A5048420700- Crystallization and Solubility Studies
- X-ray Diffraction in Crystallography
- Conducting polymers and applications
- Luminescence and Fluorescent Materials
- Industrial Vision Systems and Defect Detection
- Organic Electronics and Photovoltaics
- Machine Learning in Materials Science
- Electron and X-Ray Spectroscopy Techniques
- Fuel Cells and Related Materials
- Additive Manufacturing Materials and Processes
- Additive Manufacturing and 3D Printing Technologies
- Photovoltaic System Optimization Techniques
- Organic and Molecular Conductors Research
- Optical measurement and interference techniques
- Olfactory and Sensory Function Studies
- biodegradable polymer synthesis and properties
- Polymer Nanocomposites and Properties
- Thermography and Photoacoustic Techniques
- Image Processing Techniques and Applications
- Advanced X-ray and CT Imaging
- Photovoltaic Systems and Sustainability
- Hydrogen embrittlement and corrosion behaviors in metals
- Photochromic and Fluorescence Chemistry
- Advanced Sensor and Energy Harvesting Materials
- Image Processing and 3D Reconstruction
Case Western Reserve University
2020-2025
Lawrence Livermore National Laboratory
2023-2025
Drexel University
2023
Temple University
2015-2019
Understanding pitting corrosion is critical, yet its kinetics and morphology remain challenging to study from X‐ray computed tomography (XCT) due manual segmentation barriers. To address this, an automated pipeline leveraging deep learning for efficient large‐scale XCT analysis developed, revealing new insights. The enables pit segmentation, 3D reconstruction, statistical characterization, a topological transformation visualization. applied 87 648 images capturing commercial purity aluminum...
<title>Abstract</title> Automated high-throughput screening is accelerating and changing the way we discover design world around us. High-throughput screening, in which robotic liquid solid handling systems investigate chemical material combinations, critical to next big leap scientific advancement. Because high viscosity materials are difficult for liquid-handling systems, researchers fields like polymer composite chemistry still need synthesize, mix, cast, characterize formulations by...
Abstract Phase transformations are a challenging problem in materials science, which lead to changes properties and may impact performance of material systems various applications. We introduce general framework for the analysis particle growth kinetics by utilizing concepts from machine learning graph theory. As model system, we use image sequences atomic force microscopy showing crystallization an amorphous fluoroelastomer film. To identify crystalline particles matrix track temporal...
Abstract Metal-based additive manufacturing requires active monitoring solutions for assessing part quality. Multiple sensors and data streams, however, generate large heterogeneous sets that are impractical manual assessment characterization. In this work, an automated pipeline is developed enables feature extraction from high-speed camera video multi-modal analysis. The framework removes the need through utilization of deep learning techniques training models in a weakly supervised...
Degradation pathway models constructed using network structural equation modeling (netSEM) are used to study degradation modes and pathways active in photovoltaic (PV) system variants exposure conditions of high humidity temperature. This data-driven technique enables the exploration simultaneous pairwise multiple regression relationships between variables which several specific conditions. Durable degrading identified from netSEM mechanisms pathways, along with potential ways mitigate these...
Tetraphenylazadipyrromethenes (ADPs) are attractive near-infrared (NIR) dyes because of their simple synthesis and exceptional optical electronic properties. The typical BF2 less explored intramolecular BO coordination planarize the molecule, making them promising π-conjugated materials for organic applications. However, use has been mostly limited to vacuum-deposited devices. To improve properties, we synthesized characterized a series ADP complexes used density functional theory...
Abstract Laser-powder bed fusion (L-PBF) is a popular additive manufacturing (AM) process with rich data sets coming from both in situ and ex sources. Data derived multiple measurement modalities an AM capture unique features but often have different encoding methods; the challenge of registration not directly intuitive. In this work, we address between modalities. Large spaces must be organized machine-compatible method to maximize scientific output. FAIR (findable, accessible,...
Abstract Electrospun biopolymer fibers are utilized in a wide variety of industries such as tissue engineering, sensors, drug delivery, membrane filtration, and protective membranes. The chitosan, the partially N ‐deacetylated derivative chitin, which has been focus many studies, contains amine or hydroxyl functionalities that may be substituted with number chemistries carboxylate, benzene, cyano groups. Modified chitosan solutions often challenging to electrospin, an entirely new set...
The homoleptic zinc(II) complex of [2,8-di(1-naphthylethynyl) 3,7-diphenyl 1,9-(4-hexylphenyl)azadipyrromethene (ZnL2)2] is a promising non-planar non-fullerene acceptor for organic photovoltaic applications, but it has relatively low electron mobility that may limit its performance. Here, we explored the fluorination peripheral aryl groups to increase intermolecular cofacial π–π stacking interactions, which are desirable transport. Complexes with fluorine on distal phenyls [Zn(1F-L2)2],...
Abstract Using Direct Ink Write (DIW) technology in a rapid and large-scale production requires reliable quality control for printed parts. Data streams generated during printing, such as print mechatronics, are massive diverse which impedes extracting insights. In our study protocol approach, we developed data-driven workflow to understand the behavior of sensor-measured X- Y- axes positional errors with process parameters, velocity control. We uncovered patterns showing that instantaneous...
Side chain engineering of non-planar zinc( ii ) complexes azadipyrromethene enables either very high hole mobility, electron mobility or both as estimated by the space-charge limited current (SCLC) method in diodes.
Advancements of solid polymer electrolytes are critical for the next generation lithium-ion batteries within our highly energy-dependent society. Research techniques that speed up materials discovery crucial to meet this need. Towards end we have invented a Studying-Polymers-On-a-Chip (SPOC) platform integrates active mixing direct ink-write 3D printing, in-situ impedance characterization and machine learning experimental planning systems. Collectively, technology enables automated...
Zinc(II) complexes of tetraphenylazadipyrromethenes are potential non-planar n-type conjugated materials. To tune the properties, we installed 5-quinolylethynyl groups at pyrrolic positions. Compared to complex with 1-napthylethynyl, found evidence for stronger intermolecular interactions in new complex, including much higher overlap integrals crystals. X-ray analysis revealed unconventional C–H···N hydrogen bonding between two quinolyls neighboring molecules, pointing a strategy development...
ct: PV service lifetime prediction (SLP) enables accurate calculation of levelized cost energy (LCOE), which is crucial to rationalizing investment and installation. However, SLP challeging since reliability in the field affected by many combined factors, including various environmental stresses module quality. In order map out active degradation mechanisms pathways that best resemble real world conditions, we introduce framework a study protocol use network models fitted data, enable...