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RESEARCH PAPER · Science China Materials · 2023

A prediction-driven database to enable rapid discovery of nonlinear optical materials

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A prediction-driven database to enable rapid discovery of nonlinear optical materialsOriginalRoom-Temperature Phase Transition Material with Switchable Second-Order Nonlinear Optical Properties9Machine learning regression model for predicting the band gap of multi-elements nonlinear optical crystals17Old tree blossoms anew: Research progress on the structures and optical properties of ultraviolet selenites56Fluorine-driven materials design of novel deep-ultraviolet nonlinear optical crystal materials: Research progress and challenges6A Machine-Learning-Assisted Crystalline Structure Prediction Framework To Accelerate Materials Discovery19From B 3 O 3 (OH) 3 to B 3 O 3 F 3 : Uncovering Series of New Functional Units Based on [BO 2 F] Beneficial for Deep‐Ultraviolet Birefringence1Graph neural network guided design of novel deep-ultraviolet optical materials with high birefringence23Crystal Structure Design and Synthesis of Noncentrosymmetric Superconductors in Intercalation-Induced Transition Metal Dichalcogenides0Rb 1.87 Cs 1.13 B 8 O 13 (NO 3 ): a new acentric borate-nitrate with two types of three-dimensional interpenetrating lattices1Artificial intelligence guided search for van der Waals materials with high optical anisotropy7A potential UV nonlinear-optical crystal with a strong second-harmonic response: RbNa 2 Eu 2 (BO 3 ) 35Accelerating the discovery of high-performance nonlinear optical materials using active learning and high-throughput screening11Anion ratio-directed design of CaB 4 O 5 F 4 and CaB 6 O 8 F 4 : [BO 3 ]/[BO 2 F 2 ] hybridization tailoring deep-ultraviolet nonlinear optical performance2新型非线性光学晶体和双折射晶体的研究进展(特邀)4Accelerating Discovery of Infrared Nonlinear Optical Materials with High Lattice Thermal Conductivity: Combining Machine Learning and First‐Principles Calculations10New Ways to Discover Novel Nonlinear Optical Materials: Scaling Machine Learning with Chemical Descriptors Information20K2PbB5P3O17: A Mixed-Coordinated Borophosphate with Enhanced Birefringence Driven by the [B2O5] Unit5Prediction of New Functional Fluorooxoborates with Expected Anionic Framework: A Case of CaB3O5F4AI4NLO: An Integrated Data Platform for Machine Learning-Driven Exploration of Inorganic Nonlinear Optical Materials8Designing High-Performance Short-Wave UV Tellurium-Based Mixed Halides Birefringent Crystals via Halogen Substitution Engineering4First principle analysis of the electronic structure and optoelectronic properties of glycine copper chloride (GCC) and gadolinium doped glycine copper chloride (Gd: GCC) single crystals0Two-dimensional graphene-like BeO sheet: a promising deep-ultraviolet nonlinear optical material with strong and highly tunable second harmonic generation5Stepwise Substitution Strategy for Beryllium-Based Selenites with Enhanced SHG Response, Moderate Birefringence, and Short UV Cutoff Edges6Symmetry‐Aware Equivariant Network for Discovering SHG‐Active Materials5Screening practical nonlinear optical crystals by using graph neural networks0High‐Throughput Discovery of Large Birefringence Materials in Mixed‐N Hf‐O Systems0Novel [BO 2 ] superhalogen module-enabled deep-ultraviolet nonlinear optical material: rational design for tailored birefringence and phase matching0Navigating the Landscape of Next-Generation Nonlinear Optical Materials Discovery: Opportunities and Challenges Driven by Artificial Intelligence4Computational design of new DUV NLO fluorooxoborates with [BO 3 ] : [BO 3 F] = 2 : 1 via an anionic framework dimensionality-fixed strategy0Polymerization-enhanced optical anisotropy in selenites: a trimeric [H 2 Se 3 O 7 ] motif delivering large UV birefringence0InO6X (X = Cl, Br): distinct functional motif family for nonlinear optical materials5Functional Unit Design of Deep‐UV NLO Crystals With Short Phase‐Matching and Large SHG Response22Self-optimizing machine learning potential assisted automated workflow for highly efficient complex systems material design13Normalized Descriptor for Unbiased Screening of Second-Order Nonlinear Optical Materials3Artificial intelligence-enabled chiral functional materials design4Accelerating the discovery of athermal deep-ultraviolet nonlinear optical crystals via physics-informed herarchical graph learning1Minimizing Oscillator Strength: A Strategy for Engineering Deep-Ultraviolet Nonlinear Optical Crystals with Optimized Refractive-Index Dispersion0Interpretable Machine Learning for Bandgap Prediction and Descriptor‐Guided Design Rules of Phosphates1Design of deep-ultraviolet nonlinear optical BePNO2 guided by non-π-conjugated NLO-active unit0Toward the vacuum-ultraviolet frontier in nonlinear optical frequency conversion: phase-matching mechanisms across dimensions and architectures2Prediction of deep-ultraviolet nonlinear optical material in borosilicate system: a case of RbSiB3O70Uma abordagem com autoencoders variacionais condicionais para geração de materiais NLO com bandgap alvo0Accelerating the Discovery of Deep-Ultraviolet Nonlinear Optical Materials by Combining Machine Learning Interatomic Potentials with First-Principles Calculations: A Case of LiB2O3F0Attention-based composition learning for thermodynamic and electronic property prediction in inorganic materials0AlGaS3: a wide band gap ternary diamond-like infrared nonlinear optical material with high laser-induced damage threshold1Coordination chemistry of Sb(III)-based optical crystals: from lone-pair-induced distortion to birefringence and second-harmonic generation0

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

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

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  3. Old tree blossoms anew: Research progress on the structures and optical properties of ultraviolet selenites

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    Pengfei Li, Chun‐Li Hu, Jiang‐Gao Mao, Fang Kong

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  4. Fluorine-driven materials design of novel deep-ultraviolet nonlinear optical crystal materials: Research progress and challenges

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  5. A Machine-Learning-Assisted Crystalline Structure Prediction Framework To Accelerate Materials Discovery

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  6. From B 3 O 3 (OH) 3 to B 3 O 3 F 3 : Uncovering Series of New Functional Units Based on [BO 2 F] Beneficial for Deep‐Ultraviolet Birefringence

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    Kewang Zhang, Dongdong Chu, Juanjuan Lu, Zhihua Yang, Shilie Pan

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  7. Graph neural network guided design of novel deep-ultraviolet optical materials with high birefringence

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  8. Crystal Structure Design and Synthesis of Noncentrosymmetric Superconductors in Intercalation-Induced Transition Metal Dichalcogenides

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  9. Rb 1.87 Cs 1.13 B 8 O 13 (NO 3 ): a new acentric borate-nitrate with two types of three-dimensional interpenetrating lattices

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    Changyou Liu, Xu Liu, Qiuyuan Feng, Ketian Hou, Bei Zhang, Juanjuan Lu

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  10. Artificial intelligence guided search for van der Waals materials with high optical anisotropy

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  11. A potential UV nonlinear-optical crystal with a strong second-harmonic response: RbNa 2 Eu 2 (BO 3 ) 3

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    Journal of Materials Chemistry C · 2025-01-01

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  13. Anion ratio-directed design of CaB 4 O 5 F 4 and CaB 6 O 8 F 4 : [BO 3 ]/[BO 2 F 2 ] hybridization tailoring deep-ultraviolet nonlinear optical performance

    Journal of Materials Chemistry C · 2025-01-01

    Ke Li, Abudukadi Tudi, Congwei Xie, Wenqi Jin, Linlin Liu, Miriding Mutailipu, Kenneth Reinhard Poeppelmeier, Fangfang Zhang, Zhihua Yang, Shilie Pan

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  14. 新型非线性光学晶体和双折射晶体的研究进展(特邀)

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  15. Accelerating Discovery of Infrared Nonlinear Optical Materials with High Lattice Thermal Conductivity: Combining Machine Learning and First‐Principles Calculations

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  16. New Ways to Discover Novel Nonlinear Optical Materials: Scaling Machine Learning with Chemical Descriptors Information

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  17. K2PbB5P3O17: A Mixed-Coordinated Borophosphate with Enhanced Birefringence Driven by the [B2O5] Unit

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  18. Prediction of New Functional Fluorooxoborates with Expected Anionic Framework: A Case of CaB3O5F

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  19. AI4NLO: An Integrated Data Platform for Machine Learning-Driven Exploration of Inorganic Nonlinear Optical Materials

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  20. Designing High-Performance Short-Wave UV Tellurium-Based Mixed Halides Birefringent Crystals via Halogen Substitution Engineering

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  21. First principle analysis of the electronic structure and optoelectronic properties of glycine copper chloride (GCC) and gadolinium doped glycine copper chloride (Gd: GCC) single crystals

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    Tariq Mustafa, Nisha Devi, Mitesh B. Solanki, Bharat B. Parekh, K. K. Bamzai

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  22. Two-dimensional graphene-like BeO sheet: a promising deep-ultraviolet nonlinear optical material with strong and highly tunable second harmonic generation

    Science China Materials · 2025-11-06

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  23. Stepwise Substitution Strategy for Beryllium-Based Selenites with Enhanced SHG Response, Moderate Birefringence, and Short UV Cutoff Edges

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  24. Symmetry‐Aware Equivariant Network for Discovering SHG‐Active Materials

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  25. Screening practical nonlinear optical crystals by using graph neural networks

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  26. High‐Throughput Discovery of Large Birefringence Materials in Mixed‐N Hf‐O Systems

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  27. Novel [BO 2 ] superhalogen module-enabled deep-ultraviolet nonlinear optical material: rational design for tailored birefringence and phase matching

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  28. Navigating the Landscape of Next-Generation Nonlinear Optical Materials Discovery: Opportunities and Challenges Driven by Artificial Intelligence

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  29. Computational design of new DUV NLO fluorooxoborates with [BO 3 ] : [BO 3 F] = 2 : 1 via an anionic framework dimensionality-fixed strategy

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  30. Polymerization-enhanced optical anisotropy in selenites: a trimeric [H 2 Se 3 O 7 ] motif delivering large UV birefringence

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  31. InO6X (X = Cl, Br): distinct functional motif family for nonlinear optical materials

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  32. Functional Unit Design of Deep‐UV NLO Crystals With Short Phase‐Matching and Large SHG Response

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  33. Self-optimizing machine learning potential assisted automated workflow for highly efficient complex systems material design

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  34. Normalized Descriptor for Unbiased Screening of Second-Order Nonlinear Optical Materials

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  37. Minimizing Oscillator Strength: A Strategy for Engineering Deep-Ultraviolet Nonlinear Optical Crystals with Optimized Refractive-Index Dispersion

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  38. Interpretable Machine Learning for Bandgap Prediction and Descriptor‐Guided Design Rules of Phosphates

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  39. Design of deep-ultraviolet nonlinear optical BePNO2 guided by non-π-conjugated NLO-active unit

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  40. Toward the vacuum-ultraviolet frontier in nonlinear optical frequency conversion: phase-matching mechanisms across dimensions and architectures

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  41. Prediction of deep-ultraviolet nonlinear optical material in borosilicate system: a case of RbSiB3O7

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  42. Uma abordagem com autoencoders variacionais condicionais para geração de materiais NLO com bandgap alvo

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  43. Accelerating the Discovery of Deep-Ultraviolet Nonlinear Optical Materials by Combining Machine Learning Interatomic Potentials with First-Principles Calculations: A Case of LiB2O3F

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  45. AlGaS3: a wide band gap ternary diamond-like infrared nonlinear optical material with high laser-induced damage threshold

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  46. Coordination chemistry of Sb(III)-based optical crystals: from lone-pair-induced distortion to birefringence and second-harmonic generation

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