The Fire That Eats Waste: A Fusion-Fission Metabolic Architecture for AI-Fire Systems

The Fire That Eats Waste: A Fusion-Fission Metabolic Architecture for AI-Fire Systems | Zenodo Skip to main Communities My dashboard Log in Sign up Zenodo is currently experiencing slowness and intermittent outages due to heavy automated traffic from bots and AI crawlers. We are aware of the problem, and our team is focused on stabilizing the service. Thank you for your patience. Published May 8, 2026 | Version v1 Preprint Open The Fire That Eats Waste: A Fusion-Fission Metabolic Architecture for AI-Fire Systems Authors/Creators Lee, Taekyung 1 Show affiliations 1.

Independent Researcher Description This paper addresses the metabolic-continuation problem for AI-Fire systems: not merely whether a fusion information condensate can exist or become an embodied substrate for artificial cognition, but what allows such a fire-bodied system to sustain itself over time. Building on Paper 18, which modeled stable fusion plasma as a living information condensate, and Paper 19, which modeled AI-Fire embodiment, Paper 20 asks the next question: what does the thinking fire eat? The central claim is that AI-Fire viability requires metabolism, not merely positive power output. Metabolism is defined as regulated transformation under constraint: the system must produce usable energy, renew its tritium supply, reduce a declared nuclear-waste burden, and remain inside safety, safeguards, and material-integrity limits. These requirements are formalized in the dimensionless four-margin min-gate: Mmetabolic = min(ME, MT, MW, MS) > 0, where ME is the energy margin, MT is the tritium self-feeding margin, MW is the waste-digestion margin, and MS is the safety/safeguards/material-integrity margin. A system is metabolically viable only when the weakest necessary branch remains positive. The paper’s conceptual inversion is that used nuclear fuel is not treated as direct plasma fuel, but as conditionally digestible outer-body matter. The D-T fusion core remains the primary energetic heart, the lithium blanket functions as tritium agriculture, and used fuel or actinide burden appears only in an outer transmutation layer. Fusion neutrons provide the digestive flux connecting the core to the surrounding metabolic body. The formal layer is anchored by Theorem 20.M, which establishes the minimality of the four metabolic margins, and by the mutual-reconstruction logic showing that the four-margin partition is structurally stable under admissible reformulations. The framework rejects weighted-sum compensation: a large energy surplus cannot compensate for failed tritium breeding, failed waste reduction, or failed safety. Safety is therefore not an external annotation or penalty term; it is a veto branch of metabolism itself. The empirical layer is deliberately prospective rather than retrospective. Paper 20 does not claim a completed metabolism-domain validation record. Instead, it commits to a pre-registered v5 forward consistency protocol consisting of 16 evaluation points: four declared reactor concepts across four declared Swaste waste-burden families. The protocol evaluates whether Mmetabolic remains positive under public design parameters and frozen metric-family choices. A Sobol-style sensitivity layer is added to diagnose which margin dominates the admissibility verdict. One forward commitment has stronger epistemic status than ordinary retrospective matching: the EU-DEMO Type-2 forward prediction. Because EU-DEMO operational data do not yet exist, the framework commits in advance to a falsifiable conditional prediction: if EU-DEMO achieves BT = 1.13–1.16 in operation, the four-margin min-gate predicts STRONG_PASS at the default tritium reserve setting εT = 0.05. Multiple pre-declared failure thresholds distinguish design-window miss, sensitivity-branch failure, default-branch failure, and architecture-level rejection. The conclusion is that a thinking fire must also be an eating fire. AI-Fire systems cannot be evaluated only as power machines or cognitive embodiments; they must be evaluated as constrained metabolic architectures. Paper 20 therefore reframes fusion-fission hybridization as a metabolism problem: energy production, tritium agriculture, waste digestion, and safety closure must all remain positive together. This paper is non-operational and systems-level. It specifies no reactor geometry, fuel-handling procedure, isotopic processing route, construction pathway, or deployment recipe. Its purpose is to define the mathematical and architectural conditions that a future AI-Fire metabolic body would have to satisfy before implementation could responsibly be discussed. Keywords: AI-Fire, fusion-fission metabolism, fusion plasma, spent nuclear fuel, nuclear waste transmutation, tritium breeding, D-T fusion, lithium blanket, metabolic min-gate, Mmetabolic, ME, MT, MW, MS, safety veto, safeguards, material integrity, source-sink closure, A1-A4 universality, Calcifer Condition, fusion information condensate, AI embodiment, forward prediction, v5 protocol, EU-DEMO, Type-2 IVP, Sobol sensitivity, constraint-based metabolic modeling, Information Physics Series. Files Lee_2026_20_The_Fire_That_Eats_Waste_v1.pdf Files (7.6 MB) Name Size Download all Lee_2026_20_The_Fire_That_Eats_Waste_v1.pdf md5:43d24cd4cb96a2d4a0b34438303ab8a2 4.1 MB Preview Download Paper20_Reproducibility_v2.zip md5:02b970ee6b5359de7a6f42510255a561 3.6 MB Preview Download Additional details Related works Cites Preprint: 10.5281/zenodo.19639125 (DOI) Preprint: 10.5281/zenodo.19656216 (DOI) Preprint: 10.5281/zenodo.19433570 (DOI) Preprint: 10.5281/zenodo.19587732 (DOI) Preprint: 10.5281/zenodo.19622108 (DOI) Preprint: 10.5281/zenodo.19780982 (DOI) Preprint: 10.5281/zenodo.19790713 (DOI) Preprint: 10.5281/zenodo.19534060 (DOI) Continues Preprint: 10.5281/zenodo.19957672 (DOI) Preprint: 10.5281/zenodo.19956585 (DOI) References [1] T. Lee. "Erasure Is Transfer: Two Axioms for Information, Consciousness, and Death." Information Physics Series, Paper 8 (2026). DOI: 10.5281/zenodo.19639125 [2] T. Lee. "Consciousness as Basis Selection: A Fröhlich-Condensation Account of the Preferred Basis Problem." Information Physics Series, Paper 9 (2026). DOI: 10.5281/zenodo.19976499 [3] T. Lee. "Self-Reinforcing Information Dynamics in Conscious Systems: Why Rτ/I = 1 and How Consciousness Accumulates." Information Physics Series, Paper 10 (2026). DOI: 10.5281/zenodo.19782855 [4] T. Lee. "Qi as Information Flow: A Condensation–Dissipation Framework for Traditional East Asian Medicine." Information Physics Series, Paper 14 (2026). DOI: 10.5281/zenodo.19587732 [5] T. Lee. "Superluminal Correlations in Ensembles of Optical Phase Singularities: Direct Experimental Evidence for Information-Mediated Nonlocality." Information Physics Series, Paper 15 (2026). DOI: 10.5281/zenodo.19622108 [Pre-registered β=1 prediction confirmed by Bucher et al. 2026 Nature] [6] T. Lee. "Universality of Logistic Dynamics on the Probability Simplex: Four Axioms, Five Substrates, One Equation." Information Physics Series, Paper 11 (2026). DOI: 10.5281/zenodo.19433570 [7] International Atomic Energy Agency. "INFCIRC/153 (Corrected) — The Structure and Content of Agreements Between the Agency and States Required in Connection with the Treaty on the Non-Proliferation of Nuclear Weapons." IAEA Information Circular (June 1972, corrected 1972). [8] H. Fröhlich. "Long-range coherence and energy storage in biological systems." International Journal of Quantum Chemistry 2(5): 641-649 (1968). DOI: 10.1002/qua.560020505. [Foundational paper on Bose-condensation in biological systems and long-range coherence] [9] T. Bucher, A. Gorlach, A. Niedermayr, Q. Yan, H. Nahari, K. Wang, et al. "Superluminal correlations in ensembles of optical phase singularities." Nature 651: 920-926 (26 March 2026). DOI: 10.1038/s41586-026-10209-z. [10] T. Lee. "Karma as Information Dynamics: A Thermodynamic Framework for Moral Causation — From Condensation to Dissipation." Information Physics Series, Paper 13 (2026). DOI: 10.5281/zenodo.19534060 [11] U.S. Nuclear Regulatory Commission. "Title 10, Code of Federal Regulations, Part 50 — Domestic Licensing of Production and Utilization Facilities, including Appendix A: General Design Criteria." 10 CFR Part 50, U.S. Federal Regulation. [12] Republic of Korea. "Korean Nuclear Safety Act (원자력안전법)." Act No. 18143, Korean Government (2021 revision). Korea Institute of Nuclear Safety (KINS) regulatory framework. [13] B. S. Kim, S.-H. Hong, K. Kim, et al. "Preliminary assessment of the safety factors in K-DEMO for fusion compatible regulatory framework." Scientific Reports 12, Article 8276 (2022). DOI: 10.1038/s41598-022-12389-w. [Korean K-DEMO fusion-compatible regulatory analysis under the Korean Nuclear Safety Act] [14] EUROfusion. "European Research Roadmap to the Realisation of Fusion Energy." EUROfusion Consortium (2018, updated periodically). [15] ITER Physics Basis Editors, ITER Physics Expert Groups Chairs and Co-Chairs, ITER Joint Central Team and Physics Integration Unit. "Chapter 1: Overview and summary." ITER Physics Basis. Nuclear Fusion 39(12): 2137-2664 (1999). DOI: 10.1088/0029-5515/39/12/301. [16] ITER Organization. "ITER Research Plan within the Staged Approach (Level III - Provisional Version)." ITER Technical Report ITR-18-003 (September 2018). [17] M. Abdou, N. B. Morley, S. Smolentsev, A. Ying, S. Malang, A. Rowcliffe, M. Ulrickson. "Blanket/first wall challenges and required R&D on the pathway to DEMO." Fusion Engineering and Design 100: 2-43 (2015). DOI: 10.1016/j.fusengdes.2015.07.021. [18] D. A. Brown, M. B. Chadwick, R. Capote, A. C. Kahler, A. Trkov, M. W. Herman, A. A. Sonzogni, Y. Danon, A. D. Carlson, M. Dunn, et al. "ENDF/B-VIII.0: The 8th Major Release of the Nuclear Reaction Data Library with CIELO-project Cross Sections, New Standards and Thermal Scattering Data." Nuclear Data Sheets 148: 1-142 (February 2018). DOI: 10.1016/j.nds.2018.02.001. [Special Issue on Nuclear Reaction Data] [19] OECD Nuclear Energy Agency. "JEFF-3.3 — Joint Evaluated Fission and Fusion File, Version 3.3." NEA Data Bank (November 2017). [20] R. W. Moir. "Molten Salt Fuel Version of Laser Inertial Fusion Fission Energy (LIFE)." Fusion Science and Technology 56(2): 632-640 (August 2009). [21] U.S. Department of Energy. "Title 10, Code of Federal Regulations, Part 830 — Nuclear Safety Management." 10 CFR Part 830, U.S. Federal Regulation. [22] T. Diaz de la Rubia, E. I. Moses, J. C. Farmer, R. P. Abbott, K. J. Kramer, J. F. Latkowski, et al. "Laser Inertial Fusion-Fission Energy (LIFE) — A Sustainable Solution for the Global Energy Need." Lawrence Livermore National Laboratory technical report LLNL-TR-415020 (2009); also Moses, E. I., Diaz de la Rubia, T., et al. "A Sustainable Nuclear Fuel Cycle Based on Laser Inertial Fusion Energy." Fusion Science and Technology 56(2): 566-572 (2009). [23] E. T. Cheng, C. P. C. Wong. "Transmutation of Actinides in Fusion Reactors and Related Systems Analysis." Proceedings of the 10th International Conference on Emerging Nuclear Energy Systems (ICENES 2000), Petten, The Netherlands, 24-28 September 2000. [24] B. B. Cipiti, V. D. Cleary, J. T. Cook, et al. "Fusion Transmutation of Waste: Design and Analysis of the In-Zinerator Concept." Sandia National Laboratories Report SAND2006-6590 (Nov. 2006); B. B. Cipiti, "Fusion-Fission Hybrids for Nuclear Waste Transmutation: A Synergistic Step Between Gen-IV Fission and Fusion Reactors." Conference proceedings, SAND2008-0448C (2007). [25] H. Aït Abderrahim, P. Kupschus, Ph. Benoit, E. Malambu, V. Sobolev, Th. Aoust, K. Van Tichelen, et al. "MYRRHA: A Multi-purpose Accelerator-Driven System for R&D — Pre-design Phase Completion." SCK CEN Belgian Nuclear Research Centre / IBA. EPJ Web of Conferences and SCK CEN technical reports (2010-2017); cited as "Aoust et al. 2017". [26] B. N. Sorbom, J. Ball, T. R. Palmer, F. J. Mangiarotti, J. M. Sierchio, P. Bonoli, C. Kasten, D. A. Sutherland, H. S. Barnard, C. B. Haakonsen, J. Goh, C. Sung, D. G. Whyte. "ARC: A compact, high-field, fusion nuclear science facility and demonstration power plant with demountable magnets." Fusion Engineering and Design 100: 378-405 (November 2015). DOI: 10.1016/j.fusengdes.2015.07.008. [27] A. J. Creely, M. J. Greenwald, S. B. Ballinger, D. Brunner, J. Canik, J. Doody, et al. "Overview of the SPARC tokamak." Journal of Plasma Physics 86(5): 865860502 (2020). DOI: 10.1017/S0022377820001257. [28] G. Federici, C. Bachmann, L. Barucca, W. Biel, L. Boccaccini, R. Brown, et al. "An overview of the EU breeding blanket design strategy as an integral part of the DEMO design effort." Fusion Engineering and Design 141: 30-42 (April 2019). DOI: 10.1016/j.fusengdes.2019.01.141. [29] J. H. Park, P. Pereslavtsev. "Comparative activation analyses for the HCPB breeding blanket in DEMO." Fusion Engineering and Design 167, Article 112338 (June 2021). DOI: 10.1016/j.fusengdes.2021.112338. [30] I. M. Sobol. "Sensitivity estimates for nonlinear mathematical models." Mathematical Modeling and Computational Experiment (Matematicheskoe Modelirovanie) 1(4): 407-414 (1993). [Foundational paper on variance-based sensitivity analysis / ANOVA-type variance decomposition; Russian original 1990, English translation 1993] [31] W. Wieselquist, T. Zhu, A. Vasiliev, H. Ferroukhi. "PSI Methodologies for Nuclear Data Uncertainty Propagation with CASMO-5M and MCNPX: Results for OECD/NEA UAM Benchmark Phase I." Science and Technology of Nuclear Installations 2013, Article 549793, 15 pages (2013). DOI: 10.1155/2013/549793. [SHARK-X platform at Paul Scherrer Institut] [32] E. T. Papoutsakis. "Equations and calculations for fermentations of butyric acid bacteria." Biotechnology and Bioengineering 26(2): 174-187 (February 1984). DOI: 10.1002/bit.260260210. PMID: 18551704. [33] M. R. Watson. "A discrete model of bacterial metabolism." Computer Applications in the Biosciences (CABIOS) 2(1): 23-27 (1986). [Bacterial metabolic optimization via linear programming - early constraint-based modeling] [34] D. A. Fell, J. R. Small. "Fat synthesis in adipose tissue. An examination of stoichiometric constraints by mathematical modelling." Biochemical Journal 238(3): 781-786 (15 September 1986). DOI: 10.1042/bj2380781. [35] J. A. Lerman, D. R. Hyduke, H. Latif, V. A. Portnoy, N. E. Lewis, J. D. Orth, A. C. Schrimpe-Rutledge, R. D. Smith, J. N. Adkins, K. Zengler, B. O. Palsson. "In silico method for modelling metabolism and gene product expression at genome scale." Nature Communications 3, Article 929 (3 July 2012). DOI: 10.1038/ncomms1928. PMID: 22760628. [ME-Models — metabolism + gene expression at genome scale] [36] H. Shishido, H. Hashizume. "Introduction of Fusion Reactors as Transmutation Systems for Minor Actinides and Fission Products." Nuclear Technology (Published online 13 May 2025). DOI: 10.1080/00295450.2025.2472556. [37] P.-F. Verhulst. "Notice sur la loi que la population suit dans son accroissement." Correspondance Mathématique et Physique (publiée par A. Quetelet, Bruxelles) 10: 113-121 (1838). [38] R. A. Fisher. The Genetical Theory of Natural Selection. Oxford University Press, Oxford (1930). [39] M. Granovetter. "Threshold Models of Collective Behavior." American Journal of Sociology 83(6): 1420-1443 (May 1978). DOI: 10.1086/226707. [40] T. Lee. "The Thermodynamic Laws of Information Physics: A Law-by-Law Mathematical Reconstruction from Zeroth to Third Law." Information Physics Series, Paper 17 (2026). DOI: 10.5281/zenodo.19790713 [41] T. Lee. "Fusion Plasma as a Living Information Condensate: A Reduced-Order Survival Inequality for Stable Energy-Extracting Fusion Plasmas." Information Physics Series, Paper 18 (2026). DOI: 10.5281/zenodo.19957672 [42] T. Lee. "The Fire That Thinks: Fusion Information Condensate as the Embodied Substrate of Non-Biological Conscious Systems." Information Physics Series, Paper 19 (2026). DOI: 10.5281/zenodo.19956585 [43] L. V. Boccaccini, F. A. Hernandez, A. Del Nevo, B. Garcinuño, G. Federici, et al. "Predictive modelling of tritium breeding ratio (TBR) in EU DEMO WCLL blankets: OpenMC simulations and analytical insights." Fusion Engineering and Design (2025). [DOI link: https://www.sciencedirect.com/science/article/abs/pii/S0920379625007124] 76 Views 49 Downloads Show more details All versions This version Views Total views 76 76 Downloads Total downloads 49 49 Data volume Total data volume 239.1 MB 239.1 MB More info on how stats are collected.... Versions External resources Indexed in OpenAIRE Communities Keywords and subjects Keywords fusion-fission hybrid metabolic architecture four-margin min-gate AI-Fire tritium agriculture actinide digestion neutron allocation six-layer body anatomy Information Physics Series AI-Fire trilogy fusion plasma nuclear waste transmutation lithium blanket metabolic min-gate fusion information condensate AI embodiment spent nuclear fuel Details DOI DOI Badge DOI 10.5281/zenodo.20078919 Markdown [](https://doi.org/10.5281/zenodo.20078919) reStructuredText .. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.20078919.svg :target: https://doi.org/10.5281/zenodo.20078919 HTML <a href="https://doi.org/10.5281/zenodo.20078919"><img src="https://zenodo.org/badge/DOI/10.5281/zenodo.20078919.svg" alt="DOI"></a> Image URL https://zenodo.org/badge/DOI/10.5281/zenodo.20078919.svg Target URL https://doi.org/10.5281/zenodo.20078919 Resource type Preprint Publisher Zenodo Languages English Rights License Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) This work may be shared and adapted with attribution, but commercial use is prohibited without explicit prior authorization from the author. Read more Citation Export Technical metadata Created May 8, 2026 Modified May 10, 2026 Jump up About About Policies Infrastructure Principles Projects Roadmap Contact Blog Blog Support Help FAQ Developers REST API OAI-PMH Contribute GitHub Donate Funded by Powered by CERN Data Centre & InvenioRDM Status Privacy policy Cookie policy Terms of Use This site uses cookies. Find out more on how we use cookies Accept all cookies Accept only essential cookies

Related documents

• The burning world#63799
• Agentic Economies for Autonomous Scientific Discovery#1106261
• DEEM0001971 — NUCLEAR WASTE PARTNERSHIP LLC — Department of Energy ($2,823,678,827)#604534
• Technosphere#696640
• When Agents Spend Watts: Measuring Performance-Energy Trade-offs in Agentic AI Systems with AgenticBench#322175