About

Dr. Tae Jin Kim is an Associate Professor in the Department of Materials Science and Chemical Engineering at Stony Brook University. His research focuses on the development of catalytic methodologies that can control hydrocarbon-based reaction pathways. He is particularly engaged in exploring new catalyst development, active sites, and providing insights into reaction mechanisms and intermediate molecular structures through in-situ and operando experimental conditions. His work aims to advance biomass conversion to fuels and chemicals, utilizing heterogeneous and homogeneous catalysis, supported metal oxides, solid acids, mineral acids, and zeolites. Dr. Kim employs a combination of experimental techniques, including in-situ and operando spectroscopy, to improve and understand catalytic processes, identify intermediate species, and active sites. He is also interested in elucidating complex reaction pathways, transition state geometries, and thermodynamic properties through Density Functional Theory calculations, collaborating with the theoretical calculation research group at Argonne National Laboratory. His research contributes to the production of biochemicals and biodiesel from biomass-derived resources, emphasizing the evaluation of catalytic activity and selectivity, and integrating experimental and computational methods to understand molecular structures and thermodynamic properties. He earned his Ph.D. in Chemical Engineering from Lehigh University in 2007, after completing his M.S. and B.A. in Chemical Engineering at Hong Ik University in Korea. Dr. Kim has held positions as a Postdoctoral Researcher at Argonne National Laboratory and UC Berkeley before joining Stony Brook University as an Assistant Professor in 2013. His academic and research activities are dedicated to advancing catalytic science and engineering, with a focus on biomass conversion and sustainable chemical processes.

Research topics

• Materials science
• Organic chemistry
• Chemistry
• Artificial Intelligence
• Nanotechnology
• Chemical engineering
• Computer Science
• Biochemical engineering
• Engineering
• Psychology
• Optics
• Neuroscience
• Polymer chemistry
• Biology
• Nuclear chemistry
• Waste management
• Composite material

Selected publications

• Achieving Outstanding Endurance (>10⁷) in Large-Array Two-Deck 16 Nm SOM Through Process, Structure, and Design Strategies for Emerging SCM Applications

  2025-06-08 · 1 citations

  article

  We successfully demonstrated a two-deck structure selectoronly memory (SOM) based on a 16 nm half-pitch, achieving endurance exceeding 10<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">7</sup> cycles at raw bit error rate (RBER) 200 ppm through process, structure, and design strategies. Our findings reveal that SOM endurance is not only influenced by process factors such as dual functional material (DFM) and encapsulation but also strongly depends on the spike charge. This underscores the importance of both spike charge suppression and process optimizations to enhance SOM performance.

  PublisherDOI

• Ex-Post Settling up of Financial Misreporting and CEO Compensation&amp;nbsp;

  SSRN Electronic Journal · 2025-01-01

  preprintOpen accessSenior author
  PublisherDOI

• Ce-Doped NiO aerogel with hierarchical porosity and abundant oxygen vacancies for enhanced CO2 cycloaddition to epoxides

  Separation and Purification Technology · 2025-06-26 · 4 citations

  article
  PublisherDOI

• Thermally Triggered Double Emulsion‐Integrated Hydrogel Microparticles for Multiplexed Molecular Diagnostics (Adv. Sci. 12/2025)

  Advanced Science · 2025-03-01

  articleOpen access

  Double emulsion-integrateD HyDrogel microparticlesIn article number 2408158, Sang Kyung Kim, Seungwon Jung, and co-workers introduce TaqPIN, a hydrogel microparticle platform for multiplexed molecular diagnostics.Thermo-responsive double emulsion carriers efficiently deliver target-specific reagents into each microparticle, where confined amplification enables independent reactions.Integrated into a structured array, TaqPIN achieves nine-plex SARS-CoV-2 variant detection with high sensitivity and specificity.

  PublisherOA PDFDOI

• Research on Enhancing the Solubility and Bioavailability of Canagliflozin Using Spray Drying Techniques with a Quality-by-Design Approach

  Pharmaceutics · 2025-10-11

  articleOpen access

  Objectives: The objective of this study was to enhance the solubility and bioavailability of canagliflozin (CFZ) using a spray drying technique with a Quality-by-Design (QbD) approach. Methods: The formulation of CFZ-loaded solid dispersions (CFZ-SDs) was optimized using a Box–Behnken design (BBD) with three factors at three levels, resulting in a total of fifteen experiments, including three central point replicates. The design space was determined using the BBD, and the optimized CFZ-SD was evaluated for reproducibility, morphology, and physical properties and subjected to in vitro and in vivo tests. Results: The optimal values for each X factor were identified using a response optimization tool, achieving a yield (Y1) of 62.8%, a solubility (Y2) of 9941 μg/mL, and a particle size (Y3) of 5.89 μm, all of which were within the 95% prediction interval (PI). Additionally, amorphization induced by spray drying was confirmed for the optimized CFZ-SD using scanning electron microscopy (SEM), differential scanning calorimetry (DSC), and powder X-ray diffraction (PXRD) analyses. In in vitro dissolution tests, the final dissolution rate of the CFZ-SD increased 3.58-fold at pH 1.2 and 3.84-fold at pH 6.8 compared to an Invokana® tablet. In addition, relative to CFZ, it showed an 8.67-fold and 8.85-fold increase at pH 1.2 and pH 6.8, respectively. The in vivo pharmacokinetic behavior of CFZ and the CFZ-SD was evaluated in Sprague–Dawley rats following oral administration at a dose of 5 mg/kg. The AUC of the CFZ-SD increased 1.9-fold compared to that of CFZ. Conclusions: In this study, a solid dispersion (SD) formulation of CFZ, a BCS class IV SGLT2 inhibitor, was developed and optimized using a QbD approach to enhance solubility and oral bioavailability.

  PublisherOA PDFDOI

• Development of an Efficient Integrated Test Circuit for Overcurrent and Short Circuit Current Testing of the MMC-Based MVDC Valve

  Journal of Electrical Engineering and Technology · 2025-04-02 · 1 citations

  article
  PublisherDOI

• Spatially Organized DNA-templated Silver Nanoclusters as Potent Antimicrobial Agents for ESKAPE Infections

  bioRxiv (Cold Spring Harbor Laboratory) · 2025-10-03 · 2 citations

  preprintOpen access

  ABSTRACT Antibiotic-resistant bacteria cause more than one million deaths annually worldwide. The rapid evolution and gene exchange among pathogens often render new antibiotic drugs ineffective soon after deployment, underscoring the urgent need for alternative therapeutic strategies. Nanoscale silver is well known for its innate bacteriostatic and bactericidal activity but typically requires high concentrations for efficacy that causes toxicities and limits broader clinical applications. To address this, we introduce programmable self-assembling DNA scaffolds that template, stabilize, and spatially organize multiple copies of monodisperse silver nanoclusters (DNA-AgNCs). These assemblies enhance antimicrobial potency of formulations while also exhibiting intrinsic fluorescence, providing dual functionality for therapeutic and bioimaging applications. Detailed characterization identified DNA-AgNC scaffolds with improved stability and enhanced activity against clinically relevant antibiotic-resistant planktonic ESKAPE pathogens. We also revealed the DNA-AgNC constructs that significantly lowered intracellular infections of human bone cells with Staphylococcus aureus . Collectively, the results highlight spatially organized DNA-AgNCs as a promising modular platform for next-generation antibacterial therapy and real-time bioimaging.

  PublisherOA PDFDOI

• In-situ Raman spectroscopic analysis of phase transition temperatures in silica interacting with water and NaCl solutions

  Scientific Reports · 2025-07-21

  articleOpen accessSenior author

  Phase transition temperatures of pure water and aqueous sodium chloride (NaCl) solutions, both in bulk form and mixed with the silica (SiO2) powder, were investigated using in-situ Raman spectroscopy. To determine the freezing and melting temperatures, the OH-stretching and bending regions of the Raman spectrum were analysed, along with investigation of hydrohalite (HH) formation in saline water. A spectral phase transition marker, SD, defined as the intensity ratio of asymmetric to symmetric OH-stretching bands (Iasym/Isym), was applied to measure the freezing and melting temperatures. In the case of bulk water and aqueous salt solutions, complete tranformation of liquid to solid phase was noticed. However, in the case of SiO2 mixed liquids, a non-freezable liquid layer was observed, which could be due to the interaction between the silanol (Si–OH) functional groups and the water/NaCl solution. These findings are expected to provide valuable insights into the freezing and thawing processes in both normal and saline soil in cold regions.

  PublisherOA PDFDOI

• DCL-A: An Unsupervised Ultrasound Beamforming Framework with Adaptive Deep Coherence Loss for Single Plane Wave Imaging

  Diagnostics · 2025-12-14

  articleOpen access1st author

  Background/Objectives: Single plane wave imaging (SPWI) offers ultrafast acquisition rates suitable for real-time ultrasound imaging applications; however, its image quality is compromised by beamforming artifacts such as sidelobe and grating lobe interferences. Methods: In this paper, we introduce an unsupervised beamforming framework based on adaptive deep coherence loss (DCL-A), which employs linear (αlinear) or nonlinear weighting (αnonlinear) within the coherence loss function to enhance the artifact suppression and improve overall image quality. During training, the adaptive weight (α) is determined by the angular distance between the input and target PW frames, assigning lower α values for smaller distances and higher α values for larger distances. Therefore, this adaptability enables the method to surpass conventional DCL (no weighting) by emphasizing the different spatial correlation characteristics of mainlobe and sidelobe signals. To assess the performance of the proposed method, we trained and validated the network using publicly available datasets, including simulation, phantom and in vivo images. Results: In the simulation and phantom studies, the DCL-A with αnonlinear outperformed the comparison methods (i.e., conventional DCL and DCL-A with αlinear) in terms of peak range sidelobe level (PRSLL), achieving 7 dB and 14 dB greater sidelobe suppression, respectively, while maintaining a comparable full width at half maximum (FWHM). In the in vivo study, it achieved the highest contrast resolution among the comparison methods, yielding 2% and 3% improvements in generalized contrast-to-noise ratio (gCNR), respectively. Conclusions: These results demonstrate that the proposed deep learning-based beamforming framework can significantly enhance SPWI image quality without compromising frame rate, indicating promising potential for high-speed, high-resolution clinical applications such as cardiac assessment and real-time interventional guidance.

  PublisherOA PDFDOI

• Spatial Distribution of Dissolved Trace Metals in the Nakdong River Estuary: Impact of an Estuarine Barrage on Their Chemical Behaviors

  2025-01-01

  article
  PublisherDOI

Recent grants

• Green chemistry degradation of cotton waste for circular economy textiles

  NSF · $315k · 2020–2023

• EAGER: Alternative Pathways for Biofuel formation from Furfuryl alcohol over Heterogeneous Catalysts

  NSF · $112k · 2015–2016

• Collaborative Research & GOALI: Direct-Fed Ethanol Metal-Supported Solid Oxide Fuel Cells

  NSF · $233k · 2021–2025

Frequent coauthors

• Nusnin Akter

  Brookhaven National Laboratory

  57 shared

• J. Anibal Boscoboinik

  51 shared

• Darı́o Stacchiola

  Brookhaven National Laboratory

  46 shared

• Jian‐Qiang Zhong

  Hangzhou Normal University

  46 shared

• Gihan Kwon

  Brookhaven National Laboratory

  43 shared

• Ashley R. Head

  42 shared

• Jerzy T. Sadowski

  Brookhaven National Laboratory

  42 shared

• Samuel Tenney

  Brookhaven National Laboratory

  42 shared

Education

• B.A., Chemical engineering

  Hong Ik University

  1994

• M.S., Chemical engineering

  Hong Ik University

  1996

• Ph.D., Chemical Engineering

  Lehigh University

  2007