Discover reviews trends, future challenges, and strategic directions when it comes to advancing science and innovation in the U.S., including High Energy Physics, with Prof. Dr. Cecilia Van Cauwenberghe, Research Director at Everest Group
Introduction: Science and innovation funding dynamics
Over the past decades, science funding in the United States (U.S.) has been instrumental in driving technological innovation, economic competitiveness, and national security. The U.S. has maintained R&D through a collaborative ecosystem of government agencies, academia, and private industry (Ganz and Vincent, 2024). However, increased business investment, evolving funding models, and growing competition from China and other nations demand key priority changes in these dynamics to keep leadership.
The changing dynamics of R&D investment
The U.S. continues to lead global R&D investment, surpassing Japan, Germany, and the UK combined. However, China has rapidly closed the gap, reaching US$500 billion in R&D spending in 2019 and growing at twice the rate of the U.S. (Ganz and Vincent, 2024). While federal funding has plateaued, business investment in R&D has surged, accounting for 73% of total U.S. R&D funding. This trend, largely driven by tax incentives, has fostered product development and commercialization but raises concerns about the sustainability of basic research (Ganz and Vincent, 2024).
Higher education institutions play a central role in basic research, performing 48% of all fundamental scientific studies, primarily in life sciences, engineering, and physical sciences. Despite this, federal funding for university research has remained stagnant, posing a challenge to long-term scientific exploration (Ganz and Vincent, 2024). The U.S. National Institutes of Health (NIH), the Department of Defense (DOD), and the Department of Energy (DOE) remain the primary federal science funders, yet shifting budget allocations and the growing reliance on industry collaborations have introduced uncertainties in the funding landscape (Boyce, 2023).
The Department of Energy’s role in publicly funded research
The DOE has long been a cornerstone of U.S. energy innovation, supporting nuclear, renewable, and grid modernization research (Boyce, 2023). Its collaborative R&D initiatives have historically driven breakthroughs, from the Manhattan Project to modern clean energy solutions. The Biden administration’s FY 2024 budget request proposed an 18% increase in clean energy research, highlighting the strategic focus on energy security and emissions reduction (Chong, 2023).
However, funding levels for key programs, including ARPA-E and advanced nuclear reactor demonstration projects, remain below recommended targets, raising concerns about long-term technological leadership (Chong, 2023).
Emerging AI-driven research models
Artificial intelligence (AI) and machine learning (ML) are reshaping scientific discovery and R&D strategies across all investigational fields and domains. DOE national laboratories and universities are exploring AI-driven materials discovery, autonomous experimentation, and AI-powered nuclear data analysis to enhance efficiency and accuracy (Pruet, 2024). Proposed initiatives such as AI University Teams and the Scientific Foundation Model Collective aim to establish large-scale, collaborative AI research ecosystems, positioning the U.S. as a global leader in AI-driven science, energy, and security (Pruet, 2024).
Advancements in materials science and AI-driven characterization
Materials science is at the core of numerous technological advancements, from energy storage and semiconductors to advanced manufacturing and sustainable materials. Scientists at the National Renewable Energy Laboratory (NREL) comment that AI/ ML plays a transformative role in materials discovery, enabling faster characterization, predictive modeling, and autonomous experimentation (Spurgeon, 2024). AI-driven electron microscopy and graph-based analytics are now being used to map microstructures and predict material degradation under extreme conditions, accelerating the development of more resilient and efficient materials (Spurgeon, 2024).
The alike transmission electron microscopy (TEM) and X-ray diffraction. These innovations enable scientists to analyze material properties in real-time, significantly improving materials research speed and accuracy (Spurgeon, 2024). Moreover, the rise of intelligent materials science is leading to breakthroughs in clean energy technologies, including high-performance solar cells, next-generation batteries, and advanced catalysts for carbon capture.
Energy Sciences Network (ESnet) and High Energy Physics infrastructure
With High Energy Physics experiments generating petabytescale data, the DOE’s Energy Sciences Network (ESnet) is undergoing significant upgrades to support data mobility, AI-enhanced workflows, and transatlantic connectivity for projects such as the Large Hadron Collider (Zurawski et al., 2024). Expanding network capacity and integrating AI into data analysis will be critical to maintaining leadership in particle physics and neutrino research.
Beyond physics, ESnet is increasingly important in the energy sector by supporting real-time data sharing for smart grids, renewable energy management, and climate modeling. The network facilitates seamless collaboration between national laboratories, universities, and private industries, enabling rapid response to energy challenges. Future enhancements to ESnet will integrate AI-driven network optimization, ensuring efficient handling of large-scale datasets critical for energy forecasting, cybersecurity, and infrastructure resilience (Zurawski et al., 2024).
The future of U.S. science funding and innovation
According to scientific innovation experts and strategists, continued investments in foundational R&D, AI-driven research models, and scientific infrastructure are imperative to sustain U.S. technological leadership. As a fundamental part of such commitment, expanding public-private partnerships, modernizing federal funding mechanisms, and strengthening AI integration will be key to maintaining competitiveness against global rivals such as China and the European Union. Policymakers must balance industry-driven innovation with robust support for basic science to ensure the long-term scientific and economic resilience that has characterized the country over the past decades.
Strategic investments in energy R&D, nuclear science, and AI-enabled research ecosystems will define the future trajectory of U.S. science and innovation funding. By prioritizing collaborative, high-risk, high-reward research, the Nation can drive future materials science, clean energy, and national security breakthroughs.
References
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