In a groundbreaking advancement for nuclear fusion research, scientists from the Institute of Applied Physics and Computational Mathematics and Tsinghua University have unveiled the results of a comprehensive theoretical evaluation of the five-nucleon helium-5 (^5He) system. This work marks a pivotal step toward resolving enduring uncertainties in nuclear data pivotal for fusion applications. By adopting the Generalized Reduced R-matrix theoretical framework, the researchers achieved an unprecedented unified analysis of multiple reaction channels that involve the ^5He nucleus, which acts as a crucial transient state in key fusion reactions.
Understanding nuclear fusion demands precise knowledge of intermediate nuclear systems that mediate fundamental reaction pathways. The ^5He system lies at the core of several reactions integral to both energy generation and astrophysical processes. Notably, the reaction T(d,n)^4He, where tritium (T) and deuterium (d) interact to produce neutrons and alpha particles, dominates neutron production within thermonuclear fusion setups. Despite its vital role, previous nuclear data repositories have contained evaluated cross sections with incomplete characterizations of uncertainties and covariances, limiting their utility in refined computational models and engineering designs.
To overcome these limitations, the research team utilized the sophisticated R-matrix Analysis Code (RAC), developed under the guidance of Professor Chen Zhenpeng at Tsinghua University. This computational tool integrates the Generalized Reduced R-matrix formalism with advanced covariance analysis protocols, thus enabling the simultaneous optimization of multiple reaction parameters against vast experimental datasets. This approach not only ensures internal consistency across reaction channels but also rigorously quantifies the uncertainties inherent in nuclear cross section evaluations — a critical factor for high-fidelity fusion simulations.
A focal point of the study was the low-energy reaction regime spanning 0.01 to 0.1 MeV. Here, angular distribution measurements exhibit subtle resonance effects that profoundly affect neutron emission profiles from fusion reactions. Detailed partial-wave analyses coupled with Legendre polynomial decompositions elucidated how the resonant 3/2^+ state of ^5He predominantly shapes the forward-angle scattering, while interference patterns between S- and P-wave states linked to the 3/2^- resonance further modulate angular distributions. This nuanced characterization refines theoretical predictions, rendering them more aligned with empirical observations.
Expanding the evaluated reaction energy range represents an important feat of this research. For neutron-induced reactions, the scope was extended up to 46 MeV, with deuteron-induced reactions evaluated up to 30 MeV. This broad coverage surpasses many previous nuclear data libraries, offering a self-consistent and comprehensive dataset that can serve as a benchmark reference. Such a dataset enhances confidence in nuclear reaction modeling for both fundamental physics explorations and applied fusion engineering.
Critically, the evaluated cross section values remain consistent with those from leading nuclear data libraries, including ENDF/B-VIII.0, but the present analysis surpasses predecessors through its exhaustive detailing of uncertainties and correlations. This advance provides fusion researchers and reactor designers with data that are not only reliable but also carry quantified error margins, enabling more robust sensitivity analyses and risk assessments in fusion systems.
The implications of this work extend beyond pure data enhancement. The systematically derived nuclear datasets underpin neutron transport simulations and radiation shielding design, two pillars of practical fusion reactor operation. High-fidelity nuclear data ensure safety protocols meet stringent standards and optimize reactor performance. Thus, this evaluation of the ^5He system contributes directly to the engineering challenges that must be addressed to realize viable fusion energy.
Moreover, the methodology demonstrated here signifies a paradigm shift towards establishing an independent, systematic nuclear data evaluation framework tailored for light nuclear systems. By building from first principles and comprehensive statistical treatment, researchers can generate datasets that better capture complex nuclear interactions, moving beyond empirical tabulations toward theoretically grounded, uncertainty-quantified libraries.
Looking forward, the team plans to apply this pioneering approach to a suite of other light nuclei that play roles in fusion and astrophysics, including ^5Li, ^6He, and ^12C. Developing similarly rigorous evaluations for these systems will further solidify the nuclear data foundation that fusion energy development depends on. As the field edges closer to commercial fusion power, such foundational studies are crucial for bridging theoretical nuclear physics and engineering implementation.
In summary, the Generalized Reduced R-matrix theoretical analysis of the ^5He system represents a decisive enhancement in fusion nuclear data accuracy and consistency. By harmonizing multiple reaction channels within a unified framework and meticulously characterizing low-energy resonance phenomena, this work extends the boundaries of both computational nuclear physics and fusion reactor design. The improved understanding of ^5He’s reaction dynamics not only advances nuclear science but also serves as a cornerstone for the next generation of fusion research and technology.
This study was published in the journal Nuclear Science and Techniques on January 28, 2026, and stands as a testament to international collaboration and computational prowess in tackling one of science’s most demanding frontiers—efficient, reliable, and safe nuclear fusion energy.
Article Title: Generalized reduced R-matrix theoretical analysis of the 5^He system
News Publication Date: 28-Jan-2026
Web References:
10.1007/s41365-025-01874-2
Image Credits: Xu Han
Keywords
Nuclear physics, Nuclear fusion
