annual meetings of the Principal Investigators ("PIs") and other principal researchers involved in the collaborations will be held at the Simons Foundation in New York City. This program complements NSF's National Artificial Intelligence Research Institutes program by supporting collaborative research focused on the mathematical and scientific foundations of Deep Learning through a different modality and at a different scale.

The National Science Foundation (NSF), through its Divisions of Electrical, Communications and Cyber Systems (ECCS), Computing and Communication Foundations (CCF), Molecular and Cellular Biosciences (MCB), and Materials Research (DMR) announces a follow-up solicitation on the Semiconductor Synthetic Biology for Information Storage and Retrieval Program (SemiSynBio-II).  Future ultra-low energy storage-based computing systems can be built on principles derived from organic systems that are at the intersection of physics, chemistry, biology, computer science and engineering.  Next-generation information storage technologies can be envisioned that are driven by biological principles and use biomaterials in the fabrication of devices and systems that can store data for more than 100 years with storage capacity 1,000 times more than current storage technologies.  Such a research effort can have a significant impact on the future of information storage and retrieval technologies. This focused solicitation seeks high-risk/high-return interdisciplinary research on novel concepts and enabling technologies that will address the fundamental scientific issues and technological challenges associated with the underpinnings of synthetic biology integrated with semiconductor technology. This research will foster interactions among various disciplines including biology, physics, chemistry, materials science, computer science and engineering that will enable in heretofore unanticipated breakthroughs.