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Ozcan, Soydan [ORNL] (ORCID:0000000238254589)

Publications and source records attributed to Ozcan, Soydan [ORNL] (ORCID:0000000238254589).

8 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

A synergistic approach to improve the cellulose nanofibril dispersion in poly(lactic acid) composites as feedstocks for extrusion-based additive manufacturing

Hybrid fiber-reinforced polymer composites (HFRPs) are multifunctional materials that bear more than one characteristic benefit. In this study, hybrid cellulose fibers, e.g., pulp fiber (PF) and cellulose nanofibril (CNF), were used for reinforcing poly(lactic acid) (PLA). A synergistic approach was applied to disperse CNF. The low-surface-tension solvent (ethanol), together with PF templating, assisted the dispersion of CNF in PLA. The HFRP achieved a higher tensile strength (∼70 MPa, 29% increase from PLA) and modulus (∼7 GPa, 46% increase from PLA), as well as a higher heat deflection temperature (∼60℃, 6℃ increase compared to neat PLA), compared to single-reinforcement FRPs. Additionally, the formulation was demonstrated to be potentially suitable for large-scale additive manufacturing.

Bista, Bivek [University of Maine]↗
DOE OSTI2026

Harnessing biomass-derived reinforcements for sustainable flame-resistant composite

Bio-based composites containing natural fiber reinforcements have been integral to developing innovative, low-cost, and low-energy technologies for transportation applications in marine, automotive, and other industries. The low density of natural fibers gives these materials a high specific stiffness and strength, which can lead to significant weight savings in composites. This study focused on a specialty type of wood fiber treated with boric acid (≤ 7%) sourced from Northern White Pine in the USA, marketed as TimberFill. TimberFill is a high aspect ratio, fibrillated wood fiber that is produced commercially for wood fiber insulation; it is chemically treated to improve both its flame retardance and water resistance. In the present study, TimberFill was processed into non-woven mats using a process akin to papermaking and then infiltrated with epoxy resin. Biochar from wood waste was also incorporated into the epoxy resin as a low-cost filler and functional additive. The effects of biochar concentration on composites’ flame retardance (17% improvement in burn rate), thermal conductivity (improved by 9%), and mechanical performance (33% improvement in modulus) are herein presented. Additionally, it explores the plasticizing effect of the boric acid used in the treatment of TimberFill on the thermal and mechanical properties of the resulting composites, specifically on the thermal expansion coefficient.

Joshy, Joslin [ORNL]↗
DOE OSTI2026

HYBRID COMPOSITES VIA CO-EXTRUSION ADDITIVE MANUFACTURING-COMPRESSION MOLDING FOR PERFORMANCE OPTIMIZATION

The growing demand for hybrid polymer composites with multifunctional properties has led to the development of various hybridization techniques, such as multi-material compounding and controlled laminate stacking sequence. In this study, a novel hybrid manufacturing approach was used by integrating a multiplexing extrusion system (MExS) based on additive manufacturing with subsequent compression molding process. This technique enabled the co-extrusion of different materials during the additive manufacturing process to fabricate composites with tailored performance. The developed hybrid composite featured a skin layer of glass fiberreinforced polycarbonate (PC/GF) encapsulating a carbon fiber-reinforced acrylonitrile butadiene styrene (CF/ABS) core. The structure was engineered to promote improved thermal and impact resistance at the surface, supported by a stiff core for enhanced overall mechanical integrity. Mechanical, thermal and morphological properties of the hybrid composites were investigated to understand trade-offs in performance compared to a single-material system. The results demonstrate that this approach enables the production of multifunctional composites suitable for applications such as automotive body panels and protective housings, where a balance of weight, mechanical strength, and thermal performance is essential.

Wasti, Sanjita [ORNL]↗
DOE OSTI2026

Biochar–polymer composites for 3D printing: a review

Biochar, a bio-based co-product of biofuel production via thermochemical conversion, holds potential as a filler for polymer composites to reduce costs, improve thermomechanical properties, and aid in environmental remediation. 3D-printed biochar composites have received growing interest over the past few years but have experienced difficulties such as poor layer adhesion and nozzle clogging. Currently, no literature review examines 3D-printed biochar composites and related biochar properties in-depth. This work summarizes and discusses recent studies on 3D-printed polymer and biochar composites and examines their mechanical, thermal, and additional properties that result from each study. Technical challenges in printability, such as nozzle clogging from particle size and biochar aggregation, are also discussed. Furthermore, this work discusses the variability of biochar properties resulting from the pyrolysis conditions and feedstock choice in relation to potential 3D printing outcomes. In particular, several studies reported that high lignin feedstocks could be candidates for 3D printing. The post-processing approaches of the biochar via physical and chemical methods are also introduced. Ball milling appears to hold the most promise for physical treatments due to its tunability of particle size, surface area, and functional groups, while chemical treatments with acids or alkalis are used to tailor biochar porosity and wettability. Overall, it was determined that future research needs to be done relating biochar production and post-processing methods to resulting 3D printing parameters as the number of studies is limited.

Day, Rachel [Auburn University, Auburn, AL]↗
DOE OSTI2025

Multiplexing core & sheath extrusion system development for additive manufacturing for inner-bead multi-material capability

Single-feed polymer extruders are widely used in large-format additive manufacturing (AM) systems; however, the increasing demand for multi-material functionality within a single part has driven significant innovation in this field. One approach involves robotic pick-and-place operations, while another explores mechanical switching of feed lines during extrusion. Although robotic pick-and-drop systems offer flexibility, they introduce longer layer times during material changes, which can negatively affect the structural integrity of the part. On the other hand, mechanical feed switching causes delays in material transitions, as the existing material must be flushed before the new material emerges from the nozzle. This poses particular challenges for smaller or more intricate parts. In this study we are developing a unique multiplexing extrusion system with core & sheath nozzle that combines two extruders via co-extrusion. This allows for a unique inside and outside inner-bead (i.e., within the same bead) multi-material capability. We believe that this technology will allow for combining neat and filled materials, ductile and stronger materials, and many other combinations to address the problems aforementioned above and disrupt the AM technology creating new opportunities and opening application areas.

Tekinalp, Halil [ORNL]↗
DOE OSTI2025

Intelligent Manufacturing Support: Specialized LLMs for Composite Material Processing and Equipment Operation

Engineering educational curriculum and standards cover many material and manufacturing options. However, engineers and designers are often unfamiliar with certain composite materials or manufacturing techniques. Large language models (LLMs) could potentially bridge the gap. Their capacity to store and retrieve data from large databases provides them with a breadth of knowledge across disciplines. However, their generalized knowledge base can lack targeted, industry-specific knowledge. To this end, we present two LLM-based applications based on the GPT-4 architecture: (1) The Composites Guide: a system that provides expert knowledge on composites material and connects users with research and industry professionals who can provide additional support and (2) The Equipment Assistant: a system that provides guidance for manufacturing tool operation and material characterization. By combining the knowledge of general AI models with industry-specific knowledge, both applications are intended to provide more meaningful information for engineers. In this paper, we discuss the development of the applications and evaluate it through a benchmark and two informal user studies. The benchmark analysis uses the Rouge and Bertscore metrics to evaluate our models’ performance against GPT-4o. The results show that GPT-4o and the proposed models perform similarly or better on the ROUGE and BERTScore metrics. The two user studies supplement this quantitative evaluation by asking experts to provide qualitative and open-ended feedback about our model’s performance on a set of domain-specific questions. The results of both studies highlight a potential for more detailed and specific responses with the Composites Guide and the Equipment Assistant.

Kapoor, Gunnika [Oak Ridge National Laboratory (OR↗
DOE OSTI2025

Toolpath Optimization of Polymer Composite Additive Manufacturing AM Printed Mold to Improve Performance for Compression Molding Applications

This study explores the optimization of toolpaths for short fiber polymer composite additive manufacturing (AM) printed molds in compression molding applications, an emerging trend driven by advancements in 3D printing technology. AM printed molds offer reduced tooling costs and greater design flexibility, particularly for prototyping and low-volume production. The proposed optimization approach evaluates mold performance using two key metrics: deformation and shape accuracy. Multiple toolpaths are generated, and finite element (FE) simulations capture fiber orientation and material properties, which are then integrated into a mechanical performance model. Shape accuracy is assessed by comparing the deformed mold shape with the original using surface normals as a descriptor. The analysis identifies the toolpath that delivers the best overall performance, establishing it as the most suitable option for achieving optimal mold characteristics in compression molding applications.

Limaye, Madhura [ORNL]↗