arXiv subjects

Linggang Zhu

Publications and source records attributed to Linggang Zhu.

7 recordsLinked to original sources

arXiv2026

ALKEMIE Agent: an autonomous platform for computational materials design

Despite the powerful multi-scale modeling methods and high-throughput infrastructures established in the materials community, real material computation workflows remain fragmented and heavily manual, requiring researchers to constantly bridge software tools, data analysis, and intermediate decisions. This growing gap between methodological capability and practical execution highlights the need for a new kind of autonomous computational framework, one that can coordinate tools, knowledge, and workflows in a more unified and adaptive way. Here, we introduce ALKEMIE Agent, an agentic platform in which retrieval-augmented generation, a materials-computation knowledge base, registered skills, database-supported provenance, AI-assisted structure modeling, bounded task execution, tool-calling iteration, and error-diagnostic assistance are integrated within a traceable control loop. The capabilities of ALKEMIE Agent are demonstrated through applications including materials recommendation, structure modeling, phonon calculations, machine-learned interatomic potential training, LAMMPS simulations, Ab Initio Monte Carlo (AIMC) sampling, and active-learning-based materials screening. Finally, we outline the future directions and challenges for the development of agentic platforms for computational materials design.

cond-mat.mtrl-sci↗

arXiv2026

AI2Pot: A scalable and unified framework for machine-learning interatomic potential development and large-scale molecular dynamic simulations

Machine-learning interatomic potentials (MLIPs) bridge the accuracy of first-principles calculations and the efficiency required for large-scale molecular dynamics (MD) simulations. However, existing MLIP software remains fragmented across different model architectures, making it difficult to establish unified workflows that support flexible model development, efficient training, and scalable MD deployment. Here, we present AI2Pot, a scalable and unified MLIP framework that seamlessly integrates model training, evaluation, and large-scale MD simulations with PyTorch-compatible ecosystem. Instead of relying on generic automatic differentiation for expensive atomistic operators, AI2Pot re-engineers the core computations of Moment tensor potential (MTP) and Neuroevolution potential (NEP) for both training and inference using hand-crafted C++/CUDA code. These specialized operators constitute a unified computational backend shared by training and inference, improving training-inference consistency and reducing memory usage by avoiding large intermediate caches. As a result, AI2Pot enables fast inference for large-scale atomic systems containing millions of atoms on a single GPU, while retaining the flexibility of PyTorch for model construction, training, and evaluation. Trained models can be deployed in ASE and LAMMPS for MD simulations. Furthermore, AI2Pot provides a companion command-line toolkit (AI2Pot-cli) and Python APIs to facilitate practical MLIP workflows. By unifying high-performance atomistic computing with modern machine-learning ecosystems, AI2Pot offers an user-friendly end-to-end framework for the developing, training, and deploying MLIPs for large scale MD.

cond-mat.mtrl-sci↗

arXiv2026

Hidden ordered compound-layer and its tailoring of the electronic/optical property in Ge2Sb2SexTe5-x alloys

Ge2Sb2SexTe5-x (GSST) alloys represent an emerging class of phase-change materials for integrated photonics. However, the microscopic origins underlying their superior performance compared to the parent compound Ge2Sb2Te5 remain elusive. By using atomic simulations, this work elucidates that the thermal stability and low optical loss of GSST are fundamentally governed by the formation of an in-layer compound-like structure with SeTe2 or Se2Te stoichiometry depending on the Se content, contrasting to the previously believed pure-element-layered model where Se and Te atoms occupy separate layers inside GSST. The newly identified compound-layered structures maintaining stability at temperature above 370 K, yield an enlarged bandgap, weakened antibonding character, and more importantly, a moderate refractive index as well as decreased extinction coefficient which align better with the experiment compared to the previously believed model. The present findings not only help bridge the long-standing theory-experiment gap regarding the optical properties of GSST by redefining its atomic structure, but also establish local chemical ordering as a critical materials design principle for high-performance photonics.

cond-mat.mtrl-sci↗

arXiv2017

Origin of the abnormal diffusion of transition metal in rutile

Diffusion of dopants in rutile is the fundamental process that determines the performance of many devices in which rutile is used. The diffusion behavior is known to be highly sample-dependent, but the reasons for this are less well understood. Here, rutile is studied by using first-principles calculations, in order to unravel the microscopic origins of the diverse diffusion behaviors for different doping elements. Anomalous diffusion behavior in the open channel along [001] direction is found: larger atoms include Sc and Zr have lower energy barrier for diffusion via interstitial mechanism, apparently contradicting their known slow diffusion rate. To resolve this, we present an alternate model for the overall diffusion rate of the large-size dopants in rutile, showing that parallel to the [001] channel, it is limited by the formation of the interstitial states, whereas in the direction perpendicular to [001], it proceeds via a kick-out mechanism. By contrast, Co and Ni, prefer to stay in the interstitial site of rutile, and have conventional diffusion with a very small migration barrier in the [001] channel. This leads to highly anisotropic and fast diffusion. The diffusion mechanisms found in the present study can explain the diffusion data measured by experiments, and these findings provide novel understanding for the classic diffusion topic.

cond-mat.mtrl-sci↗

arXiv2016

Insight into the Role of Oxygen in Phase-Change Material GeTe

Oxygen is widely used to tune the performance of chalcogenide phase-change materials in the usage of phase-Change random access memory (PCRAM) which is considered as the most promising next-generation non-volatile memory. However, the microscopic role of oxygen in the write-erase process, i.e., the reversible phase transition between crystalline and amorphous state of phase-change materials is not clear yet. Using oxygen doped GeTe as an example, this work unravels the role of oxygen at the atomic scale by means of ab initio total energy calculations and ab initio molecular dynamics simulations. Our main finding is that after the amorphization and the subsequent re-crystallization process simulated by ab initio molecular dynamics, oxygen will drag one Ge atom out of its lattice site and both atoms stay in the interstitial region near the Te vacancy that was originally occupied by the oxygen, forming a "dumbbell-like" defect (O-VTe-Ge), which is in sharp contrast to the results of ab initio total energy calculations at 0 K showing that the oxygen prefers to substitute Te in crystalline GeTe. This specific defect configuration is found to be responsible for the slower crystallization speed and hence the improved data retention of oxygen doped GeTe as reported in recent experimental work. Moreover, we find that the oxygen will increase the effective mass of the carrier and thus increases the resistivity of GeTe. Our results unravel the microscopic mechanism of the oxygen-doping optimization of phase-change material GeTe, and the present reported mechanism can be applied to other oxygen doped ternary chalcogenide phase-change materials.

cond-mat.mtrl-sci↗

arXiv2015

Realization of a reversible switching in TaO2 polymorphs via Peierls distortion for resistance random access memory

Transition-metal-oxide based resistance random access memory is a promising candidate for next-generation universal non-volatile memories. Searching and designing appropriate new materials used in the memories becomes an urgent task. Here, a new structure with the TaO2 formula was predicted using evolutionary algorithms in combination with first-principles calculations. This new structure having a triclinic symmetry (T-TaO2) is both energetically and dynamically more favorable than the commonly believed rutile structure (R-TaO2). Our hybrid functional calculations show that T-TaO2 is a semiconductor with a band gap of 1.0 eV, while R-TaO2 is a metallic conductor. This large difference in electrical property makes TaO2 a potential candidate for resistance random access memory (RRAM). Furthermore, we have shown that T-TaO2 is actually a Peierls distorted R-TaO2 phase and the transition between these two structures is via a directional displacement of Ta atoms. The energy barrier for the reversible phase transition from R-TaO2 to T-TaO2 is 0.19 eV/atom and the other way around is 0.23 eV/atom, suggesting low power consumption for the resistance switch. The present findings provide a new mechanism for the resistance switch and will also stimulate experimental work to fabricate tantalum oxides based RRAM.

cond-mat.mtrl-sci↗

arXiv2012

Binding of an oxide layer to a metal: the case of Ti(10-10)/TiO2(100)

We study the chemical nature of the bonding of an oxide layer to the parent metal. In order to disentangle chemical effects from strain/misfit, Ti(10$\bar{1}$0)/TiO$_{2}$(100) interface has been chosen. We use the density functional pseudopotential method which gives good agreement with experiment for known properties of bulk and surface Ti and TiO$_2$. Two geometries, a film-like model (with free surface in the structure) and a bulk-like model (with no free surface in the structure) are used to simulate the interface, in each case with different terminations of Ti and TiO$_2$. For the single-oxygen interfaces, the interface energy obtained using these two models agree with each other; however for the double-oxygen ones, the relative stability is quite different. The disturbance to the electronic structure is confined within a few atomic layers of the interface. The interfacial bonding is mainly ionic, and surprisingly there is more charge transfer from Ti to O in the interface than in the bulk. In consequence the Ti/TiO$_2$ interface has stronger binding than the bulk of either material. This helps to explain why the oxide forms a stable, protective layer on Ti and Ti alloys.

cond-mat.mtrl-sci↗