The evolution of machine learning potentials for molecules, reactions and materials

Chemical Society Reviews, Год журнала: 2025, Номер unknown

Опубликована: Янв. 1, 2025

This review offers a comprehensive overview of the development machine learning potentials for molecules, reactions, and materials over past two decades, evolving from traditional models to state-of-the-art.

Язык: Английский

---

Understanding Defects in Amorphous Silicon with Million‐Atom Simulations and Machine Learning

Angewandte Chemie International Edition, Год журнала: 2024, Номер 63(22)

Опубликована: Март 22, 2024

The structure of amorphous silicon (a-Si) is widely thought as a fourfold-connected random network, and yet it defective atoms, with fewer or more than four bonds, that make particularly interesting. Despite many attempts to explain such "dangling-bond" "floating-bond" defects, respectively, unified understanding still missing. Here, we use advanced computational chemistry methods reveal the complex structural energetic landscape defects in a-Si. We study an ultra-large-scale, quantum-accurate model containing million thousands individual allowing reliable defect-related statistics be obtained. combine descriptors machine-learned atomic energies develop classification different types results suggest revision established floating-bond by showing fivefold-bonded atoms a-Si exhibit wide range local environments-analogous fivefold centers coordination chemistry. Furthermore, shown (but not threefold) tend cluster together. Our provides new insights into one most studied solids, has general implications for disordered materials beyond alone.

Язык: Английский

---

Theoretical Study on Ion Diffusion Mechanism in W-Doped K₃SbS₄ as Solid-State Electrolyte for K-Ion Batteries

Inorganic Chemistry, Год журнала: 2024, Номер 63(15), С. 6743 - 6751

Опубликована: Апрель 4, 2024

The development of a solid-state electrolyte (SSE) is crucial for overcoming the side reactions metal potassium anodes and advancing progress K-ion batteries (KIBs). Exploring diffusion mechanism K ion in SSE important deepening our understanding promoting its development. In this study, we conducted static calculations utilized deep potential molecular dynamics (DeepMD) to investigate behavior cubic K3SbS4. original K3SbS4 exhibited poor ionic conductivity, but discovered that introducing heterovalent tungsten doping created vacancies, which significantly reduced activation energy 0.12 eV enhanced conductivity 1.80 × 10–2 S/cm. K-ions primarily occurs through exchange positions with vacancies. This research provides insights into design high conductivity. Furthermore, it highlights effectiveness DeepMD as powerful tool studying SSE.

Язык: Английский

---

Effect of Cation Disorder on Lithium Transport in Halide Superionic Conductors

ACS Energy Letters, Год журнала: 2024, Номер 9(6), С. 2775 - 2781

Опубликована: Май 16, 2024

Li2ZrCl6 (LZC) is a promising solid-state electrolyte due to its affordability, moisture stability, and high ionic conductivity. We computationally investigate the role of cation disorder in LZC effect on Li-ion transport by integrating thermodynamic kinetic modeling. The results demonstrate that fast conductivity requires Li-vacancy disorder, which dependent degree Zr disorder. temperature required form equilibrium precludes any synthesis processes for achieving conductivity, rationalizing why only nonequilibrium methods, such as ball-milling, lead good Our simulations show lowers Li/vacancy order–disorder transition temperature, necessary creating Li diffusivity at room temperature. These insights raise challenge large-scale production these materials potential long-term stability their properties.

Язык: Английский

---

Understanding the role of aliovalent cation substitution on the li-ion diffusion mechanism in Li_6+xP_1−xSi_xS₅Br argyrodites

Materials Advances, Год журнала: 2024, Номер 5(5), С. 1952 - 1959

Опубликована: Янв. 1, 2024

The Si-induced uniform Li distribution enhances intercage diffusion, enabled through the T4 interstitial positions, resulting in increased macroscopic diffusion and ionic conductivity.

Язык: Английский

---

Size dependent lithium-ion conductivity of solid electrolytes in machine learning molecular dynamics simulations

Artificial Intelligence Chemistry, Год журнала: 2024, Номер 2(1), С. 100051 - 100051

Опубликована: Янв. 24, 2024

Solid-state electrolytes are key ingredients in next-generation devices for energy storage and release. Machine learning molecular dynamics (MLMD) has shown great promise studying the diffusivity of mobile ions solid-state electrolytes, with much higher efficiency than conventional ab initio (AIMD). In this work, we combine an efficient embedded atom neural network (EANN) approach uncertainty-driven active algorithm that optimally selects data points from high-temperature AIMD trajectories to construct ML potentials validate strategy a benchmark system, Li3YCl6, which several controversy theoretical results exist. Through systematic MLMD simulations, find typically used small supercell simulations fails predict supersonic transition at critical temperature, leading significant overestimation Li+ conductivity Li3YCl6 room temperature. Fortunately, thanks scalability EANN potential, extended sufficiently large cell does yield notable change temperature-dependence ~420 K lower room-temperature excellent experiment. Interestingly, our all based on semi-local PBE density functional, was argued unable superionic transition. We analyze possible reasons seemingly inconsistent reported literature different potentials. This work paves way simply using generate more reliable low-temperature ionic conductivities electrolytes.

Язык: Английский

---

Theoretical calculations and simulations power the design of inorganic solid-state electrolytes

Nanoscale, Год журнала: 2024, Номер 16(33), С. 15481 - 15501

Опубликована: Янв. 1, 2024

With increasing computational capabilities and ongoing methodological innovations, theoretical calculation simulations will play a more significant role in the design development of high-performance energy storage materials.

Язык: Английский

---

Dynamic Lone Pairs and Fluoride-Ion Disorder in Cubic-BaSnF₄

Journal of the American Chemical Society, Год журнала: 2023, Номер 145(43), С. 23739 - 23754

Опубликована: Окт. 16, 2023

Introducing compositional or structural disorder within crystalline solid electrolytes is a common strategy for increasing their ionic conductivity. (M,Sn)F

Язык: Английский

---

Advances in the application of first principles calculations to phosphate-based NASICON battery materials

Journal of Materials Chemistry A, Год журнала: 2024, Номер unknown

Опубликована: Янв. 1, 2024

NASICON potential unlocked: first-principles calculations guide doping for sodium ion battery advancement.

Язык: Английский

---

Optimizing Ionic Transport in Argyrodites: A Unified View on the Role of Sulfur/Halide Distribution and Local Environments

Journal of Materials Chemistry A, Год журнала: 2024, Номер unknown

Опубликована: Янв. 1, 2024

Understanding diffusion mechanisms in solid electrolytes is crucial for advancing solid-state battery technologies. This study investigates the role of structural disorder Li

Язык: Английский

---