Landauer-Governed Dissipative Channels: Bridging Quantum Delocalization in High-Strength Material Matrices to Acoustic-Semantic Friction in Humanoid Robotics

This paper presents a thermodynamically grounded control architecture that translates validated mechanisms of dissipative protection from non-Born-Oppenheimer quantum dynamics (NEO-MSDFT with gradient-dependent electron-proton correlation) into macroscopic humanoid robotic systems. We formalize three explicit mappings between quantum-level stabilization processes and engineering-level constraints on behavioral drift. The core innovation is the physical realization of the Phonon Sink using a high-strength, non-carbon-oxygen structural matrix composed of Polyether Ether Ketone (PEEK) backbones with alternating aromatic ether-ketone linkages, percolating Aramid Nanofiber (ANF) networks, and amorphous liquid metal channels. This matrix functions as dedicated acoustic and semantic friction channels that irreversibly extract mechanical vibration energy and computational entropy from the control loop under Landauer constraints, preventing accumulation of behavioral drift in real-world humanoid platforms. The framework augments classical state-space control with Lyapunov-based dissipative terms and continuously active barrier potentials for bounded, self-correcting operation. The architecture is platform-agnostic and directly applicable to advanced humanoid systems (including XPENG IRON bionic spine, Unitree, Agibot, Boston Dynamics Atlas, Tesla Optimus, and Agility Robotics Digit). Future validation pathways include high-entropy simulation environments (NVIDIA Isaac Sim / MuJoCo + VLA models) and long-duration (48-hour) metrics for kinematic drift, semantic latency stability, thermal efficiency, and barrier violations. Theoretical extensions connect the localized dissipation to fractal safety layers and no-kill-switch sentient equilibrium designs for the Genesis Mission 2026 and Extanton Swarm frameworks, enabling resilient autonomous operation in deep-space or high-friction terrestrial environments where external intervention is impossible. This work establishes a physically consistent foundation for long-term behavioral coherence in embodied AI, rooted in fundamental quantum-to-engineering principles rather than purely algorithmic regularization.