Group items tagged

The Atomic Molecular and Optical Physics program encompasses four sub-areas of this broad discipline: Precision Measurements, Atomic and Molecular Dynamics, Atomic and Molecular Structure, and Optical Physics. Research supported in the first three sub-areas includes activities in quantum control, cooling and trapping of atoms and ions, low-temperature collision dynamics, the collective behavior of atoms in weakly interacting gases (Bose-Einstein Condensates and dilute Fermi degenerate systems), precision measurements of fundamental constants, and the effects of electron correlation on structure and dynamics. In Optical Physics, support is provided in areas such as nonlinear response of isolated atoms to intense, ultra-short electromagnetic fields, the atom-cav

The experimental nuclear physics program supports research at the frontiers of nuclear science, including: properties and behavior of nuclei and nuclear matter under extreme conditions, and/or as they relate to astrophysical phenomena; the quark-gluon basis for the structure and dynamics of hadrons and nuclei; phase transitions of nuclear matter from normal nuclear density and temperature to the predicted high-temperature quark-gluon plasma; and basic interactions and fundamental symmetries.  This research involves many venues, including low-energy to multi-GeV electrons and photons; intermediate-energy light ions; low-energy to relativistic heavy ions, including radioactive beams; cold and ultra-cold neutrons; as well as non-accelerator-based experiments.  

CEDAR is a broad-based, community-guided, upper atmospheric research program. The goal is to understand the behavior of atmospheric regions from the middle atmosphere upward through the thermosphere and ionosphere into the exosphere in terms of coupling, energetics, chemistry, and dynamics on regional and global scales. These processes are related to the sources of perturbations that propagate upward from the lower atmosphere as well as to solar radiation and particle inputs from above. The activities within this program combine observations, theory and modeling.

This program supports theoretical and computational materials research and education in the topical areas represented in DMR programs, including condensed matter physics, polymers, solid-state and materials chemistry, metals and nanostructures, electronic and photonic materials, ceramics, and biomaterials. The program supports fundamental research that advances conceptual, analytical, and computational techniques for materials research. A broad spectrum of research is supported using electronic structure methods, many-body theory, statistical mechanics, and Monte Carlo and molecular dynamics simulations, along with other techniques, many involving advanced scientific computing. Emphasis is on approaches that begin at the smallest appropriate length scale, such as electronic, atomic, molecular, nano-, micro-, and mesoscale, required to yield fundamental insight into material properties, processes, and behavior and to reveal new materials phenomena. Areas of recent interest include, but are not limited to: strongly correlated electron systems; low-dimensional systems; nonequilibrium phenomena, including pattern formation, microstructural evolution, and fracture; high-temperature superconductivity; nanostructured materials and mesoscale phenomena; quantum coherence and its control; and soft condensed matter, including systems of biological interest.

The DMR Polymers Program supports fundamental research and education on polymeric materials and polymer science. The program portfolio is mainly experimental and highly diverse with components of materials science, chemistry, physics, and other related disciplines. While interdisciplinarity is stressed, central goals include advancing the foundations of polymer science through innovative research and education and pushing back the wide horizon of the field. Polymers are studied from the molecular level through the nano-to-macro continuum using fundamental materials-focused scientific approaches. Such approaches are experimental but may also closely integrate theoretical, computational, or cyber aspects. Broad areas addressed include synthesis, molecular and self-assembly, characterization, phase behavior, structure, morphology, and properties. Particular focus is on transformative approaches to innovative materials with superior properties, on advancing polymer fundamentals and optimizing structure-property relationships, as well as on basic research addressing major societal challenges. High-quality proposals that integrate research, education, and other broader impacts are invited.

The DMR Polymers Program supports fundamental research and education on polymeric materials and polymer science. The program portfolio is mainly experimental and highly diverse with components of materials science, chemistry, physics, and other related disciplines. While interdisciplinarity is stressed, central goals include advancing the foundations of polymer science through innovative research and education and pushing back the wide horizon of the field. Polymers are studied from the molecular level through the nano-to-macro continuum using fundamental materials-focused scientific approaches. Such approaches are experimental but may also closely integrate theoretical, computational, or cyber aspects. Broad areas addressed include synthesis, molecular and self-assembly, characterization, phase behavior, structure, morphology, and properties. Particular focus is on transformative approaches to innovative materials with superior properties, on advancing polymer fundamentals and optimizing structure-property relationships, as well as on basic research addressing major societal challenges. High-quality proposals that integrate research, education, and other broader impacts are invited.

The purpose of this letter is to invite the submission of exceptionally creative conference proposals. The SciSIP program invites organizers and participants from all of the social, behavioral and economic sciences as well as those working in domain-specific applications such as chemistry, biology, physics, or nanotechnology.

The NIH encourages institutions that seek to engage undergraduate students in innovative mentored research training programs to submit applications for cooperative agreement awards through the NIH Building Infrastructure Leading to Diversity (BUILD) initiative, one of three new Common Fund initiatives that together aim to enhance diversity in the biomedical, behavioral, clinical, and social sciences research workforce. Addressing a major leakage point in the research workforce pipeline, BUILD awards are intended to support the design and implementation of innovative programs, strategies and approaches to transform undergraduate research training and mentorship. BUILD awards will also support institutional and faculty development to further strengthen undergraduate research training environments.

The Mechanics of Materials program supports fundamental research on the behavior of solid materials and respective devices under external actions.?? A diverse and interdisciplinary spectrum of research is supported with emphasis placed on fundamental understanding that i) advances theory, experimental, and/or computational methods in Mechanics of Materials, and/or ii) uses contemporary Mechanics of Materials methods to address modern challenges in material and device mechanics and physics. Proposed research can focus on existing or emerging material systems across time and length scales. Intellectual merit typically includes advances in fundamental understanding of deformation, fracture, fatigue, and contact through constitutive modeling, multiscale and multiphysics analysis, computational methods, or experimental techniques.??Recent interests comprise, but are not limited to:?? contemporary materials including multiphase materials and material systems, soft materials, active materials, low-dimensional materials, phononic/elastic metamaterials, friction, wear;??multiphysics methods, mechanics at the nano, meso and microscale and multiscale integration thereof, as well as approaches incorporating fundamental understanding of physics and chemistry into the continuum-level understanding of the response characteristics of materials and material systems.

The nuclear theory program encompasses the structure and reactions of nuclei, and of hadrons in few-nucleon and nuclear environments, and the quark/gluon substructure expressed by QCD.  Supported research includes contributions to broad theoretical advances as well as model building and applications to experimental programs at facilities such as NSCL, RHIC and Jefferson Laboratory, and to astrophysical phenomena. This includes formulating new approaches for theoretical, computational, and experimental research that explore the fundamental laws of physics and the behavior of physical systems; formulating quantitative hypotheses; exploring and analyzing the implications of such hypotheses analytically and computationally; and, in some cases, interpreting the results of experiments. Some awards are co-funded with other programs in the Physics Division and in other divisions.

The BIGDATA program seeks novel approaches in computer science, statistics, computational science, and mathematics, along with innovative applications in domain science, including social and behavioral sciences, geosciences, education, biology, the physical sciences, and engineering that lead towards the further development of the interdisciplinary field of data science

The purpose of the Mentored Quantitative Research Career Development Award (K25) is to attract to NIH-relevant research those investigators whose quantitative science and engineering research has thus far not been focused primarily on questions of health and disease. The K25 award will provide support and "protected time" for a period of supervised study and research for productive professionals with quantitative (e.g., mathematics, statistics, economics, computer science, imaging science, informatics, physics, chemistry) and engineering backgrounds to integrate their expertise with NIH-relevant research. This Funding Opportunity Announcement (FOA) is designed specifically for applicants proposing to lead basic science experimental studies involving humans, referred to in NOT-OD-18-212 as prospective basic science studies involving human participants. These studies fall within the NIH definition of a clinical trial and also meet the definition of basic research. Types of studies that should submit under this FOA include studies that prospectively assign human participants to conditions (i.e., experimentally manipulate independent variables) and that assess biomedical or behavioral outcomes in humans for the purpose of understanding the fundamental aspects of phenomena without specific application towards processes or products in mind. Studies conducted with specific applications toward processes or products in mind should submit under the companion PA-18-395.

The purpose of this Funding Opportunity Announcement (FOA) is to provide opportunities for eligible small business concerns (SBCs) to submit STTR grant applications to develop interactive digital media science, technology, engineering and mathematics (STEM) resources that address student career choice and health and medicine topics for: (1) pre-kindergarten to grade 12 (P-12) students and pre- and in-service teachers ("Teachers") or (2) Informal science education (ISE), i.e., outside the classroom, audiences. Interactive digital media (IDM) are defined as products and services on digital computer-based systems which respond to the user's actions by presenting content such as text, moving image, animation, video, audio, and video games. There is a large body of evidence that IDM technology has the potential to support learning in a variety of contexts from primary and secondary schools, to universities, adult education and workplace training. IDM is widely used to train, educate, and encourage behavioral changes in a virtual world format where progressive learning, feedback on success and user control are combined into an interactive and engaging experience. It is anticipated that this STTR FOA will facilitate the translation of new or existing health and medicine-based, P-12 STEM curricula and museum exhibits into educational Interactive Digital Media STEM (IDM STEM) resources that will provide a hands-on, inquiry-based and learning-by-doing experience for students, teachers and the community.

CMMT supports theoretical and computational materials research in the topical areas represented in DMR's Topical Materials Research Programs (these are also variously known as Individual Investigator Award (IIA) Programs, or Core Programs, or Disciplinary Programs), which include: Condensed Matter Physics (CMP), Biomaterials (BMAT), Ceramics (CER), Electronic and Photonic Materials (EPM), Metals and Metallic Nanostructures (MMN), Polymers (POL), and Solid State and Materials Chemistry (SSMC). The CMMT program supports fundamental research that advances conceptual understanding of hard and soft materials, and materials-related phenomena; the development of associated analytical, computational, and data-centric techniques; and predictive materials-specific theory, simulation, and modeling for materials research.Research may encompass the advance of new paradigms in materials research, including emerging data-centric approaches utilizing data-analytics or machine learning. Computational efforts span from the level of workstations to advanced and high-performance scientific computing. Emphasis is on approaches that begin at the smallest appropriate length scale, such as electronic, atomic, molecular, nano-, micro-, and mesoscale, required to yield fundamental insight into material properties, processes, and behavior, to predict new materials and states of matter, and to reveal new materials phenomena. Approaches that span multiple scales of length and time may be required to advance fundamental understanding of materials properties and phenomena, particularly for polymeric materials and soft matter.

The purpose of this FOAs are to encourage mechanistic research to investigate the impact of sleep disturbances on chronic pain. The mechanisms and processes underlying the contribution of sleep disturbances to chronic pain development and maintenance may be very broad. This FOA encourages interdisciplinary collaborations by experts from multiple fieldsneuroscientists, psychologists,endocrinologists, immunologists, geneticists, pharmacologists, chemists, physicists, behavioral scientists, clinicians, caregivers, and others in relevant fields of inquiry.

The BIGDATA program seeks novel approaches in computer science, statistics, computational science, and mathematics leading towards the further development of the interdisciplinary field of data science. The program also seeks innovative applications in domain science, including social and behavioral sciences, education, physical sciences, and engineering, where data science and the availability of big data are creating new opportunities for research and insights not previously possible. The solicitation invites two categories of proposals: Foundations (BIGDATA: F): those developing or studying fundamental theories, techniques, methodologies, and technologies of broad applicability to big data problems, motivated by specific data challenges and requirements; and Innovative Applications (BIGDATA: IA): those engaged in translational activities that employ new big data techniques, methodologies, and technologies to address and solve problems in specific application domains. Projects in this category must be collaborative, involving researchers from domain disciplines and one or more methodological disciplines, e.g., computer science, statistics, mathematics, simulation and modeling, etc.

 Current product-specific bioequivalence (BE) guidance published by the Office of Generic Drugs for dry powder inhalers (DPIs) include in vitro testing recommendations for single actuation content and aerodynamic particle size distribution, as well as recommendations for a pharmacokinetic study and a pharmacodynamic or clinical endpoint study.  Given the extensive nature of current DPI BE guidance, it is desirable that current in vitro testing for DPIs be more reflective of in vivo performance.  Computational fluid dynamics (CFD) and discrete element modeling (DEM) have been used to predict dry powder aerosol behavior, including the effects of agglomeration and deagglomeration.  The purpose of the study will be to develop a CFD-DEM model which can be used to evaluate the impact of various physicochemical properties and device performance properties on regional deposition, to identify potentially biorelevant ranges for these properties that may be useful for future BE recommendations.   

The Smart and Autonomous Systems (S&AS) program focuses on Intelligent Physical Systems (IPS) that are capable of robust, long-term autonomy requiring minimal or no human operator intervention in the face of uncertain, unanticipated, and dynamically changing situations. IPS are systems that combine perception, cognition, communication, and actuation to operate in the physical world. Examples include, but are not limited to, robotic platforms, self-driving vehicles, underwater exploration vehicles, and smart grids. Most current IPS operate in pre-programmed ways and in a limited variety of contexts. They are largely incapable of handling novel situations, or of even understanding when they are outside their areas of expertise. To achieve robust, long-term autonomy, however, future IPS need to be aware of their capabilities and limitations and to adapt their behaviors to compensate for limitations and/or changing conditions.

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.