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Beyond Beryllium: AI-Accelerated Materials Discovery for Interstellar Spacecraft Shielding

Yue Li, Xu Pan, Kaiyuan Guo

Abstract

Project Daedalus (1973--1978), the most detailed interstellar probe design study ever conducted, specified a 9 mm beryllium erosion shield to protect the spacecraft payload during its 5.9 light-year cruise to Barnard's Star at 12% of the speed of light. This design, however, predated both the isolation of two-dimensional materials and the development of graph neural network (GNN) property predictors. Here, we systematically screen 20 candidate materials--spanning conventional aerospace metals, transition metal dichalcogenides, and ultra-high-temperature ceramics--using density functional theory (DFT) data from the JARVIS database (76,000 materials) with independent validation by the Atomistic Line Graph Neural Network (ALIGNN). We evaluate candidates across four criteria: specific mechanical stiffness (KV/rho), sputtering resistance, thermal neutron absorption cross-section, and thermodynamic stability. Our screening identifies hexagonal boron nitride (h-BN) and boron carbide (B4C) as dual-function materials offering simultaneous mechanical protection and neutron radiation shielding, and we propose a graphene/h-BN/polymer layered heterostructure shield design that achieves an estimated 47% mass reduction relative to the original beryllium specification. These findings will become immediately actionable upon the successful development of fusion pulse propulsion, which we note remains an outstanding engineering challenge.

Beyond Beryllium: AI-Accelerated Materials Discovery for Interstellar Spacecraft Shielding

Abstract

Project Daedalus (1973--1978), the most detailed interstellar probe design study ever conducted, specified a 9 mm beryllium erosion shield to protect the spacecraft payload during its 5.9 light-year cruise to Barnard's Star at 12% of the speed of light. This design, however, predated both the isolation of two-dimensional materials and the development of graph neural network (GNN) property predictors. Here, we systematically screen 20 candidate materials--spanning conventional aerospace metals, transition metal dichalcogenides, and ultra-high-temperature ceramics--using density functional theory (DFT) data from the JARVIS database (76,000 materials) with independent validation by the Atomistic Line Graph Neural Network (ALIGNN). We evaluate candidates across four criteria: specific mechanical stiffness (KV/rho), sputtering resistance, thermal neutron absorption cross-section, and thermodynamic stability. Our screening identifies hexagonal boron nitride (h-BN) and boron carbide (B4C) as dual-function materials offering simultaneous mechanical protection and neutron radiation shielding, and we propose a graphene/h-BN/polymer layered heterostructure shield design that achieves an estimated 47% mass reduction relative to the original beryllium specification. These findings will become immediately actionable upon the successful development of fusion pulse propulsion, which we note remains an outstanding engineering challenge.

Paper Structure

This paper contains 15 sections, 3 equations, 6 figures, 2 tables.

Table of Contents

  1. Introduction
  2. Methods
  3. Mission Parameters
  4. Material Screening Criteria
  5. Material Data Sources
  6. Composite Figure of Merit
  7. Results
  8. Mechanical Properties
  9. Shield Mass Analysis
  10. Multi-Objective Screening
  11. ALIGNN Validation
  12. Layered Heterostructure Shield Concept
  13. Figure of Merit Ranking
  14. Discussion
  15. Conclusion

Figures (6)

  • Figure 1: Voigt bulk modulus $K_V$ of 20 candidate shielding materials (JARVIS-DFT). Dashed line: Be baseline.
  • Figure 2: Specific modulus $K_V/\rho$, the key mass-efficiency metric. Dashed line: Be baseline from the Daedalus design.
  • Figure 3: Erosion-adjusted shield mass for a 5.9 ly mission at $0.12c$. Bar color indicates thermal neutron absorption cross-section (color bar, log scale). Dashed line marks the beryllium baseline (8.5 t). Colored markers indicate material family.
  • Figure 4: Multi-objective screening: specific modulus versus thermal neutron absorption cross-section. Point size is proportional to surface binding energy. Staircase line indicates the Pareto front. The gold star marks beryllium (Daedalus baseline).
  • Figure 5: ALIGNN predictions versus JARVIS-DFT values for (a) $K_V$ and (b) $G_V$. B$_4$C (inverted triangle) is an outlier due to structural complexity. Statistics exclude B$_4$C.
  • ...and 1 more figures