Literature DB >> 24437942

Discovery of a phosphor for light emitting diode applications and its structural determination, Ba(Si,Al)5(O,N)8:Eu2+.

Woon Bae Park1, Satendra Pal Singh, Kee-Sun Sohn.   

Abstract

Most of the novel phosphors that appear in the literature are either a variant of well-known materials or a hybrid material consisting of well-known materials. This situation has actually led to intellectual property (IP) complications in industry and several lawsuits have been the result. Therefore, the definition of a novel phosphor for use in light-emitting diodes should be clarified. A recent trend in phosphor-related IP applications has been to focus on the novel crystallographic structure, so that a slight composition variance and/or the hybrid of a well-known material would not qualify from either a scientific or an industrial point of view. In our previous studies, we employed a systematic materials discovery strategy combining heuristics optimization and a high-throughput process to secure the discovery of genuinely novel and brilliant phosphors that would be immediately ready for use in light emitting diodes. Despite such an achievement, this strategy requires further refinement to prove its versatility under any circumstance. To accomplish such demands, we improved our discovery strategy by incorporating an elitism-involved nondominated sorting genetic algorithm (NSGA-II) that would guarantee the discovery of truly novel phosphors in the present investigation. Using the improved discovery strategy, we discovered an Eu(2+)-doped AB5X8 (A = Sr or Ba, B = Si and Al, X = O and N) phosphor in an orthorhombic structure (A21am) with lattice parameters a = 9.48461(3) Å, b = 13.47194(6) Å, c = 5.77323(2) Å, α = β = γ = 90°, which cannot be found in any of the existing inorganic compound databases.

Entities:  

Year:  2014        PMID: 24437942     DOI: 10.1021/ja409865c

Source DB:  PubMed          Journal:  J Am Chem Soc        ISSN: 0002-7863            Impact factor:   15.419


  5 in total

1.  Classification of crystal structure using a convolutional neural network.

Authors:  Woon Bae Park; Jiyong Chung; Jaeyoung Jung; Keemin Sohn; Satendra Pal Singh; Myoungho Pyo; Namsoo Shin; Kee-Sun Sohn
Journal:  IUCrJ       Date:  2017-06-13       Impact factor: 4.769

2.  New strategy for designing orangish-red-emitting phosphor via oxygen-vacancy-induced electronic localization.

Authors:  Yi Wei; Gongcheng Xing; Kang Liu; Guogang Li; Peipei Dang; Sisi Liang; Min Liu; Ziyong Cheng; Dayong Jin; Jun Lin
Journal:  Light Sci Appl       Date:  2019-01-30       Impact factor: 17.782

3.  Dirty engineering data-driven inverse prediction machine learning model.

Authors:  Jin-Woong Lee; Woon Bae Park; Byung Do Lee; Seonghwan Kim; Nam Hoon Goo; Kee-Sun Sohn
Journal:  Sci Rep       Date:  2020-11-24       Impact factor: 4.379

4.  Optimal Composition of Li Argyrodite with Harmonious Conductivity and Chemical/Electrochemical Stability: Fine-Tuned Via Tandem Particle Swarm Optimization.

Authors:  Sunggeun Shim; Woon Bae Park; Jungmin Han; Jinhyeok Lee; Byung Do Lee; Jin-Woong Lee; Jung Yong Seo; S J Richard Prabakar; Su Cheol Han; Satendra Pal Singh; Chan-Cuk Hwang; Docheon Ahn; Sangil Han; Kyusung Park; Kee-Sun Sohn; Myoungho Pyo
Journal:  Adv Sci (Weinh)       Date:  2022-07-21       Impact factor: 17.521

5.  A deep-learning technique for phase identification in multiphase inorganic compounds using synthetic XRD powder patterns.

Authors:  Jin-Woong Lee; Woon Bae Park; Jin Hee Lee; Satendra Pal Singh; Kee-Sun Sohn
Journal:  Nat Commun       Date:  2020-01-03       Impact factor: 14.919

  5 in total

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