arXiv subjects

Xiaoqian M Chen

Publications and source records attributed to Xiaoqian M Chen.

3 recordsLinked to original sources

arXiv2026

Metastable short-range charge order in superconducting CuxTiSe2

In a vast array of materials, including cuprates, transition metal dichalcogenides (TMDs) and rare earth tritellurides, superconductivity is found in the vicinity of short-range charge density wave (CDW) order. The crossover from long-range to short-range charge order often occurs as quenched disorder is introduced, yet it is unclear how this disorder disrupts the CDW. Here, using x-ray photon correlation spectroscopy (XPCS), we investigate the prototypical TMD superconductor CuxTiSe2 and show that disorder induces substantial CDW dynamics. We observe CDW phase fluctuations on a timescale of minutes to hours above the nominal transition temperature while the order parameter amplitude remains finite. These long timescale fluctuations prevent the system from finding the global free energy minimum upon cooling and ultimately traps it in a short-range ordered metastable state. Our findings demonstrate how correlated disorder can give rise to a distinct mechanism of domain formation that may be advantageous to the emergence of superconductivity.

cond-mat.str-el↗

arXiv2026

Probing Non-Equilibrium Grain Boundary Dynamics with XPCS and Domain-Adaptive Machine Learning

Grain-boundary (GB) dynamics control the stability, mechanical, and functional response of nanocrystalline materials, but direct experimental access to their slow non-equilibrium motion has been limited. Here we establish X-ray photon correlation spectroscopy (XPCS), combined with domain-adaptive machine learning, as a quantitative probe of GB dynamics. Temperature- and grain-size-dependent two-time XPCS measurements in nanocrystalline silicon reveal pronounced departures from time-translation invariance, showing that GB relaxation can remain far from equilibrium over experimental timescales. However, direct extraction of quantitative physical information from these high-dimensional, noisy fluctuation maps faces a significant challenge. To overcome this barrier, we develop a semi-supervised learning framework that transfers physical parameter labels from continuum simulations to unlabeled experimental XPCS maps through domain-adaptive representation alignment. This AI-augmented approach enables the extraction of key kinetic parameters, including bulk diffusivity, GB stiffness, and effective GB concentration, directly from experimental XPCS measurements. Our results show how machine learning can transform indirect fluctuation signals into quantitative materials dynamics, providing a general route to study non-equilibrium defect motion in solids.

cond-mat.mtrl-sci↗

arXiv2020

Switchable X-ray Orbital Angular Momentum from an Artificial Spin Ice

Artificial spin ices (ASI) have been widely investigated as magnetic metamaterials with exotic properties governed by their geometries. In parallel, interest in X-ray photon orbital angular momentum (OAM) has been rapidly growing. Here we show that a square ASI with a programmed topological defect, a double edge dislocation, imparts OAM to scattered X-rays. Unlike single dislocations, a double dislocation does not introduce magnetic frustration, and the ASI equilibrates to its antiferromagnetic (AF) ground state. The topological charge of the defect differs with respect to the structural and magnetic order; thus, X-ray diffraction from the ASI produces photons with even and odd OAM quantum numbers at the structural and AF Bragg conditions, respectively. The magnetic transitions of the ASI allow the AF OAM beams to be switched on and off by modest variations of temperature and applied magnetic field. These results demonstrate ASIs can serve as metasurfaces for reconfigurable X-ray optics that could enable selective probes of electronic and magnetic properties.

cond-mat.mes-hall↗