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Eunsong Kim,Minseon Kim,Juo Kim,Joonchul Kim,Jung-Hwan Park,Kyoung-Tak Kim,Joung-Hu Park,Taesic Kim,Kyoungmin Min 한국정밀공학회 2023 International Journal of Precision Engineering and Vol.24 No.7
Lithium-ion batteries are widely used in electric vehicles, electronic devices, and energy storage systems owing to their high energy density, long life, and outstanding performance. However, various internal and external factors affect the battery performance, leading to deterioration and ageing. Accurately estimating the state of health (SOH), state of charge (SOC), and remaining useful life (RUL) of batteries is challenging owing to complex operating characteristics and changing internal physical parameters. With the increasing availability of shared battery data and improved computer performance, the use of data-driven methods for battery health estimations and RUL predictions has gained popularity. We provide a comprehensive review of several studies in which data-driven methods were used for SOC and SOH estimation and RUL prediction. Specifically, we focus on the importance of open battery-cycling databases, various prediction methods used, and results obtained using each of these methods. Moreover, we aim to facilitate further research by providing a comprehensive description of the current state-of-the-art methods employed in battery health estimation and RUL prediction using open databases and machine-learning algorithms. Thus, we hope that this review will help researchers to develop accurate and reliable predictive models for battery health assessment in the future.
기계 학습을 적용한 나트륨 초이온 전고체(NASICON) 전해질 탐색 방법
김주오(Juo Kim),강승표(SeungPyo Kang),민경민(Kyoungmin Min) 대한기계학회 2022 대한기계학회 춘추학술대회 Vol.2022 No.11
Sodium-ion battery is considered promising alternatives as similar types of Lithium-ion battery because of their low manufacturing cost, wide abundance, and similar chemical/electrochemical properties. Among them, numerous studies are being conducted on solid state electrolytes(SSEs) that can solve the flammability problem of existing liquid state electrolytes(LSEs). Since the SSE tends to have lower ionic conductivity than the LSEs, research into finding a SSEs having ionic conductivity close to LSEs has been actively conducted. This research suggests a method to find a superionic materials among sodium (Na) superionic conductor (NASICON), one of the sodium-ion SSE, through machine learning. Various machine learning classification models were compared for 3,585 NASICON candidate materials, and the highest model showed an average accuracy of 0.84. Structural information was generated for the selected materials using Ewald summation, and the performance of the model is being verified through DFT calculation based on this structural information. Through this study, it is expected to accelerate the speed of NASICON material search.
기계 학습을 적용한 나트륨 초이온 전고체(NASICON) 전해질 탐색 방법
김주오(Juo Kim),강승표(SeungPyo Kang),민경민(Kyoungmin Min) 대한기계학회 2022 대한기계학회 춘추학술대회 Vol.2022 No.11
Sodium-ion battery is considered promising alternatives as similar types of Lithium-ion battery because of their low manufacturing cost, wide abundance, and similar chemical/electrochemical properties. Among them, numerous studies are being conducted on solid state electrolytes(SSEs) that can solve the flammability problem of existing liquid state electrolytes(LSEs). Since the SSE tends to have lower ionic conductivity than the LSEs, research into finding a SSEs having ionic conductivity close to LSEs has been actively conducted. This research suggests a method to find a superionic materials among sodium (Na) superionic conductor (NASICON), one of the sodium-ion SSE, through machine learning. Various machine learning classification models were compared for 3,585 NASICON candidate materials, and the highest model showed an average accuracy of 0.84. Structural information was generated for the selected materials using Ewald summation, and the performance of the model is being verified through DFT calculation based on this structural information. Through this study, it is expected to accelerate the speed of NASICON material search.
그래프 신경망 기반 원자간 상호작용 포텐셜을 통한 나트륨 초이온 전도체 하이브리드 고체 전해질 탐색 방법
김주오(Juo Kim),김지환(Ji-Hwan Kim),홍지민(Ji-Min Hong),박경원(Kyung-Won Park),민경민(Kyoungmin Min) 대한기계학회 2023 대한기계학회 춘추학술대회 Vol.2023 No.11
Recently, research on solid electrolytes with high energy density and stability has been actively conducted. This study proposes a new exploration method for composite electrolytes formed by synthesizing NASICON, one of the inorganic electrolytes, and PVDF-HFP, one of the polymer electrolytes. For this purpose, 24,181 NASICON materials were created through element substitution and screened based on synthesizability, thermodynamic stability, insulation, mechanical properties, and ionic conductivity. In the process of creating the structure of NASICON and predicting its properties, Graph Neural Network-based Machine Learning Interatomic Potential and machine learning models were used. Finally, the electrochemical performance of the composite produced through synthesis of the screened NASICON material and PVDF-HFP is tested, and the feasibility of the screening process and a new composite electrolyte material are proposed.
머신 러닝을 활용한 고엔트로피 가넷 구조의 전고체 전지를 위한 고체 전해질 발견
선지원(Jiwon Sun),김은송(Eunsong Kim),김주오(Juo Kim),김준철(Joonchul Kim),민경민(Kyoungmin Min) 대한기계학회 2023 대한기계학회 춘추학술대회 Vol.2023 No.11
Research in all-solid-state batteries (ASSBs) has surged due to their improved energy density and safety over liquid-based lithium-ion batteries. To enhance electrochemical performance, stable solid-state electrolytes (SSEs) are crucial. This study employed a novel machine learning (ML) screening platform to explore 161,280 high-entropy (HE) garnet-type SSE originated from known Li₇La₃Zr₂O<SUB>12</SUB> (LLZO) structures. Initially, an ML-based surrogate model identified electronconductive (bandgap < 1 eV) and thermodynamically unfavorable (energy above hull > 0.035 eV) materials to prevent short-circuits and decomposition. A recently developed ML interatomic potential (M3GNet) guided atomic arrangement for stability. Elastic properties were predicted to ensure dendrite suppression and interfacial stability. Molecular dynamics using M3GNet confirmed Li diffusivity. In conclusion, 23 promising HE garnet materials were identified for advanced ASSBs with these methods.
박영주,홍성빈,고석면,박용구,오윤주,김영완,김성기,남문석,김용성 대한내분비학회 2002 Endocrinology and metabolism Vol.17 No.1
Osteoporosis imperfecta (OI) is a genetic disorder characterized by fragility of bone, deafness, blue sclerae; and laxity of joints. Four types of OI are distinguished by clinical findings. Although mutations affecting collagen I are responsible for the disease in the most patients, the mechanism by which the genetic defects cause abnormal bone development has not been well established. Therefore we evaluated static and dynamic bone histomorphometry of type I OI in the case study of a 15 year old boy with OI who had blue sclerae, a history of frequent fracture and a familial history of blue sclerae. Biopsy of the ilium showed loss of connection between the cortical bone and trabecular bones. The Harversian system in the cortical bone was poorly developed. In the trabecular bones, the lamellar pattern was poorly developed. Mineral apposition rate of the cortical bone was 1.0 ㎛/day and of the trabecular bone was 0.79 ㎛/day. Thus OI might be regard as a disease whereby abnormal collagen synthesis interferes with bone strength by multiple mechanisms
( Juo Choi ),( Taejoon Park ),( Daun Kang ),( Jeongju Lee ),( Yungpil Kim ),( Pilgoo Lee ),( Gregory J. Y. Chung ),( Kyungyun Cho ) 한국미생물 · 생명공학회 2021 한국미생물·생명공학회지 Vol.49 No.4
Argyrins are a group of anticancer and antibacterial octapeptide bioactive substances isolated from myxobacteria. In this study, we showed that the myxobacterium Archangium gephyra MEHO_001, isolated in Korea, produces argyrins A and B. MEHO_001 cells tend to aggregate when cultured in liquid media. Hence, a dispersion mutant, MEHO_002, was isolated from MEHO_001. The MEHO_002 strain produced approximately 3.5 times more argyrins than that produced by the wild-type strain MEHO_001. We determined the whole-genome sequence of A. gephyra MEHO_002 and identified a putative argyrin biosynthetic gene cluster comprising five genes, arg1-arg5, encoding non-ribosomal peptide synthases and tailoring enzymes. Inactivation of arg2 by plasmid insertion disrupted argyrin production. The amino acid sequences of the proteins encoded by arg2-arg5 of A. gephyra MEHO_002 were 90-98% similar to those encoded by the argyrin biosynthetic genes of Cystobacter sp. SBCb004, an argyrin-producing myxobacterium with identical domain organization.
Dohee Kim,Juo Choi,Sunjin Lee,현혜숙,Kyoung Lee,Kyungyun Cho 한국미생물학회 2019 The journal of microbiology Vol.57 No.9
Myxococcus xanthus, a myxobacterium, displays phase variation between yellow phase and tan phase. We found that deletion of the encA gene encoding encapsulin and the encF gene encoding a metalloprotease causes formation of tan colonies that never transform into yellow colonies. The encA and encF mutants were defective in the production of DKxanthene and myxovirescin. They did not produce extracellular polysaccharides; hence, the cells did not aggregate in liquid and showed reduced swarming on agar plates. The mutants had defective sporulation, but were rescued extracellularly by wild type cells. All these traits indicate that the encA and encF mutants are likely to be tan-phase-locked, and encapsulin has a close relationship with phase variation in M. xanthus. The encA and encF genes are localized in the same gene cluster, encBAEFG (MXAN_3557~MXAN_3553). Unlike the encA and encF genes, deletion of other genes in the cluster did not show tan-phase-locked phenotype.