The TELOS Architecture: Theoretical Prediction of Bounded 167 K – 316 K Superconductivity in hBN-Encapsulated, Uniaxially Strained Magic-Angle Trilayer Graphene via Proximity Effect

Revision Update V4: This manuscript has been extensively upgraded to formally introduce the TELOS (Twisted Encapsulated Layered Optimized Strain) Architecture. We have eliminated previous reliance on phenomenological "toy model" parameters by integrating large-scale, first-principles Density Functional Theory (DFT) and Maximally Localized Wannier Function (MLWF) simulations. The computational extraction of 670 unique hopping parameters empirically proves the massive kinetic suppression (tavg=0.111 eV). By feeding this exact parameter into an IBM Qiskit quantum phase sweep, we explicitly plot the crossover into the strongly correlated high-temperature superconducting regime, providing an unbroken, first-principles-to-quantum-tensor computational pipeline. Achieving high-temperature superconductivity at ambient conditions remains one of the preeminent challenges in condensed matter physics. We propose a novel quantum heterostructure, designated the TELOS (Twisted Encapsulated Layered Optimized Strain) Architecture, capable of sustaining a theoretical superconducting critical temperature (Tc) bounded between 167.3 K (unshielded lower-bound) and 315.6 K (macroscopic upper-bound). Our TELOS architecture utilizes Magic-Angle Trilayer Graphene (MATTG) symmetrically encapsulated by monolayer Hexagonal Boron Nitride (hBN) and proximitized by Copper (Cu) thin films. Using the CHGNet Neural Network Potential, we conduct large-scale (~4,100 atom) atomistic simulations to prove structural and thermal stability up to 350 K. To maximize the Van Hove singularity, we implement a dynamic uniaxial strain loop, identifying a catastrophic structural fracture limit at 1.40% and optimizing the lattice at a 1.39% "Redline" strain. Furthermore, we extract the exact first-principles tight-binding Hamiltonian, proving a massive kinetic hopping suppression (tavg=0.111 eV) that forces the lattice into the strongly correlated regime. We then employ IBM Qiskit Aer to model the Attractive Hubbard Model using these exact parameters, proving a 98.74% Cooper pair trapping efficiency. Open Quantum System modeling of thermal decoherence and heat transport establishes the 167.3 K baseline and validates the thermal shielding properties of the hBN gaskets. We submit these empirical proxy simulations as an urgent call-to-action for experimental verification via Molecular Beam Epitaxy (MBE).

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-08-20
DOI
https://doi.org/10.5281/zenodo.22021039
Primary Topic
Machine Learning in Materials Science
Type
preprint
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preprint

The TELOS Architecture: Theoretical Prediction of Bounded 167 K – 316 K Superconductivity in hBN-Encapsulated, Uniaxially Strained Magic-Angle Trilayer Graphene via Proximity Effect

Nathan Rivera
Zenodo (CERN European Organization for Nuclear Research)
Machine Learning in Materials Science
preprint

The TELOS Architecture: Theoretical Prediction of Bounded 167 K – 316 K Superconductivity in hBN-Encapsulated, Uniaxially Strained Magic-Angle Trilayer Graphene via Proximity Effect

Nathan Rivera
preprint en

Abstract

Revision Update V4: This manuscript has been extensively upgraded to formally introduce the TELOS (Twisted Encapsulated Layered Optimized Strain) Architecture. We have eliminated previous reliance on phenomenological "toy model" parameters by integrating large-scale, first-principles Density Functional Theory (DFT) and Maximally Localized Wannier Function (MLWF) simulations. The computational extraction of 670 unique hopping parameters empirically proves the massive kinetic suppression (tavg=0.111 eV). By feeding this exact parameter into an IBM Qiskit quantum phase sweep, we explicitly plot the crossover into the strongly correlated high-temperature superconducting regime, providing an unbroken, first-principles-to-quantum-tensor computational pipeline. Achieving high-temperature superconductivity at ambient conditions remains one of the preeminent challenges in condensed matter physics. We propose a novel quantum heterostructure, designated the TELOS (Twisted Encapsulated Layered Optimized Strain) Architecture, capable of sustaining a theoretical superconducting critical temperature (Tc) bounded between 167.3 K (unshielded lower-bound) and 315.6 K (macroscopic upper-bound). Our TELOS architecture utilizes Magic-Angle Trilayer Graphene (MATTG) symmetrically encapsulated by monolayer Hexagonal Boron Nitride (hBN) and proximitized by Copper (Cu) thin films. Using the CHGNet Neural Network Potential, we conduct large-scale (~4,100 atom) atomistic simulations to prove structural and thermal stability up to 350 K. To maximize the Van Hove singularity, we implement a dynamic uniaxial strain loop, identifying a catastrophic structural fracture limit at 1.40% and optimizing the lattice at a 1.39% "Redline" strain. Furthermore, we extract the exact first-principles tight-binding Hamiltonian, proving a massive kinetic hopping suppression (tavg=0.111 eV) that forces the lattice into the strongly correlated regime. We then employ IBM Qiskit Aer to model the Attractive Hubbard Model using these exact parameters, proving a 98.74% Cooper pair trapping efficiency. Open Quantum System modeling of thermal decoherence and heat transport establishes the 167.3 K baseline and validates the thermal shielding properties of the hBN gaskets. We submit these empirical proxy simulations as an urgent call-to-action for experimental verification via Molecular Beam Epitaxy (MBE).

Zenodo (CERN European Organization for Nuclear Research)
Purdue Global (US)
Machine Learning in Materials Science
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