Sublimation–Vapor Transport–Redeposition 3D Generation: A Physics-Inspired Framework for Constructing Three-Dimensional Geometry Through Phase-Transition Dynamics
Abstract
Most three-dimensional generative methods construct geometry by sampling or transforming learned representations, including voxel grids, point clouds, implicit fields, and collections of Gaussian primitives. This paper proposes Sublimation–Vapor Transport–Redeposition 3D Generation (SVR-3D), a physics-inspired framework in which three-dimensional structures emerge through a simulated sequence of solid-material removal, vapor-phase transport, nucleation, and redeposition. Instead of treating the final geometry as the only generative state, SVR-3D explicitly represents the evolving distribution of source material, mobile vapor, nucleation sites, and deposited solid matter. A coupled model combines solid-phase evolution, vapor concentration dynamics, transport, local supersaturation, stochastic nucleation, anisotropic deposition, and material conservation. A geometry decoder converts the resulting solid-phase field into a mesh, point cloud, or radiance-compatible representation. The framework supports conditional generation through boundary conditions, source geometry, temperature fields, transport fields, and deposition parameters. Unlike conventional geometry-first generation, its principal design objective is to make phase-transition dynamics the organizing mechanism of the generation process. This paper establishes a mathematical formulation, proposes a numerical implementation, and defines an experimental protocol for evaluating geometric diversity, physical consistency, controllability, and computational cost. SVR-3D is presented as a research hypothesis rather than an experimentally validated model. Its novelty and practical advantages remain to be established through comparisons with existing deposition simulations, phase-field methods, procedural geometry systems, and learned 3D generative models.
Related
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BibTeX
@misc{zhang2026sublimationvapor,
title = {{Sublimation–Vapor Transport–Redeposition 3D Generation: A Physics-Inspired Framework for Constructing Three-Dimensional Geometry Through Phase-Transition Dynamics}},
author = {Jincheng Zhang},
howpublished = {Zenodo},
year = {2026},
month = oct,
doi = {10.5281/zenodo.23636121},
url = {https://zenodo.org/records/23636121},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Sublimation–Vapor Transport–Redeposition 3D Generation: A Physics-Inspired Framework for Constructing Three-Dimensional Geometry Through Phase-Transition Dynamics
AU - Jincheng Zhang
PY - 2026
DA - 2026/10/25
PB - Zenodo
DO - 10.5281/zenodo.23636121
UR - https://zenodo.org/records/23636121
AB - Most three-dimensional generative methods construct geometry by sampling or transforming learned representations, including voxel grids, point clouds, implicit fields, and collections of Gaussian primitives. This paper proposes Sublimation–Vapor Transport–Redeposition 3D Generation (SVR-3D), a physics-inspired framework in which three-dimensional structures emerge through a simulated sequence of solid-material removal, vapor-phase transport, nucleation, and redeposition. Instead of treating the final geometry as the only generative state, SVR-3D explicitly represents the evolving distribution of source material, mobile vapor, nucleation sites, and deposited solid matter. A coupled model combines solid-phase evolution, vapor concentration dynamics, transport, local supersaturation, stochastic nucleation, anisotropic deposition, and material conservation. A geometry decoder converts the resulting solid-phase field into a mesh, point cloud, or radiance-compatible representation. The framework supports conditional generation through boundary conditions, source geometry, temperature fields, transport fields, and deposition parameters. Unlike conventional geometry-first generation, its principal design objective is to make phase-transition dynamics the organizing mechanism of the generation process. This paper establishes a mathematical formulation, proposes a numerical implementation, and defines an experimental protocol for evaluating geometric diversity, physical consistency, controllability, and computational cost. SVR-3D is presented as a research hypothesis rather than an experimentally validated model. Its novelty and practical advantages remain to be established through comparisons with existing deposition simulations, phase-field methods, procedural geometry systems, and learned 3D generative models.
ER -