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Synopsis

Plasma science is a transdisciplinary field of research where fundamental studies in many disciplines, including plasma physics, plasma chemistry, materials science, and space science, come together to advance knowledge for discovery and technological innovation.  The primary goal of the ECosystem for Leading Innovation in Plasma Science and Engineering (ECLIPSE) program is to identify and capitalize on opportunities for bringing fundamental plasma science investigations to bear on problems of societal and technological need within the scope of science and engineering supported by the participating NSF programs.

The ECLIPSE meta-program has been created to foster an inclusive community of scientists and engineers, an ecosystem spanning multiple NSF Directorates, in the pursuit of translational research at the interface of fundamental plasma science and technological innovation.  The ECLIPSE program builds on the long history of NSF leadership in supporting multi-disciplinary research in plasma science and engineering, and is intended to enhance organizational

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RSS feed source: National Science Foundation

Synopsis

Correctness for Scientific Computing Systems (CS2) is a joint program of the National Science Foundation (NSF) and the Department of Energy (DOE). The program addresses challenges that are both core to DOE’s mission and essential to NSF’s mission of ensuring broad scientific progress. The program’s overarching goal is to elevate correctness as a fundamental requirement for scientific computing tools and tool chains, spanning low-level libraries through complex multi-physics simulations and emerging scientific workflows.

At an elementary level, correctness of a system means that desired behavioral properties will be satisfied during the system’s execution. In the context of scientific computing, correctness can be understood, at both the level of software and hardware, as absence of faulty behaviors such as excessive numerical rounding, floating-point exceptions, data races deadlocks, memory faults, violations of specifications at interfaces of system modules, and so on. The CS2 program puts

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The U.S. National Science Foundation (NSF) has announced six major awards through its EPSCoR Research Infrastructure Improvement Program: Focused EPSCoR Collaborations (FEC), investing $29.2 million across 11 jurisdictions to strengthen research capacity and drive translational research across the nation.

These four-year awards aim to catalyze transformative research and infrastructure enhancement in states historically underfunded in federal research. The selected projects span critical areas, including use-inspired research in the study of Earth systems, wildfire management, water resource management, ecosystem and human health risks, functionality of electronic devices, biotechnology and artificial intelligence-driven health care.

“These EPSCoR FEC awards are an example of NSF’s commitment to ensuring that all states and jurisdictions across the United States have the opportunity to be part of our research enterprise and benefit from the jobs and economic prosperity that result from American innovation,” said Brian Stone, performing the duties of the NSF director. “These multi-state collaborative teams are tackling real-world research challenges that matter to the citizens of their regions while also building competitive research environments for the entire nation.”

This year’s FEC awards include:

Optical properties of mineral dust aerosols: Building capacity for use-inspired applications through experimental and theoretical investigations (Nevada System of Higher Education – Desert Research Institute, University of Oklahoma Norman Campus and University of Wyoming) Mineral dust aerosols are significant in the atmosphere, affecting radiative forcing, ecosystem fertilization,

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The U.S. National Science Foundation Directorate for Technology, Innovation and Partnerships (NSF TIP) announced an inaugural investment of nearly $32 million to five teams across the U.S. through the NSF Use-Inspired Acceleration of Protein Design (NSF USPRD) initiative. This effort aims to accelerate the translation of artificial intelligence-based approaches to protein design and enable new applications of importance to the U.S. bioeconomy.

“NSF is pleased to bring together experts from both industry and academia to confront and overcome barriers to the widespread adoption of AI-enabled protein design,” said Erwin Gianchandani, NSF assistant director for TIP. “Each of the five awardees will focus on developing novel approaches to translate protein design techniques into practical, market-ready solutions. These efforts aim to unlock new uses for this technology in biomanufacturing, advanced materials, and other critical industries. Simply put, NSF USPRD represents a strategic investment in maintaining American leadership in biotechnology at a time of intense global competition.”

Researchers have made significant progress in predicting the 3D structures of proteins and are now leveraging this knowledge to design proteins with specific, desirable characteristics. These advances have been driven by macromolecular modeling, access to training data, applications of AI and machine learning, and high-throughput methods for protein characterization. The NSF USPRD investment seeks to build on this foundation by bringing together cross-disciplinary and cross-sector experts nationwide. The goal is to

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