About

Dr. Jason Patrick is an Assistant Professor in the Department of Civil, Construction, and Environmental Engineering at North Carolina State University. His research interests focus on the development of multifunctional, structural composites to address interdisciplinary challenges in modern aerospace, automotive, civil, and naval applications. He has a background in Civil Engineering, having received both his B.S. and M.S. from North Carolina State University, and earned a Ph.D. in Structural Engineering from the University of Illinois at Urbana-Champaign. Prior to his current faculty position, he was a postdoctoral fellow at the Beckman Institute for Advanced Science and Technology on the Illinois campus. Dr. Patrick currently teaches courses in Structural Analysis and has contributed to numerous publications in the field of structural composites, self-healing materials, and microvascular systems.

Research topics

• Composite material
• Materials science
• Nanotechnology
• Mechanical engineering
• Metallurgy
• Optoelectronics

Selected publications

• Self-healing for the long haul: In situ automation delivers century-scale fracture recovery in structural composites

  Proceedings of the National Academy of Sciences · 2026-01-09 · 1 citations

  articleOpen accessSenior authorCorresponding

  Nature's structural composites, such as bone and wood, achieve mechanical performance through hierarchical multimaterial design. Though, their real vantage lies in the exceptional ability to repeatedly heal after damage. Synthetic fiber-reinforced polymer (FRP) composites also leverage material hierarchy via fibrous reinforcement encapsulated within a polymer matrix, maximizing stiffness and strength. However, the layered architecture of laminated FRP composites makes them vulnerable to interlaminar delamination-debonding of fibers from the matrix-which significantly compromises structural integrity. Recently, we introduced a self-healing strategy via in situ heating, where soft yet tough thermoplastic inclusions achieve interlaminar fracture recovery via polymer chain re-entanglement, i.e., thermal remending. Here, in our latest embodiment, by automating in situ thermo-mechanical experiments, we achieve an order-of-magnitude enhancement in self-healing repeatability-reaching an unprecedented 1,000 cycles. Healing begins at 175% and slowly declines to 60% of the mode-I fracture resistance of a plain (nonhealing) composite, revealing unique chemo-physical mechanisms that govern this behavior. Both fiber-debris accumulation in the molten poly(ethylene-co-methacrylic acid) (EMAA) healing agent, and waning interfacial chemical reactions between the EMAA and epoxy matrix, contribute. A Weibull distribution capturing this complex fracture recovery predicts an asymptotic healing limit above 40%, suggesting sustained repair is possible. Translating these newfound thermal remending results into real-world context, a modest quarterly self-healing schedule could maintain interlaminar fracture repair of FRP composites for over 125 y-well beyond the typical design life of many modern structures including aircraft and wind turbines. Thus, this latest self-healing paradigm effectively eliminates delamination as a failure mode.

  PublisherDOI

• Integrated damage sensing and self-healing in polymers and composites: Progress and opportunities

  Journal of Intelligent Material Systems and Structures · 2025-08-08 · 1 citations

  articleSenior authorCorresponding

  Biological materials self-regulate throughout their lifetime, controlling cellular proliferation and mitigating damage for greater longevity through a coordinated effort of sensing and self-repair. In contrast, synthetic materials generally serve a predetermined purpose and lack the autonomic control necessary for environmental adaptability. Polymeric materials can greatly benefit from bioinspired attributes to last longer and offset their negative environmental impacts from petroleum precursors and end-of-life waste accumulation. Fiber-reinforced polymer (FRP) composites, in particular, which are increasingly used in large structures (e.g., aircraft, wind turbines) and inherently difficult to recycle given their heterogeneous makeup, are well poised to further global sustainability efforts. However, to date, intelligent material systems with integrated damage sensing and self-healing functionality are largely limited to soft polymers. In this article, we examine sensing/healing attributes in living materials and compare them with synthetic strategies that have evolved over the past 20+years. We highlight fundamental features to attain autonomous mechanical stasis and provide key insights that reveal immediate opportunities for overcoming outstanding challenges.

  PublisherDOI

• Mobile-Based Multi-Output Animal Taxonomy Classification Using CNN with Edge and Cloud Deployment

  Journal of Applied Informatics and Computing · 2025-10-08

  articleOpen access1st authorCorresponding

  Distinguishing animals that appear visually similar but belong to different species or taxonomic groups, such as Eurasian and house sparrows, koi and common carp, or leopard cat and domestic cat, remains challenging and hinders biodiversity education. This study develops a Convolutional Neural Network (CNN)-based multi-output, multi-class taxonomy classification system capable of identifying seven animal species across five taxonomic levels (class, order, family, genus, species), producing 35 possible outputs. The dataset comprised 6,998 images from public sources. Among various configurations, the best-performing model (D3-M2), trained using the High Dataset with 256×256 input size, 0.2 dropout, and four hidden layers, achieved 90.15% average accuracy, the highest F1-score at the family level (98.11%), and 95.99% at the species level. Slightly lower species-level performance was due to high visual similarity among particular species. Edge AI deployment offered faster inference (0.17s) and offline capability, making it ideal for field use. Real-world testing under bright and low light at 30, 60, and 100 cm showed higher accuracy (64.8%) than low light (57.1%), with the most stable performance at 60 cm. However, limitations include an imbalanced dataset and limited environmental variation affecting species-level accuracy. Future work will focus on expanding dataset diversity and employing advanced architectures to improve fine-grained classification. This system offers a practical tool for biodiversity education and species identification, particularly in field environments where rapid, offline, and accurate classification is essential.

  PublisherOA PDFDOI

• Tailoring interlaminar shear and mode-I fracture behavior in fiber-composites via soft self-healing thermoplastic inclusions

  Composites Part A Applied Science and Manufacturing · 2025-02-27 · 7 citations

  articleSenior authorCorresponding
  PublisherDOI

• Effect of Temperature-Dependent Material Properties on Thermal Regulation in Thin Microvascular Composites

  International Journal of Applied and Computational Mathematics · 2025-02-23 · 1 citations

  article
  PublisherDOI

• An integrated microstructure reconstruction and meshing framework for finite element modeling of woven fiber-composites

  Computer Methods in Applied Mechanics and Engineering · 2024-02-08 · 14 citations

  articleOpen access

  Critical to finite element (FE) analysis of fiber-reinforced composites is accurately reproducing microstructural features via high-quality meshes such that the material heterogeneity and anisotropy are properly captured. Here we present an integrated computational framework for generating realistic FE models of woven composites with high fiber volume fractions (>50%). This framework relies on a virtual microstructure reconstruction algorithm that first generates a geometric model of loosely-woven yarns (i.e., bundles of fibers), followed by performing an FE compaction simulation to create the final textile composite microstructure. A non-iterative meshing algorithm, i.e., conforming to interface structured adaptive mesh refinement (CISAMR), has been adapted to automatically transform synthesized microstructures into conforming FE meshes. CISAMR can handle challenging geometrical features such as thin resin interstices and yarn interpenetrations (an artifact of the FE compaction) without the need to reprocess the digital geometry before mesh generation. We show that the homogenized elastic moduli obtained from FE simulations of an 8-harness satin woven composite laminate agree well with experimental measurements (within 3%), thereby validating the accuracy of the framework. We also present several other mechanical analysis examples, including a nonlinear damage simulation, that further demonstrate the ability of this framework to construct high-fidelity FE models of intricate woven composites with varying 2D and 3D woven architectures.

  PublisherDOI

• Transient topology optimization for efficient design of actively cooled microvascular materials

  Structural and Multidisciplinary Optimization · 2024-03-25 · 3 citations

  articleOpen access

  Abstract Microvascular materials containing internal microchannels are able to achieve multi-functionality by flowing different fluids through vasculature. Active cooling is one application to protect structural components and devices from thermal overload, which is critical to modern technology including electric vehicle battery packaging and solar panels on space probes. Creating thermally efficient vascular network designs requires state-of-the-art computational tools. Prior optimization schemes have only considered steady-state cooling, rendering a knowledge gap for time-varying heat transfer behavior. In this study, a transient topology optimization framework is presented to maximize the active-cooling performance and mitigate computational cost. Here, we optimize the channel layout so that coolant flowing within the vascular network can remove heat quickly and also provide a lower steady-state temperature. An objective function for this new transient formulation is proposed that minimizes the area beneath the average temperature versus time curve to simultaneously reduce the temperature and cooling time. The thermal response of the system is obtained through a transient Geometric Reduced Order Finite Element Model (GRO-FEM). The model is verified via a conjugate heat transfer simulation in commercial software and validated by an active-cooling experiment conducted on a 3D-printed microvascular metal. A transient sensitivity analysis is derived to provide the optimizer with analytical gradients of the objective function for further computational efficiency. Example problems are solved demonstrating the method’s ability to enhance cooling performance along with a comparison of transient versus steady-state optimization results. In this comparison, both the steady-state and transient frameworks delivered different designs with similar performance characteristics for the problems considered in this study. This latest computational framework provides a new thermal regulation toolbox for microvascular material designers.

  PublisherOA PDFDOI

• Effect of temperature-dependent material properties on thermal regulation in microvascular composites

  arXiv (Cornell University) · 2024-01-06

  preprintOpen access

  Fiber-reinforced composites (FRC) provide structural systems with unique features that appeal to various civilian and military sectors. Often, one needs to modulate the temperature field to achieve the intended functionalities (e.g., self-healing) in these lightweight structures. Vascular-based active cooling offers one efficient way of thermal regulation in such material systems. However, the thermophysical properties (e.g., thermal conductivity, specific heat capacity) of FRC and their base constituents depend on temperature, and such structures are often subject to a broad spectrum of temperatures. Notably, prior active cooling modeling studies did not account for such temperature dependence. Thus, the primary aim of this paper is to reveal the effect of temperature-dependent material properties -- obtained via material characterization -- on the qualitative and quantitative behaviors of active cooling. By applying mathematical analysis and conducting numerical simulations, we show this dependence does not affect qualitative attributes, such as minimum and maximum principles (in the same spirit as \textsc{Hopf}'s results for elliptic partial differential equations). However, the dependence slightly affects quantitative results, such as the mean surface temperature and thermal efficiency. The import of our study is that it provides a deeper understanding of thermal regulation systems under practical scenarios and can guide researchers and practitioners in perfecting associated designs.

  PublisherOA PDFDOI

• Unraveling chemical and rheological mechanisms of self-healing with EMAA thermoplastics in fiber-reinforced epoxy composites

  Composites Part A Applied Science and Manufacturing · 2024-05-22 · 13 citations

  articleOpen accessSenior authorCorresponding
  PublisherOA PDFDOI

• A methodology for measuring heat transfer coefficient and self-similarity of thermal regulation in microvascular material systems

  International Journal of Heat and Mass Transfer · 2023-09-13 · 4 citations

  articleSenior authorCorresponding
  PublisherDOI

Frequent coauthors

• Nancy R. Sottos

  University of Illinois Urbana-Champaign

  21 shared

• Scott R. White

  20 shared

• Brett P. Krull

  University of Illinois Urbana-Champaign

  12 shared

• Jeffrey S. Moore

  University of Illinois Urbana-Champaign

  12 shared

• Kevin R. Hart

  8 shared

• Alexander D. Snyder

  Sandia National Laboratories

  8 shared

• K. B. Nakshatrala

  University of Houston

  8 shared

• Ahmad R. Najafi

  Drexel University

  5 shared

Education

• Ph.D., Structural Engineering

  University of Illinois at Urbana-Champaign

  2014

• M.S., Civil, Construction, and Environmental Engineering

  North Carolina State University

  2006

• B.S., Civil, Construction, and Environmental Engineering

  North Carolina State University

  2004