Julia K. Hoskins Data-verified
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Graduate Research Assistant
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Research Areas
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Biography and Research Information
OverviewAI-generated summary
Julia K. Hoskins is a Graduate Research Assistant at the University of Arkansas at Fayetteville. Her research focuses on the application of 3D printing technologies for creating specialized devices and materials. She has co-authored publications detailing the design of bioinspired surfaces for wear resistance and friction reduction, as well as the development of customizable 3D printed microsampling devices for neuroscience applications. Hoskins has also investigated the fabrication of high-porosity membranes with submicron pores using 3D printing for microfluidics, including multiscale 2PP and LCD techniques. Her work explores the intersection of materials science, engineering, and neuroscience, with recent publications also touching on machine learning in femtosecond laser machining and the tuning of ZnO films for dust simulant adhesion. Her scholarship metrics include an h-index of 3 across 7 publications with 28 citations.
Metrics
- h-index: 3
- Publications: 7
- Citations: 29
Selected Publications
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Co-tuning ultrathin ZnO films and programmable 3D textures to control lunar dust simulant adhesion (2026)
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Multiscale 2PP and LCD 3D Printing for High-Resolution Membrane-Integrated Microfluidic Chips (2025)
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3D Printing of High-Porosity Membranes with Submicron Pores for Microfluidics (2024)
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3D Printed Microsampling Probe for Neuroscience (2024)
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Exploring Machine Learning and Machine Vision in Femtosecond Laser Machining (2023)
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3D Printed Customizable Microsampling Devices for Neuroscience Applications (2023)
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Designing a Bioinspired Surface for Improved Wear Resistance and Friction Reduction (2021)
Collaboration Network
Top Collaborators
- Designing a Bioinspired Surface for Improved Wear Resistance and Friction Reduction
- 3D Printed Customizable Microsampling Devices for Neuroscience Applications
- 3D Printing of High-Porosity Membranes with Submicron Pores for Microfluidics
- Exploring Machine Learning and Machine Vision in Femtosecond Laser Machining
- 3D Printed Microsampling Probe for Neuroscience
Showing 5 of 6 shared publications
- 3D Printed Customizable Microsampling Devices for Neuroscience Applications
- 3D Printed Microsampling Probe for Neuroscience
- Multiscale 2PP and LCD 3D Printing for High-Resolution Membrane-Integrated Microfluidic Chips
- 3D Printed Customizable Microsampling Devices for Neuroscience Applications
- 3D Printed Microsampling Probe for Neuroscience
- Multiscale 2PP and LCD 3D Printing for High-Resolution Membrane-Integrated Microfluidic Chips
- Exploring Machine Learning and Machine Vision in Femtosecond Laser Machining
- Co-tuning ultrathin ZnO films and programmable 3D textures to control lunar dust simulant adhesion
- Co-tuning ultrathin ZnO films and programmable 3D textures to control lunar dust simulant adhesion
- Co-tuning ultrathin ZnO films and programmable 3D textures to control lunar dust simulant adhesion
- Co-tuning ultrathin ZnO films and programmable 3D textures to control lunar dust simulant adhesion
- Co-tuning ultrathin ZnO films and programmable 3D textures to control lunar dust simulant adhesion
- Co-tuning ultrathin ZnO films and programmable 3D textures to control lunar dust simulant adhesion
- Co-tuning ultrathin ZnO films and programmable 3D textures to control lunar dust simulant adhesion
- Co-tuning ultrathin ZnO films and programmable 3D textures to control lunar dust simulant adhesion
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