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김동하 교수

Dongha Kim

UNIST 에너지화학공학과 · 재료과학

연구실 소개

김동하 교수의 연구실은 전자재료 및 나노구조 물질을 기반으로 한 에너지 변환 및 저장 소재의 설계와 기작 규명을 핵심으로 합니다. 주로 리치지터스, 산화물 반도체, 금속 나노입자 등에서 발생하는 표면 화학적 불안정성과 나노구조의 안정성 문제를 전기화학적 방법과 고해상도 분석 기법을 융합하여 해결하고자 합니다. 특히 리튬이온 이차전지, 고체 산화물 전기화학 세포, CO₂ 전환 촉매 등에서의 성능 향상과 내구성 향상을 목표로 하며, 나노스케일에서의 원자적 메커니즘 이해에 중점을 두고 있습니다.

전기화학적 나노소재에너지 저장표면 안정성촉매 설계고체 전지

연구 현황

논문 수
55
총 인용 수
909
최근 5년 논문
33
주요 분야
재료과학

연구 성과 추이

표시된 성과는 수집된 데이터 기준으로 산출되며, 일부 차이가 있을 수 있습니다.

5개년 연도별 논문 게재 수
33총합
2022
2023
2024
2025
2026
5개년 연도별 피인용 수
353총합
20222023202420252026

주요 논문

15
1
논문|인용수 172·2020
Protonic solid-state electrochemical synapse for physical neural networks
Xiahui Yao, Konstantin Klyukin, Wenjie Lu, Murat Onen, Seungchan Ryu, Dongha Kim, Nicolas Émond, Iradwikanari Waluyo, Adrian Hunt, Jesús A. del Alamo, Ju Li, Bilge Yildiz
SJR Q1Nature CommunicationsOA

Abstract Physical neural networks made of analog resistive switching processors are promising platforms for analog computing. State-of-the-art resistive switches rely on either conductive filament formation or phase change. These processes suffer from poor reproducibility or high energy consumption, respectively. Herein, we demonstrate the behavior of an alternative synapse design that relies on a deterministic charge-controlled mechanism, modulated electrochemically in solid-state. The device o

Electrical and Electronic EngineeringEngineering
2
논문|인용수 79·2020
Electrochemical Polarization Dependence of the Elastic and Electrostatic Driving Forces to Aliovalent Dopant Segregation on LaMnO3
Dongha Kim, Roland Bliem, Franziska Heß, Jean‐Jacques Gallet, Bilge Yildiz
SJR Q1Journal of the American Chemical SocietyOA

Segregation of aliovalent dopant cations is a common degradation pathway on perovskite oxide surfaces in energy conversion and catalysis applications. Here we focus on resolving quantitatively how dopant segregation is affected by oxygen chemical potential, which varies over a wide range in electrochemical and thermochemical energy conversion reactions. We employ electrochemical polarization to tune the oxygen chemical potential over many orders of magnitude. Altering the effective oxygen chemic

Materials ChemistryMaterials Science
3
논문|인용수 77·2012
Electrospun Ni-Added SnO2–Carbon Nanofiber Composite Anode for High-Performance Lithium-Ion Batteries
Dongha Kim, Daehee Lee, Joosun Kim, Jooho Moon
SJR Q1ACS Applied Materials & Interfaces

The SnO(2) anode is a promising anode for next-generation Li ion batteries because of its high theoretical capacity. However, it exhibits inherent capacity fading because of the large volume change and pulverization that occur during the charge/discharge cycles. The buffer matrix, such as electrospun carbon nanofibers (CNFs), can alleviate this problem to some extent, but SnO(2) particles are thermodynamically incompatible with the carbon matrix such that large Sn agglomerates form after carboni

Electrical and Electronic EngineeringEngineering
4
논문|인용수 70·2023
Improvement of oxygen reduction activity and stability on a perovskite oxide surface by electrochemical potential
Sanaz Koohfar, Masoud Ghasemi, Tyler Hafen, Georgios Dimitrakopoulos, Dongha Kim, Jenna Pike, S. Elangovan, Enrique D. Gomez, Bilge Yildiz
SJR Q1Nature CommunicationsOA

Abstract The instability of the surface chemistry in transition metal oxide perovskites is the main factor hindering the long-term durability of oxygen electrodes in solid oxide electrochemical cells. The instability of surface chemistry is mainly due to the segregation of A-site dopants from the lattice to the surface. Here we report that cathodic potential can remarkably improve the stability in oxygen reduction reaction and electrochemical activity, by decomposing the near-surface region of t

Materials ChemistryMaterials Science
5
논문|인용수 62·2024
Atomic-level Cu active sites enable energy-efficient CO2 electroreduction to multicarbon products in strong acid
Lizhou Fan, Feng Li, Tianqi Liu, Jianan Erick Huang, Rui Kai Miao, Yan Yu, Shihui Feng, Cheuk‐Wai Tai, Sung‐Fu Hung, Hsin-Jung Tsai, Mengcheng Chen, Yang Bai
SJR Q1Nature Synthesis
Renewable Energy, Sustainability and the EnvironmentEnergy
6
논문|인용수 61·2020
Enhancing the conductivity of PEDOT:PSS films for biomedical applications via hydrothermal treatment
Wooseong Jeong, Gihyeok Gwon, Jae‐Hyun Ha, Dongha Kim, Kijoo Eom, Ju Hyang Park, Seok Ju Kang, Bongseop Kwak, Jung‐Il Hong, Shinbuhm Lee, Shinbuhm Lee, Dong Choon Hyun
SJR Q1Biosensors and Bioelectronics
Polymers and PlasticsMaterials Science
7
논문|인용수 39·2024
Acid-Stable Cu Cluster Precatalysts Enable High Energy and Carbon Efficiency in CO2 Electroreduction
Dongha Kim, Sungjin Park, Junwoo Lee, Yiqing Chen, Li Feng, Jiheon Kim, Yang Bai, Jianan Erick Huang, Shijie Liu, Eui Dae Jung, Byoung‐Hoon Lee, Panagiotis Papangelakis
SJR Q1Journal of the American Chemical Society

The electrochemical reduction of CO 2 in acidic media offers the advantage of high carbon utilization, but achieving high selectivity to C 2+ products at a low overpotential remains a challenge. We identified the chemical instability of oxide-derived Cu catalysts as a reason that advances in neutral/alkaline electrolysis do not translate to acidic conditions. In acid, Cu ions leach from Cu oxides, leading to the deactivation of the C 2+ -active sites of Cu nanoparticles. This prompted us to desi

Renewable Energy, Sustainability and the EnvironmentEnergy
8
논문|인용수 21·2022
Controlling the Size of Au Nanoparticles on Reducible Oxides with the Electrochemical Potential
Dongha Kim, Georgios Dimitrakopoulos, Bilge Yildiz
SJR Q1Journal of the American Chemical Society

Controlling the size of Au nanoparticles (NPs) and their interaction with the oxide support is important for their catalytic performance in chemical reactions, such as CO oxidation and water-gas shift. It is known that the oxygen vacancies at the surface of support oxides form strong chemical bonding with the Au NPs and inhibit their coarsening and deactivation. The resulting Au/oxygen vacancy interface also acts as an active site for oxidation reactions. Hence, small Au NPs are needed to increa

Materials ChemistryMaterials Science
9
논문|인용수 14·2023
Cation deficiency enables reversal of dopant segregation at perovskite oxide surfaces under anodic potential
Dongha Kim, Adrian Hunt, Iradwikanari Waluyo, Bilge Yildiz
SJR Q1Journal of Materials Chemistry AOA

Applying anodic potential can be an efficient way to re-activate the perovskite oxide surface by incorporating the surface dopant precipitates into the perovskite phase.

Materials ChemistryMaterials Science
10
논문|인용수 7·2023
Solid‐State Catalytic Hydrogen Sponge Effects in BaInO2.5 Epitaxial Films
Dongha Kim, Yuri Jeon, Judith L. MacManus‐Driscoll, Shinbuhm Lee
SJR Q1Advanced Functional Materials

Abstract Gas sponges capable of absorbing, storing, and releasing ions in a reversible manner are in high demand for advanced electronics, energy devices, and sensors. Here, it is shown that brownmillerite BaInO 2.5 epitaxial films exhibit the capability to act as solid‐state catalytic hydrogen sponges at a remarkably low temperature (≈100 °C). Compared to sintered pellets with random crystallographic orientations and many defects, BaInO 2.5 epitaxial films give three orders of magnitude higher

Materials ChemistryMaterials Science
11
논문|인용수 7·2023
SST v1.0.0 with C API: Pluggable security solution for the Internet of Things
Dongha Kim, Yeongbin Jo, Tae-Kyung Kim, Hokeun Kim
SJR Q3SoftwareXOA

The Internet of things (IoT) integrates heterogeneous computing devices, allowing each node to communicate with one another. However, the connected “things” raise security challenges that need protection for IoT devices from network-based attacks. As an integrated solution, Secure Swarm Toolkit (SST) provides authorization infrastructure that addresses the security requirements of IoT devices. The pre-release version of SST primarily provided the Node.js and JavaScript-based API for programming

Computer Networks and CommunicationsComputer Science
12
논문|인용수 6·2023
Stable Supercapacity of Binder-Free TiO2(B) Epitaxial Electrodes for All-Solid-State Nanobatteries
Dongha Kim, Jingyeong Jeon, Joon Deok Park, Xiao‐Guang Sun, Xiang Gao, Ho Nyung Lee, Judith L. MacManus‐Driscoll, Deok‐Hwang Kwon, Shinbuhm Lee
SJR Q1Nano LettersOA

Owing to its pseudocapacitive, unidimensional, rapid ion channels, TiO 2 (B) is a promising material for application to battery electrodes. In this study, we align these channels by epitaxially growing TiO 2 (B) films with the assistance of an isostructural VO 2 (B) template layer. In a liquid electrolyte, binder-free TiO 2 (B) epitaxial electrodes exhibit a supercapacity near the theoretical value of 335 mA h g –1 and an excellent charge–discharge reproducibility for ≥200 cycles, which outperfo

Electrical and Electronic EngineeringEngineering
13
논문|인용수 6·2025
Passive direct air capture via evaporative carbonate crystallization
Dongha Kim, Shijie Liu, Tevin Devasagayam, Rui Kai Miao, Jiheon Kim, Hyeon Seok Lee, Yuxuan Gao, Kevin Golovin, Todd Scheidt, David Sinton
Nature Chemical Engineering
Biomedical EngineeringEngineering
14
논문|인용수 5·2025
Freestanding VO2 membranes on epidermal nanomesh for ultra-sensitive correlated breathable sensors
Dongha Kim, Dongju Lee, Jiseok Park, Jihoon Bae, Aiping Chen, Judith L. MacManus‐Driscoll, Sungwon Lee, Shinbuhm Lee
SJR Q1Nano ConvergenceOA

Abstract The interest in highly sensitive sensors is rapidly increasing for detecting very tiny signals for Internet of Things devices. Here, we achieve ultra-sensitive correlated breathable sensors based on freestanding VO 2 membranes. We fabricate the membranes by growing VO 2 films onto sacrificial Sr 3 Al 2 O 6 layer grown on SrTiO 3 , selectively dissolving the Sr 3 Al 2 O 6 in water, and then rendering freestanding VO 2 membrane on nanomesh. The nanomeshes are extremely flexible, sweat per

Polymers and PlasticsMaterials Science
15
논문|인용수 2·2021
Understanding Effects of Architecture Design to Invariance and Complexity in Deep Neural Networks
Dongha Kim, Yongdai Kim
SJR Q1IEEE AccessOA

This article studies the role of architecture design, i.e. choice of the number of nodes at each hidden layer, in deep neural networks (DNNs). We give a theoretical explanation that invariance and complexity of a DNN are determined by the design of its architecture. To be more specific, for DNNs with the rectified linear activation function, we prove that the variations of gradients become the largest when the bottleneck layer, the layer with the fewest nodes, changes its activation pattern and

Artificial IntelligenceComputer Science

대표 연구 분야

Materials ChemistryElectrical and Electronic EngineeringRenewable Energy, Sustainability and the EnvironmentArtificial IntelligencePolymers and PlasticsWater Science and Technology

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