Machine Learning-Assisted Accelerated Research of Energy Storage Properties of BaTiO3–BiMeO3 Ceramics DOI
Jian Liu,

Peifeng Xiong,

Changjiao Li

и другие.

ACS Sustainable Chemistry & Engineering, Год журнала: 2025, Номер unknown

Опубликована: Фев. 16, 2025

Язык: Английский

Dual-Anion Strategy Induces Dual Enhancement Toward Ultrashort Phase-Matching Wavelength in Deep-UV Transparent d0 Transition Metal Oxyfluorides DOI

Dongdong Chu,

Kewang Zhang, Congwei Xie

и другие.

ACS Materials Letters, Год журнала: 2024, Номер 6(4), С. 1094 - 1102

Опубликована: Фев. 23, 2024

The d0 transition metal oxides are the most commonly used nonlinear optical (NLO) materials in visible light region; however, their limited band gaps seriously hinder application ultraviolet (UV) and deep-ultraviolet (DUV) regions. Achieving double enhancement of gap birefringence by regulating anionic units helps to push phase-matching (PM) wavelength into UV/DUV Herein, starting from famous NLO material LiNbO3, a "dual-anion strategy" is proposed regulate [NbO6–xFx] octahedra, predicted Li2Nb2O6–xF2x·(LiF)y (x = 1, 2, 4; y 0, 2) exhibit dual-property magnification wide (3.82–6.26 eV, 1–3 eV larger than LiNbO3) extraordinary (0.100–0.322, 1–4 times that LiNbO3), along with strong second harmonic generation (SHG) response 2.6–6.2 × KDP. Remarkably, Li2NbOF5-I LiNbOF4-II have extremely short PM (λPM 209 nm) ever reported for oxyfluorides. Further analysis uncovers fluorinated modification edges increase octahedral anisotropy [NbO6−xFx] groups main reasons enhanced ability.

Язык: Английский

Процитировано

6

Layered (C5H6ON)2[Sb2O(C2O4)3] with a large birefringence derived from the uniform arrangement of π-conjugated units DOI

Dong‐Xue Jiao,

Huili Zhang, Chao He

и другие.

Chinese Journal of Structural Chemistry, Год журнала: 2024, Номер 43(6), С. 100304 - 100304

Опубликована: Апрель 13, 2024

Язык: Английский

Процитировано

6

Room-Temperature Phase Transition Material with Switchable Second-Order Nonlinear Optical Properties DOI

Yan-Ling Luo,

Lin Zhou,

Yong‐Ju Bai

и другие.

ACS Applied Materials & Interfaces, Год журнала: 2024, Номер 16(19), С. 25065 - 25070

Опубликована: Май 7, 2024

Phase transition materials with switchable second-order nonlinear optical (NLO) properties have attracted extensive attention because of their great application potential in photoelectric switches, sensors, and modulators, while metal-free organics NLO switchability near room temperature remain scarce. Herein, we report a hydrogen-bonded organic crystal, 2-methylpropan-2-aminium 2,2-dimethylpropanoate (1), exhibiting room-temperature phase favorable switchability. Through investigations on its thermal anomalies, dielectric properties, crystal structures, uncover that 1 holds near-room-temperature at 303 K from noncentrosymmetric point group C2v to centrosymmetric one D2h, which is attributed the order–disorder transformations both tert-butylamine cations dimethylpropionic acid anions. Accompanied by symmetry change during transition, exhibits reversible repeatable "on–off" desirable switching contrast ratio ca. 19 between high low states. This discovery demonstrates behavior temperature, serving as promising candidate smart ecofriendly functional devices.

Язык: Английский

Процитировано

6

Machine learning regression model for predicting the band gap of multi-elements nonlinear optical crystals DOI

Yaohui Yin,

Wang Ai,

Zhixin Sun

и другие.

Computational Materials Science, Год журнала: 2024, Номер 242, С. 113109 - 113109

Опубликована: Май 22, 2024

Язык: Английский

Процитировано

5

Interpretable Machine Learning‐Assisted High‐Throughput Screening for Understanding NRR Electrocatalyst Performance Modulation between Active Center and C‐N Coordination DOI Creative Commons

Jinxin Sun,

Anjie Chen,

Junming Guan

и другие.

Energy & environment materials, Год журнала: 2023, Номер 7(5)

Опубликована: Дек. 11, 2023

Understanding the correlation between fundamental descriptors and catalytic performance is meaningful to guide design of high‐performance electrochemical catalysts. However, exploring key factors that affect in vast catalyst space remains challenging for people. Herein, accurately identify N 2 reduction, we apply interpretable machine learning (ML) analyze high‐throughput screening results, which also suited other surface reactions catalysis. To expound on paradigm, 33 promising catalysts are screened from 168 carbon‐supported candidates, specifically single‐atom (SACs) supported by a BC 3 monolayer (TM@V B/C ‐N n = 0–3 ‐BC ) via screening. Subsequently, hybrid sampling method XGBoost model selected classify eligible non‐eligible Through feature interpretation using Shapley Additive Explanations (SHAP) analysis, two crucial features, is, number valence electrons ( v nitrogen substitution ), out. Combining SHAP analysis electronic structure calculations, synergistic effect an active center with low electron numbers reasonable C‐N coordination (a medium fraction substitution) can exhibit high performance. Finally, six superior limiting potential lower than −0.4 V predicted. Our workflow offers rational approach obtaining information results efficient be applied materials reactions.

Язык: Английский

Процитировано

11

Target-Oriented Synthesis of Borate Derivatives Featuring Isolated [B3O3] Six-Membered Rings as Structural Features DOI
Meng Cheng, Congcong Jin, Wenqi Jin

и другие.

Inorganic Chemistry, Год журнала: 2023, Номер 62(23), С. 9209 - 9216

Опубликована: Май 31, 2023

Borates provide an excellent platform for investigating the optical nonlinearity and linearity of crystals as photoelectric functional materials. In our work, borate derivatives with isolated [B3O3] six-membered rings structural features are preferred system due to their simple units properties. Herein, by utilizing target-oriented synthesis, a series derivatives, A2[B3O3F4(OH)] (A= NH4, Rb, Cs) (ABOFH), K2.3Cs0.7B3O3F6 (KCsBOF), Cs3[B3O3(OH)3]Cl3 (CsBOHCl), novel heteroanionic groups containing [BOxF4–x] (x = 0–3) and/or [BO2(OH)] were obtained. ABOFH, KCsBOF, CsBOHCl construct different two-dimensional pesudolayers featuring [B3O3F4(OH)], [B3O3F6], [B3O3(OH)3] units, respectively. Also, properties arrangement information these anionic studied. Among total five compounds, (NH4)2[B3O3F4(OH)] enlarged birefringence sufficient band gaps screened out promising birefringent optimally aligned configuration birefringence-active units. The successful results synthesis indicate more profound conclusion that now has diversified chemistry, effective strategy was proposed modify species optimize performance crystals.

Язык: Английский

Процитировано

10

Two Hydroxyfluorooxoborates Achieving Deep‐Ultraviolet Cutoff Edges and Moderate Birefringence by Assembling Multi‐Anionic Groups DOI

Huanhuan Cheng,

Xiaojing Li, Shilie Pan

и другие.

Chemistry - A European Journal, Год журнала: 2024, Номер 30(33)

Опубликована: Апрель 15, 2024

Abstract Assembling multi‐anionic groups is conducive to utilizing respective advantage achieve the enhancement of optical performance. Two new hydroxyfluorooxoborates, Ama 2‐Rb 2 B 3 O F 4 (OH) and K 8 Cs 15 14 7 20 ⋅ H with [B (OH)] six‐membered rings were synthesized for first time. The title compounds exhibit short ultraviolet cutoff edges (<200 nm) possesses a moderate experimental refractive index difference 0.051@546 nm.

Язык: Английский

Процитировано

4

Accelerating the discovery of direct bandgap doped-spinel photovoltaic materials: A target-driven approach using interpretable machine learning DOI
Chaofan Liu, Zhengxin Chen,

Chunliang Ding

и другие.

Solar Energy Materials and Solar Cells, Год журнала: 2024, Номер 271, С. 112881 - 112881

Опубликована: Апрель 25, 2024

Язык: Английский

Процитировано

4

Hierarchy-boosted funnel learning for identifying semiconductors with ultralow lattice thermal conductivity DOI Creative Commons
Mengfan Wu,

Shenshen Yan,

Jie Ren

и другие.

npj Computational Materials, Год журнала: 2025, Номер 11(1)

Опубликована: Апрель 22, 2025

Язык: Английский

Процитировано

0

A Machine-Learning-Assisted Crystalline Structure Prediction Framework To Accelerate Materials Discovery DOI
Ran An, Congwei Xie,

Dongdong Chu

и другие.

ACS Applied Materials & Interfaces, Год журнала: 2024, Номер 16(28), С. 36658 - 36666

Опубликована: Июль 8, 2024

Modern crystal structure prediction methods based on generation algorithms and first-principles calculations play important roles in the design of new materials. However, cost these is very expensive because their success mostly relies efficient sampling structures accurate evaluation energies for those sampled structures. Herein, we develop a Machine-learning-Assisted CRYStalline Materials sAmpling sysTem (MAXMAT) aiming to accelerate For given chemical composition, MAXMAT can generate with help Python package (PyXtal) quickly evaluate generated using well-developed machine learning interaction potential model (M3GNET). We have used perform searches three different systems (TiO2, MgAl2O4, BaBOF3) test its accuracy efficiency. Furthermore, apply predict nonlinear optical materials, suggesting several thermodynamically synthesizable high performance LiZnGaS3 CaBOF3 systems.

Язык: Английский

Процитировано

3