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Understanding the dynamic activity of neural circuits is central to the NIH BRAIN Initiative. 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 FOA 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. Also listed under R01

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.

A central goal of the BRAIN Initiative is to understand how electrical and chemical signals code information in neural circuits and give rise to sensations, thoughts, emotions and actions. While currently available technologies can provide some understanding, they may not be sufficient to accomplish this goal. For example, non-invasive technologies are low resolution and/or provide indirect measures such as blood flow, which are imprecise; invasive technologies can provide information at the level of single neurons producing the fundamental biophysical signals, but they can only be applied to tens or hundreds of neurons, out of a total number in the human brain estimated at 85 billion. Other BRAIN FOAs seek to develop novel technology (RFA-NS-16-006) or to optimize existing technology ready for in-vivo proof-of-concept testing and collection of preliminary data (RFA-NS-16-007) for recording or manipulating neural activity on a scale that is beyond what is currently possible. This FOA seeks applications for unique and innovative technologies that are in an even earlier stage of development than that sought in other FOAs, including new and untested ideas that are in the initial stages of conceptualization.

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.

The Chemical and Biological Separations (CBS) program supports fundamental research on novel methods and materials for separation processes.  These processes are central to the chemical, biochemical, materials, energy, and pharmaceutical industries.  A fundamental understanding of the interfacial, transport, and thermodynamic behavior of multiphase chemical systems as well as quantitative descriptions of processing characteristics in the process-oriented industries is critical for efficient resource management and effective environmental protection.  The program encourages proposals that address emerging research areas and technologies, have a high degree of interdisciplinary thought coupled with knowledge creation, and integrate education and research. Research topics OF PARTICULAR INTEREST in CBS include fundamental molecular-level work on: Nanostructured materials for separations Biorenewable resource separation processes Purification of drinking water Field (flow, magnetic, electrical) induced separations Separation of molecular constituents from blood The duration of unsolicited awards is generally one to three years.  The average annual award size for the program is $80,000.  Proposals requesting a substantially higher amount than this, without prior consultation with the Program Director, may be returned without review.  Small equipment proposals of less than $100,000 will also be considered and may be submitted during the annual submission window. 

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 Department of Biomedical Informatics hosts an annual internship program each summer which provides high school, undergraduate, and graduate students opportunities to pursue research projects in the field of biomedical informatics under the guidance of research and operational staff and renowned faculty mentors in the Department of Biomedical Informatics. Participants learn useful tools and technologies used in biomedical and clinical research and attend weekly seminars to learn more about the various fields and interdisciplinary interactions biomedical informatics facilitates. Interns also gain very useful presentation abilities through regular lab and programmatic presentation opportunities, including an end-of-program poster session. Many students who have participated in this program have gone on to pursue doctoral degrees in biomedicine, biomedical informatics, computer science, and electrical engineering or to complete degrees in medicine and nursing. All student internship positions in the Department of Biomedical Informatics have the potential to be either paid or unpaid, depending on student experience levels and faculty preference. Most positions have the ability to turn into full student employment opportunities, and/or count for course credit (depending on performance) during the school year.

The Biosensing program is part of the Engineering Biology and Health cluster, which also includes 1) the Biophotonics program; 2) the Cellular and Biochemical Engineering program; 3) the Disability and Rehabilitation Engineering program; and 4) the Engineering of Biomedical Systems program. The Biosensing program supports fundamental engineering research on devices and methods for measurement and quantification of biological analytes. Examples of biosensors include, but are not limited to, electrochemical/electrical biosensors, optical biosensors, plasmonic biosensors, and paper-based and nanopore-based biosensors. In addition to advancing biosensor technology development, proposals that address critical needs in biomedical research, public health, food safety, agriculture, forensic, environmental protection, and homeland security are highly encouraged. Proposals that incorporate emerging nanotechnology methods are especially encouraged.

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.

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.

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.

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.

New information technologies can be envisioned that are based on biological principles and that use biomaterials in the fabrication of devices and components; it is anticipated that these information technologies could enable stored data to be retained for more than 100 years and storage capacity to be 1,000 times greater than current capabilities. These could also facilitate compact computers that will operate with substantially lower power than today's computers. Research in support of these goals can have a significant impact on advanced information processing and storage technologies. This focused solicitation seeks high-risk/high-return interdisciplinary research on novel concepts and enabling technologies that will address the 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, engineering, physics, chemistry, materials science, computer science, and information science that will enable heretofore-unanticipated breakthroughs as well as meet educational goals.