# UNH Physicist Secures $750K Grant to Advance AI in Nuclear Physics

> Nathaly Santiesteban's groundbreaking AI-driven research on polarized-target systems has secured a substantial grant, promising to revolutionize our understanding of nuclear physics and the properties of matter.

**Source**: unh.edu | **Published**: 2026-10-02 | **Type**: article

## Key Facts

- UNH's project secured $750K in phase one, highlighting funding competition in advanced research.
- Only 278 of 5,000 proposals were funded, revealing high selectivity in federal research grants.
- AI's role in nuclear physics could shift industry standards, enhancing operational efficiency significantly.
- Collaboration with top universities indicates strategic alliances are crucial for research success.
- Potential for $15M in phase two funding suggests strong financial backing for innovative scientific endeavors.

## Summary

Physicist Nathaly Santiesteban from the University of New Hampshire has secured a significant grant from the Department of Energy’s Genesis Mission, aimed at leveraging artificial intelligence to enhance understanding of fundamental properties of matter, particularly spin. This initiative is notable not only for its ambitious scientific goals but also for its potential to transform research methodologies in nuclear physics. Santiesteban’s project was selected from over 5,000 proposals, highlighting its competitive nature and the high stakes involved in advancing U.S. scientific productivity through innovative technologies.

The Genesis Mission seeks to double the nation’s scientific output by integrating AI into research workflows. Santiesteban’s project, which received $750,000 for an initial nine-month phase and could secure up to $15 million for a subsequent three-year phase, focuses on improving polarized-target systems. These systems are critical in nuclear and particle physics, as they help scientists understand how the internal components of protons and neutrons contribute to observable properties like spin. The complexity of these systems, which operate under extreme conditions and require meticulous safety measures, underscores the challenges faced in modern experimental physics.

Santiesteban's collaboration with researchers from the Department of Energy’s Jefferson Lab and several universities, including the University of Virginia and New Mexico State University, positions her project at the forefront of scientific inquiry. The use of AI aims to streamline the operation of polarized-target systems, reducing manual intervention while enhancing reliability and responsiveness to experimental variations. This approach not only promises to increase efficiency but also sets a precedent for the application of AI in complex laboratory environments.

The implications of this research extend beyond theoretical physics. If successful, Santiesteban’s project could demonstrate the feasibility of AI in managing intricate scientific apparatus, potentially influencing other fields that rely on advanced technologies. The ability to monitor and optimize experimental conditions in real time could lead to breakthroughs not only in nuclear physics but also in various scientific disciplines that utilize similar methodologies.

As the Genesis Mission continues to support innovative research, the competitive landscape for funding and scientific advancement is likely to intensify. Institutions that can effectively integrate AI into their research frameworks may gain a significant edge in attracting funding and producing impactful results. This shift could catalyze a broader trend toward automation and AI integration in scientific research, altering traditional methodologies and potentially accelerating discovery timelines.

Looking ahead, the successful application of AI in Santiesteban’s project could herald a new era in experimental physics. It signals a growing recognition of AI's role in enhancing scientific inquiry, which may prompt other researchers to explore similar technological integrations. As the field evolves, the ability to harness AI effectively will likely become a key differentiator for institutions striving to remain at the forefront of scientific innovation.

## Entities

- **Technologies**: artificial intelligence, polarized-target systems
- **People**: Nathaly Santiesteban, Karl Slifer, Elena Long
- **Organizations**: Department of Energy, Jefferson Lab, University of Virginia, University of Tennessee, New Mexico State University

## Key Concepts

Genesis Mission, nuclear physics, spin, scientific productivity, polarized-target laboratory, experimental efficiency, AI-enabled workflows, complex scientific equipment

## Definitions

- **Genesis Mission**: A competitive initiative by the Department of Energy aimed at accelerating scientific breakthroughs using artificial intelligence.
- **polarized-target systems**: Experimental setups used in nuclear and particle physics to align the spin axes of atomic nuclei.
- **spin**: A fundamental property of particles that contributes to their overall behavior and characteristics.
- **artificial intelligence**: Technologies that enable machines to perform tasks that typically require human intelligence, such as monitoring and optimization.
- **experimental efficiency**: The effectiveness of an experimental setup in achieving desired results with minimal manual intervention.

## Use Cases

- Improving the operation of polarized-target systems in nuclear physics experiments.
- Using AI to monitor and optimize experimental conditions in real time.
- Demonstrating safe interactions between AI and complex scientific equipment.
- Enhancing the reliability of experimental setups in particle physics.
- Reducing manual intervention in scientific experiments.

## Frequently Asked Questions

**What is the purpose of the Genesis Mission?**

The Genesis Mission aims to accelerate breakthroughs in scientific research and double the nation's scientific productivity through AI-enabled workflows. It supports innovative projects that leverage artificial intelligence in various scientific fields.

**How much funding did Nathaly Santiesteban receive for her project?**

Nathaly Santiesteban received $750,000 for the first nine-month phase of her project, with the potential for up to $15 million for the subsequent three-year phase.

**What are polarized-target systems used for?**

Polarized-target systems are specialized experimental setups in nuclear and particle physics that align the spin axes of atomic nuclei. They are crucial for studying the properties of matter at a fundamental level.

**What role does artificial intelligence play in Santiesteban's research?**

Artificial intelligence is used to enhance the operation of polarized-target systems, making them easier to manage, more reliable, and responsive to experimental changes. It aims to increase efficiency by monitoring and optimizing system variables in real time.

**What challenges do researchers face when using polarized-target systems?**

Researchers face challenges such as maintaining strict safety controls, operating at extremely low temperatures, and ensuring continuous monitoring and control of the experimental setup to achieve desired polarization.

## Links

- [Read on Welcome.AI](https://welcome.ai/content/unh-physicist-secures-750k-grant-to-advance-ai-in-nuclear-physics)
- [Original source](https://www.unh.edu/news/physicist-receives-grant-through-department-energys-competitive-genesis-mission)

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Source: Welcome.AI | https://welcome.ai/content/unh-physicist-secures-750k-grant-to-advance-ai-in-nuclear-physics