arXiv subjects

En Ma

Publications and source records attributed to En Ma.

11 recordsLinked to original sources

arXiv2026

Multiscale simulations guided advances for all-optical phase-change waveguides

Photonic computing using chalcogenide phase-change materials (PCMs) is under active development for energy-efficient artificial intelligence (AI) applications. A key requirement is to enable as many optically programmable levels per device as possible, while maintaining relatively low optical loss. In this work, we carry out multiscale simulations using density functional theory and finite-difference time-domain methods, proposing a "the shorter the better" strategy to optimize the performance of Sb2Te photonic waveguide devices. Our subsequent experimental characterizations of Sb2Te thin films and optical device measurements fully verify our theoretical predictions. In particular, we reveal the unconventional optical properties of metastable crystalline Sb2Te, and utilize these features for device design, yielding a simultaneous improvement in both the programming window and the optical loss. Overall, an optical programming precision exceeding 7-bit is achieved using a single waveguide cell, setting a new record for all-optical phase-change memory devices. Our work serves as a compelling example of computational material design, which demonstrates the predictive power of multiscale simulations in guiding the design of phase-change photonic devices for enhanced performance.

cond-mat.mtrl-sci↗

arXiv2025

Defining structural gradient hardening through Type II back stress for heterostructured materials

The recently proposed term "heterostructured (HS) materials" serves as an umbrella classification encompassing a wide range of materials that hold great promise for enhanced mechanical properties. Most HS materials exhibit back-stress strengthening, as is typical for all plastically non-homogeneous materials. To better embody the distinctiveness of materials crafted via innovative heterostructuring, here we introduce the concept of "structural gradient hardening" (SGH), which captures an essential feature of HS materials and complements traditional strengthening mechanisms. SGH refers to the extra strengthening that arises from a characteristic gradient structure introduced by heterostructuring, beyond what is predicted by the rule of mixtures. This distinction is useful, as the overall back stress can in fact be partitioned into Type I and Type II components, with the latter specifically quantifying the extra hardening originating from the structural and strain gradients established by heterostructuring, as articulated in this Viewpoint article.

cond-mat.mtrl-sci↗

arXiv2025

Amorphous phase-change memory alloy with no resistance drift

Spontaneous structural relaxation is intrinsic to glassy materials due to their metastable nature. For phase-change materials (PCMs), the resultant temporal change in electrical resistance seriously hamper in-memory computing (IMC) applications. Here, we report an ab-initio-calculation-informed design of amorphous PCM composed of robust "molecule-like" motifs with minimal Peierls distortion, depriving the amorphous alloy of structural ingredients that would gradually evolve upon aging to entail resistance drift. We demonstrate amorphous CrTe3 thin films that display practically no resistance drift at any working temperature from -200 to 165 degree C. We achieve multilevel programming of CrTe3 through both step-wise crystallization and step-wise amorphization using a hybrid opto-electronic device at various temperatures. Moreover, the application potential of CrTe3 in neuromorphic computing is testified by its incorporation in a vehicle with automatic path-tracking function. Our work opens a new avenue to achieving IMC-requisite properties via judicious design of the composition and atomic-level structure of disordered PCM alloys.

cond-mat.mtrl-sci↗

arXiv2025

Role of seed layer in growing atomically flat TiTe2/Sb2Te3 heterostructure thin films at the wafer scale

Chalcogenide phase-change materials (PCMs) are a leading candidate for advanced memory and computing applications. Epitaxial-like growth of chalcogenide thin films at the wafer scale is important to guarantee the homogeneity of the thin film but is challenging with magnetron sputtering, particularly for the growth of phase-change heterostructure (PCH), such as TiTe2/Sb2Te3. In this work, we report how to obtain highly textured TiTe2/Sb2Te3 heterostructure thin films with atomically sharp interfaces on standard silicon substrates. By combining atomic-scale characterization and ab initio simulations, we reveal the critical role of the Sb2Te3 seed layer in forming a continuous Si-Sb-Te mixed transition layer, which provides a wafer-scale flat surface for the subsequent epitaxial-like growth of TiTe2/Sb2Te3 thin film. By gradually reducing the thickness of the seed layer, we determine its critical limit to be ~2 nm. Non-negligible in-plane tensile strain was observed in the TiTe2 slabs due to the lattice mismatch with the adjacent Sb2Te3 ones, suggesting that the chemical interaction across the structural gaps in the heterostructure is stronger than a pure van der Waals interaction. Finally, we outline the potential choices of chalcogenides for atomically flat seed layers on standard silicon substrates, which can be used for wafer-scale synthesis of other high-quality PCM or PCH thin films.

cond-mat.mtrl-sci↗

arXiv2023

Multiscale simulations of growth-dominated Sb$_2$Te phase-change material for non-volatile photonic applications

Chalcogenide phase-change materials (PCMs) are widely applied in electronic and photonic applications, such as non-volatile memory and neuro-inspired computing. Doped Sb$_2$Te alloys are now gaining increasing attention for on-chip photonic applications, due to their growth-driven crystallization features. However, it remains unknown whether Sb$_2$Te also forms a metastable crystalline phase upon nanoseconds crystallization in devices, similar to the case of nucleation-driven Ge-Sb-Te alloys. Here, we carry out ab initio simulations to understand the changes in optical properties of amorphous Sb$_2$Te upon crystallization and post annealing. During the continuous transformation process, changes in the dielectric function are highly wavelength-dependent from the visible-light range towards the telecommunication band. Our finite-difference time-domain simulations based on the ab initio input reveal key differences in device output for color display and photonic memory applications upon tellurium ordering. Our work serves as an example of how multiscale simulations of materials can guide practical photonic phase-change applications.

cond-mat.mtrl-sci↗

arXiv2023

Spin glass behavior in amorphous Cr2Ge2Te6 phase-change alloy

The layered crystal structure of Cr2Ge2Te6 shows ferromagnetic ordering at the two-dimensional limit, which holds promise for spintronic applications. However, external voltage pulses can trigger amorphization of the material in nanoscale electronic devices, and it is unclear whether the loss of structural ordering leads to a change in magnetic properties. Here, we demonstrate that Cr2Ge2Te6 preserves the spin-polarized nature in the amorphous phase, but undergoes a magnetic transition to a spin glass state below 20 K. Quantum-mechanical computations reveal the microscopic origin of this transition in spin configuration: it is due to strong distortions of the Cr-Te-Cr bonds, connecting chromium-centered octahedra, and to the overall increase in disorder upon amorphization. The tunable magnetic properties of Cr2Ge2Te6 could be exploited for multifunctional, magnetic phase-change devices that switch between crystalline and amorphous states.

cond-mat.mtrl-sci↗

arXiv2022

Unlocking device-scale atomistic modelling of phase-change memory materials

Quantum-accurate computer simulations play a central role in understanding phase-change materials (PCMs) for advanced memory technologies. However, direct quantum-mechanical simulations are necessarily limited to simplified models, containing no more than a few hundred or a thousand atoms. Machine learning (ML) based potential models that are "trained" on quantum-mechanical data are an emerging alternative approach, currently evolving from highly specialised to more widely applied simulation tools. Here we show that a universal, compositionally flexible ML model can describe a wide range of flagship Ge-Sb-Te PCMs under real device conditions, including non-isothermal heating and chemical disorder which are relevant for memory applications. The speed of the ML model enables atomistic simulations of multiple thermal cycles and delicate operations for neuro-inspired computing, namely, cumulative SET and iterative RESET. A device-scale capability demonstration (40 x 20 x 20 nm3) shows that the new ML potential can directly describe technologically relevant processes in PCM-based memory products. In a wider context, our work demonstrates how ML-driven materials simulations are now entering a stage where they can guide architecture design for high-performance electronic devices.

cond-mat.mtrl-sci↗

arXiv2022

Designing inorganic semiconductors with cold-rolling processability

While metals can be readily processed and reshaped by cold rolling, most bulk inorganic semiconductors are brittle materials that tend to fracture when plastically deformed. Manufacturing thin sheets and foils of inorganic semiconductors is therefore a bottleneck problem, severely restricting their use in flexible electronics applications. It was recently reported that a few single-crystalline two-dimensional van der Waals (vdW) semiconductors, such as InSe, are deformable under compressive stress. Here we demonstrate that intralayer fracture toughness can be tailored via compositional design to make inorganic semiconductors processable by cold rolling. We report systematic ab initio calculations covering a range of van der Waals semiconductors homologous to InSe, leading to material-property maps that forecast trends in both the susceptibility to interlayer slip and the intralayer fracture toughness against cracking. GaSe has been predicted, and experimentally confirmed, to be practically amenable to being rolled to large (three quarters) thickness reduction and length extension by a factor of three. Our findings open a new realm of possibility for alloy selection and design towards processing-friendly group-III chalcogenides for flexible electronic and thermoelectric applications.

cond-mat.mtrl-sci↗

arXiv2022

In situ characterization of vacancy ordering in Ge-Sb-Te phase-change memory alloys

Tailoring the degree of structural disorder in Ge-Sb-Te alloys is important for the development of non-volatile phase-change memory and neuro-inspired computing. Upon crystallization from the amorphous phase, these alloys form a cubic rocksalt-like structure with a high content of intrinsic vacancies. Further thermal annealing results in a gradual structural transition towards a layered structure and an insulator-to-metal transition. In this work, we elucidate the atomic-level details of the structural transition in crystalline GeSb2Te4 by in situ high-resolution transmission electron microscopy (HRTEM) experiments and ab initio density functional theory (DFT) calculations, providing a comprehensive real-time and real-space view of the vacancy ordering process. We also discuss the impact of vacancy ordering on altering the electronic and optical properties of GeSb2Te4, which is relevant to multilevel storage applications. The phase evolution paths in Ge-Sb-Te alloys are illustrated using a summary diagram, which serves as a guide for designing phase-change memory devices.

cond-mat.mtrl-sci↗

arXiv2022

Molecular-scale Integration of Multi-modal Sensing and Neuromorphic Computing with Organic Electrochemical Transistors

Abstract: Bionic learning with fused sensing, memory and processing functions outperforms artificial neural networks running on silicon chips in terms of efficiency and footprint. However, digital hardware implementation of bionic learning suffers from device heterogeneity in sensors and processing cores, which incurs large hardware, energy and time overheads. Here, we present a universal solution to simultaneously perform multi-modal sensing, memory and processing using organic electrochemical transistors with designed architecture and tailored channel morphology, selective ion injection into the crystalline/amorphous regions. The resultant device work as either a volatile receptor that shows multi-modal sensing, or a non-volatile synapse that features record-high 10-bit analog states, low switching stochasticity and good retention without the integration of any extra devices. Homogeneous integration of such devices enables bionic learning functions such as conditioned reflex and real-time cardiac disease diagnose via reservoir computing, illustrating the promise for future smart edge health informatics.

cs.ET↗

arXiv2021

Radiation-tolerant high-entropy alloys via interstitial-solute-induced chemical heterogeneities

High-entropy alloys (HEAs) composed of multiple principal elements have been shown to offer improved radiation resistance over their elemental or dilute-solution counterparts. Using NiCoFeCrMn HEA as a model, here we introduce carbon and nitrogen interstitial alloying elements to impart chemical heterogeneities in the form of the local chemical order (LCO) and associated compositional variations. Density functional theory simulations predict chemical short-range order (CSRO) (nearest neighbors and the next couple of atomic shells) surrounding C and N, due to the chemical affinity of C with (Co, Fe) and N with (Cr, Mn). Atomic-resolution chemical mapping of the elemental distribution confirms marked compositional variations well beyond statistical fluctuations. Ni+ irradiation experiments at elevated temperatures demonstrate a remarkable reduction in void swelling by at least one order of magnitude compared to the base HEA without C and N alloying. The underlying mechanism is that the interstitial-solute-induced chemical heterogeneities roughen the lattice as well as the energy landscape, impeding the movements of, and constraining the path lanes for, the normally fast-moving self-interstitials and their clusters. The irradiation-produced interstitials and vacancies therefore recombine more readily, delaying void formation. Our findings thus open a promising avenue towards highly radiation-tolerant alloys.

cond-mat.mtrl-sci↗