Searcharxiv⌕ Search
Home/Archive/arXiv

arXiv · 2610.03547

Symmetry Engineering Enables Deterministic Ensemble Polarization Control in Hexagonal Boron Nitride

Aqiq Ishraq·Eric Herrmann·Pragya Agnihotri·Alexander Hutchinson·Ramiro M. dos Santos·Shahidul Asif·Lottie Murray·Abhijith Puthiya Veettil·Luke Stockl·Muhammad Hassan Shaikh·Collin Maurtua·Kenji Watanabe·Takashi Taniguchi·Matthew Doty·Cyrus E. Dreyer·Anderson Janotti·Xi Wang·Chitraleema Chakraborty
View original source ↗Read source document ↗Export metadata ↓

Abstract

Optical polarization is a key degree of freedom in quantum photonic and sensing technologies, enabling efficient light--matter coupling and directional emission. However, in defect ensemble-based quantum systems, orientational averaging across many defects suppresses optical anisotropy and eliminates a deterministic polarization axis. Here, symmetry engineering is introduced as a strategy to restore collective optical anisotropy in negatively charged boron vacancy (V_B^-) ensembles hosted in hexagonal boron nitride (h-BN). By imposing anisotropic in-plane tensile strain through lithographically defined nano-ridge arrays, in-plane symmetry is broken and the ensemble emission dipole is aligned with the ridge-defined strain symmetry axis. Polarization-resolved photoluminescence reveals that the polarization visibility scales with the magnitude of strain anisotropy, while the emission orientation rigidly follows the engineered symmetry axis across devices with varying strain direction. This deterministic alignment is independent of crystal orientation, establishing the optical foundation for polarization-defined ensemble spin readout and programmable photonic integration in two-dimensional quantum materials

Explore related subjects

cond-mat.mtrl-sci

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Aqiq Ishraq, Eric Herrmann, Pragya Agnihotri, Alexander Hutchinson, Ramiro M. dos Santos, Shahidul Asif, Lottie Murray, Abhijith Puthiya Veettil, Luke Stockl, Muhammad Hassan Shaikh, Collin Maurtua, Kenji Watanabe, Takashi Taniguchi, Matthew Doty, Cyrus E. Dreyer, Anderson Janotti, Xi Wang, Chitraleema Chakraborty. 2026-10-02. Symmetry Engineering Enables Deterministic Ensemble Polarization Control in Hexagonal Boron Nitride. https://arxiv.org/abs/2610.03547

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

arXiv2026

Coupled reaction and diffusion governing interface evolution in solid-state batteries

Understanding and controlling the atomistic-level reactions governing the formation of the solid-electrolyte interphase (SEI) is crucial for the viability of next-generation solid state batteries. However, challenges persist due to difficulties in experimentally characterizing buried interfaces and limits in simulation speed and accuracy. We conduct large-scale explicit reactive simulations with quantum accuracy for a symmetric battery cell, {\symcell}, enabled by active learning and deep equivariant neural network interatomic potentials. To automatically characterize the coupled reactions and interdiffusion at the interface, we formulate and use unsupervised classification techniques based on clustering in the space of local atomic environments. Our analysis reveals the formation of a previously unreported crystalline disordered phase, Li$_2$S$_{0.72}$P$_{0.14}$Cl$_{0.14}$, in the SEI, that evaded previous predictions based purely on thermodynamics, underscoring the importance of explicit modeling of full reaction and transport kinetics. Our simulations agree with and explain experimental observations of the SEI formations and elucidate the Li creep mechanisms, critical to dendrite initiation, characterized by significant Li motion along the interface. Our approach is to crease a digital twin from first principles, without adjustable parameters fitted to experiment. As such, it offers capabilities to gain insights into atomistic dynamics governing complex heterogeneous processes in solid-state synthesis and electrochemistry.

cond-mat.mtrl-sci↗
arXiv2026

Amorphization-Mediated Si-I to Si-V Phase Transition and Reversible Amorphous-Si-V Phase Memory in Silicon Nanoparticles

An experiment has shown that ~10 nm Si nanoparticles undergo a Si-I (diamond cubic) to Si-V (simple hexagonal) phase transition under compression, in contrast to the Si-I to Si-II (tetragonal) transition observed in bulk silicon. However, the atomistic mechanism underlying this size-dependent transition pathway remains unclear. Here, we employ molecular dynamics simulations with a machine learning interatomic potential to reveal a stress triaxiality driven, two-step Si-I to Si-V transition pathway in a spherical Si nanoparticle subjected to an idealized triaxial contact loading model. An intermediate amorphous phase nucleates at the nanoparticle surface and propagates inward around the Si-I core in regions of low stress triaxiality dominated by shear. Within this amorphous shell, Si-V recrystallizes at locations with elevated stress triaxiality and hydrostatic pressure. Upon unloading, the Si-V structure transforms into an amorphous state. A subsequent loading-unloading cycle applied to this amorphous nanoparticle reveals a reversible amorphous-to-Si-V transformation, demonstrating a nanoscale phase-memory effect.

cond-mat.mtrl-sci↗
arXiv2026

Reduced-order topology optimization of defect spectra in phononic crystals

Defect modes localize vibrations within phononic-crystal bandgaps. Prescribing their frequencies alone does not ensure separation from competing modes. We use frequency-dependent selection weights to combine attraction of target-adjacent modes with repulsion of competing in-gap modes. Only the central defect cell is optimized within a previously designed, fixed host bandgap. Cell-level Craig--Bampton reduction retains physical interface coordinates, allowing the host contribution to be assembled once while the defect basis and matrices are updated. Across three numerical cases, the reduced-order method accelerates defect optimization by approximately 13--20 times. A comparison with attraction-only optimization shows that the combined objective moves competing modes away from the target and increases the minimum target-to-non-target frequency separation. Full-order reanalysis shows that the optimized modes remain close to the prescribed frequencies and localized around the defect. A finite-array calculation shows enhanced response near the target relative to the defect-free host under the prescribed loading.

cond-mat.mtrl-sci↗