Advanced composites have gained significant attention across various industries, including aerospace, automotive, clean energy, and healthcare, owing to their exceptional mechanical properties and versatility. Fiber-reinforced polymer (FRP) composites, particularly those reinforced with carbon fibers, are extensively used as structural materials in spacecraft, aircraft, high-performance vehicles, and wind turbines due to their high strength-to-weight ratios, stiffness, durability, and tailorable mechanical characteristics. In healthcare, the advent of additive manufacturing (3D printing) has expanded the utility of advanced composites, enabling precise customization of components to meet patient-specific needs while offering design flexibility and ease of fabrication. Despite these advantages, several challenges hinder the broader adoption of advanced composites. Critical issues include enhancing the delamination resistance and electrical conductivity of FRP composites, as well as improving the mechanical performance of 3D-printed materials while reducing weight and material waste. This research seeks to address these challenges through innovative solutions: (1) reducing carbon fiber-reinforced polymer (CFRP) delamination and enhancing electrical conductivity by incorporating polyamide (PA) and carbon non-woven veils; (2) improving the mechanical properties of digital light processing (DLP) 3D-printed materials via the addition of graphite nanoparticles; and (3) applying a novel, machine learning-aided analysis and printing method to reduce structural weight and material usage without compromising necessary mechanical integrity. The anticipated outcomes of this study aim to advance the design, performance, and application of advanced composites across these critical sectors, addressing current limitations and unlocking new possibilities for innovation.
","abstract_html":"<p>Advanced composites have gained significant attention across various industries, including aerospace, automotive, clean energy, and healthcare, owing to their exceptional mechanical properties and versatility. Fiber-reinforced polymer (FRP) composites, particularly those reinforced with carbon fibers, are extensively used as structural materials in spacecraft, aircraft, high-performance vehicles, and wind turbines due to their high strength-to-weight ratios, stiffness, durability, and tailorable mechanical characteristics. In healthcare, the advent of additive manufacturing (3D printing) has expanded the utility of advanced composites, enabling precise customization of components to meet patient-specific needs while offering design flexibility and ease of fabrication. Despite these advantages, several challenges hinder the broader adoption of advanced composites. Critical issues include enhancing the delamination resistance and electrical conductivity of FRP composites, as well as improving the mechanical performance of 3D-printed materials while reducing weight and material waste. This research seeks to address these challenges through innovative solutions: (1) reducing carbon fiber-reinforced polymer (CFRP) delamination and enhancing electrical conductivity by incorporating polyamide (PA) and carbon non-woven veils; (2) improving the mechanical properties of digital light processing (DLP) 3D-printed materials via the addition of graphite nanoparticles; and (3) applying a novel, machine learning-aided analysis and printing method to reduce structural weight and material usage without compromising necessary mechanical integrity. The anticipated outcomes of this study aim to advance the design, performance, and application of advanced composites across these critical sectors, addressing current limitations and unlocking new possibilities for innovation.</p>","abstract_has_math":false,"creators":["Narongdej, Poom"],"institution":null,"degree_name":"Engineering and Industrial Applied Mathematics Joint PhD with California State University Long Beach, PhD","degree_level":"Open Access Dissertation","degree_discipline":"Institute of Mathematical Sciences","degree_department":null,"school":null,"contributors":["Sara Moghtadernejad","Qidi Peng","Marina Chugunova"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2025,"date_issued":"2025-01-01T08:00:00Z","date_published":"2025-01-01T08:00:00Z","updated_at":"2026-07-24T01:41:09Z","subjects":["3D printing","Advanced composites","Lattice structures","Machine learning","Mechanical properties","Nanocomposites","Engineering Science and Materials","Mathematics"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://scholarship.claremont.edu/cgu_etd/987","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Sara Moghtadernejad","Qidi Peng","Marina Chugunova"]},{"key":"dc:creator","label":"Author","values":["Narongdej, Poom"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2025-06-17T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Institute of Mathematical Sciences"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Open Access Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Engineering and Industrial Applied Mathematics Joint PhD with California State University Long Beach, PhD"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["3D printing","Advanced composites","Lattice structures","Machine learning","Mechanical properties","Nanocomposites","Engineering Science and Materials","Mathematics"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://scholarship.claremont.edu/cgu_etd/987"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Advanced composites have gained significant attention across various industries, including aerospace, automotive, clean energy, and healthcare, owing to their exceptional mechanical properties and versatility. Fiber-reinforced polymer (FRP) composites, particularly those reinforced with carbon fibers, are extensively used as structural materials in spacecraft, aircraft, high-performance vehicles, and wind turbines due to their high strength-to-weight ratios, stiffness, durability, and tailorable mechanical characteristics. In healthcare, the advent of additive manufacturing (3D printing) has expanded the utility of advanced composites, enabling precise customization of components to meet patient-specific needs while offering design flexibility and ease of fabrication. Despite these advantages, several challenges hinder the broader adoption of advanced composites. Critical issues include enhancing the delamination resistance and electrical conductivity of FRP composites, as well as improving the mechanical performance of 3D-printed materials while reducing weight and material waste. This research seeks to address these challenges through innovative solutions: (1) reducing carbon fiber-reinforced polymer (CFRP) delamination and enhancing electrical conductivity by incorporating polyamide (PA) and carbon non-woven veils; (2) improving the mechanical properties of digital light processing (DLP) 3D-printed materials via the addition of graphite nanoparticles; and (3) applying a novel, machine learning-aided analysis and printing method to reduce structural weight and material usage without compromising necessary mechanical integrity. The anticipated outcomes of this study aim to advance the design, performance, and application of advanced composites across these critical sectors, addressing current limitations and unlocking new possibilities for innovation.
"]},{"key":"dc:title","label":"Title","values":["Enhancement of Mechanical, Structural, and Electrical Properties in Advanced Composites and Vat Photopolymerized 3D Printing Nanocomposites"]}]}],"canonical_facts":{"dc:contributor":["Sara Moghtadernejad","Qidi Peng","Marina Chugunova"],"dc:creator":["Narongdej, Poom"],"dc:date.available":["2025-06-17T07:00:00Z"],"dc:description.abstract":["Advanced composites have gained significant attention across various industries, including aerospace, automotive, clean energy, and healthcare, owing to their exceptional mechanical properties and versatility. Fiber-reinforced polymer (FRP) composites, particularly those reinforced with carbon fibers, are extensively used as structural materials in spacecraft, aircraft, high-performance vehicles, and wind turbines due to their high strength-to-weight ratios, stiffness, durability, and tailorable mechanical characteristics. In healthcare, the advent of additive manufacturing (3D printing) has expanded the utility of advanced composites, enabling precise customization of components to meet patient-specific needs while offering design flexibility and ease of fabrication. Despite these advantages, several challenges hinder the broader adoption of advanced composites. Critical issues include enhancing the delamination resistance and electrical conductivity of FRP composites, as well as improving the mechanical performance of 3D-printed materials while reducing weight and material waste. This research seeks to address these challenges through innovative solutions: (1) reducing carbon fiber-reinforced polymer (CFRP) delamination and enhancing electrical conductivity by incorporating polyamide (PA) and carbon non-woven veils; (2) improving the mechanical properties of digital light processing (DLP) 3D-printed materials via the addition of graphite nanoparticles; and (3) applying a novel, machine learning-aided analysis and printing method to reduce structural weight and material usage without compromising necessary mechanical integrity. The anticipated outcomes of this study aim to advance the design, performance, and application of advanced composites across these critical sectors, addressing current limitations and unlocking new possibilities for innovation.
"],"dc:identifier":["https://scholarship.claremont.edu/cgu_etd/987"],"dc:subject":["3D printing","Advanced composites","Lattice structures","Machine learning","Mechanical properties","Nanocomposites","Engineering Science and Materials","Mathematics"],"dc:title":["Enhancement of Mechanical, Structural, and Electrical Properties in Advanced Composites and Vat Photopolymerized 3D Printing Nanocomposites"],"thesis:degree_discipline":["Institute of Mathematical Sciences"],"thesis:degree_level":["Open Access Dissertation"],"thesis:degree_name":["Engineering and Industrial Applied Mathematics Joint PhD with California State University Long Beach, PhD"]},"updated_at":"2026-07-24T01:41:09Z"}