Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “REINFORCEMENT”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Aqueous-Based Polyimine Functionalization of Cellulose Nanofibrils for Effective Drying and Polymer Composite Reinforcement

Here a simple strategy was developed to synthesize polyimine-coated cellulose nanofibrils (CNF) for effective CNF drying and composite reinforcement. The polyimine was synthesized in an aqueous medium using a selective hydrophilic and hydrophobic component that forces the polyimine to precipitate, which prevents the reverse imine reaction. The polyimine coating allowed the CNF to be easily oven-dried while maintaining a fibrillar morphology to provide mechanical reinforcement in poly(ethylene terephthalate glycol) (PETG) composites. In comparison, poor mechanical performance and a heterogeneous fracture surface were observed when the coated CNF were incorporated into poly(l-lactide) (PLA) composites. It is hypothesized that intermolecular aromatic–aromatic interactions are formed at the interface between fibers and the polymer matrix in the PETG system, while no such phenomena occur in the PLA system. Overall, this facile strategy to produce modified, easily dried CNF can be adapted to produce polyimine-coated CNF with unique functionalities that are useful in a range of applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Origin of Heating-Induced Softening and Enthalpic Reinforcement in Elastomeric Nanocomposites

Molecular simulations demonstrate that the enthalpic softening of elastomeric nanocomposites upon heating can arise naturally from a Poisson’s ratio mismatch between elastomer and nanoparticle networks, providing a more parsimonious explanation for this phenomenon than the widely accepted interpretation based on glassy interparticle bridging. Despite a century of use, the mechanism of nanoparticle-driven mechanical reinforcement of elastomers is unresolved. Here, a major hypothesis attributes it to glassy interparticle bridges, supported by an observed inversion of the variation of the modulus E(T) on heating – from entropic stiffening in elastomers to enthalpic softening in nanocomposites. Here, molecular simulations reveal that elastomer enthalpic softening can instead emerge from a competition over the preferred volumes between elastomer and nanoparticulate networks. A theory for this competition accounting for softening of the bulk modulus on heating predicts the simulated E(T) inversion, suggesting that reinforcement is driven by a volume-competition mechanism unique to cocontinuous systems of soft and rigid networks.

Biopolymers↗
DOE OSTI2026

Chemical Recycling of Carbon Fiber-Reinforced Nylon Composites

Nylon-based fiber-reinforced composites are widely used in various sectors due to their strength, durability, and lightweight properties. Despite their widespread use, recycling these composites is difficult due to the inability to separate fibers and thermal instability of nylon at high temperatures. Consequently, most nylon composites are landfilled, leading to significant economic loss. Current fiber recovery methods (i.e., pyrolysis) are energetically inefficient and preclude recovery of the matrix. Dissolution methods, such as using hexafluoroisopropanol (HFIP), allow recovery of polymer and fiber but are economically taxing and require extensive safety infrastructure. Herein we report tailored glycolysis of nylon-6 composites, resulting in separated constituent fibers and nylon-6 oligomers. Deconstruction kinetics reveal nylon’s molecular weight reductions from 32,600 to 2000 g/mol, while SEM and tensile testing confirm recovered fiber integrity. In conclusion, this approach offers a pathway to reclaim high-value materials from nylon composites, providing a strategy for the chemical recycling of fiber-reinforced composites.

Zheng, Jackie [Univ. of Tennessee, Knoxville, TN (↗
DOE OSTI2020

High-Strength Polylactic Acid (PLA) Biocomposites Reinforced by Epoxy-Modified Pine Fibers

The stiffness and tensile strength of biopolymers (e.g., polylactic acid (PLA)) are less than desirable for load-bearing applications in their neat form. The use of natural fibers as reinforcements for composites (for large-scale three-dimensional (3D) printing) has expanded rapidly, attributable to their low weight, low cost, high stiffness, and renewable nature. Silane and acid/alkali are typically used to modify the surface of natural fibers to improve the fiber/polymer interfacial adhesion. In this study, a simple method of impregnation was developed to modify pine fibers (loblolly, mesh size of 90–180 μm, 30 wt %) with a solvent-borne epoxy to reinforce PLA. As a benefit of the epoxy modification (0.5–10 wt %), the tensile strengths and Young’s moduli of the epoxy-modified pine/PLA composites increased by up to 20 and 82%, respectively, as compared to that of neat PLA. Furthermore, the epoxy-modified pine/PLA composites, with an optimum epoxy modification (1.0 wt %), had fewer voids on the fracture surface as compared with pine/PLA composites without the modification of pine fibers via epoxy. Finally, results confirmed that epoxy partially penetrated the pore/hollow inner structures of pine fibers and improved the fiber/matrix interfacial adhesion. Epoxy modification is found to be a simple and effective technique to improve the properties of biocomposites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Assessing Adaptive Irrigation Impacts on Water Scarcity in Nonstationary Environments—A Multi‐Agent Reinforcement Learning Approach

Abstract One major challenge in water resource management is to balance the uncertain and nonstationary water demands and supplies caused by the changing anthropogenic and hydroclimate conditions. To address this issue, we developed a reinforcement learning agent‐based modeling (RL‐ABM) framework where agents (agriculture water users) are able to learn and adjust water demands based on their interactions with the water systems. The intelligent agents are created by a reinforcement learning algorithm adapted from the Q‐learning algorithm. We illustrated this framework in a case study where the RL‐ABM is two‐way coupled with the Colorado River Simulation System (CRSS), a long‐term planning model used for the administration of the Colorado River Basin, for assessing agriculture water uses impacts on water scarcity. Seventy‐eight intelligent agents are simulated, which can be grouped into three categories based on their parameter values: the “aggressive” (swift actions; low regrets), the “forward‐looking conservative” (mild actions; high regrets; fast learning), and the “myopic conservative” (mild actions; median regrets; slow learning). The ABM‐CRSS results showed that the major reservoirs in the Upper Colorado Basin might experience more frequent water shortages due to the increasing water uses compared to the original CRSS results. If the drought continues, the case study also demonstrates that agents can learn and adjust their demands.

Hung, Fengwei↗
DOE OSTI2021

In situ mechanical reinforcement of polymer hydrogels via metal-coordinated crosslink mineralization

Biological organic-inorganic materials remain a popular source of inspiration for bioinspired materials design and engineering. Inspired by the self-assembling metal-reinforced mussel holdfast threads, we tested if metal-coordinate polymer networks can be utilized as simple composite scaffolds for direct in situ crosslink mineralization. Starting with aqueous solutions of polymers end-functionalized with metal-coordinating ligands of catechol or histidine, here we show that inter-molecular metal-ion coordination complexes can serve as mineral nucleation sites, whereby significant mechanical reinforcement is achieved upon nanoscale particle growth directly at the metal-coordinate network crosslink sites.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Avoiding fusion plasma tearing instability with deep reinforcement learning

For stable and efficient fusion energy production using a tokamak reactor, it is essential to maintain a high-pressure hydrogenic plasma without plasma disruption. Therefore, it is necessary to actively control the tokamak based on the observed plasma state, to manoeuvre high-pressure plasma while avoiding tearing instability, the leading cause of disruptions. This presents an obstacle-avoidance problem for which artificial intelligence based on reinforcement learning has recently shown remarkable performance. However, the obstacle here, the tearing instability, is difficult to forecast and is highly prone to terminating plasma operations, especially in the ITER baseline scenario. Previously, we developed a multimodal dynamic model that estimates the likelihood of future tearing instability based on signals from multiple diagnostics and actuators. Here we harness this dynamic model as a training environment for reinforcement-learning artificial intelligence, facilitating automated instability prevention. We demonstrate artificial intelligence control to lower the possibility of disruptive tearing instabilities in DIII-D, the largest magnetic fusion facility in the United States. The controller maintained the tearing likelihood under a given threshold, even under relatively unfavourable conditions of low safety factor and low torque. In particular, it allowed the plasma to actively track the stable path within the time-varying operational space while maintaining H-mode performance, which was challenging with traditional preprogrammed control. This controller paves the path to developing stable high-performance operational scenarios for future use in ITER.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Toward a circular economy: zero-waste manufacturing of carbon fiber-reinforced thermoplastic composites

Fiber-reinforced composites are becoming ubiquitous as a way of lightweighting in the wind, aerospace, and automotive industries, but current recycling technologies fall short of a circular economy. In this work, fiber-reinforced composites made of recycled carbon fiber and polyphenylene sulfide were recycled and remanufactured using common processing technologies such as compression and injection molding. An industrially viable size-exclusive sieving technique was used to retain fiber length and reduce variability in the mechanical properties of the remanufactured composites. Fiber length reduction alone could not explain the strength reductions apparent in the composites, which we propose are due to microstructural inhomogeneity as defined by poor dispersion of the fibers. Future recycling efforts must focus on fiber length retention and good dispersion to make composite remanufacturing a viable path toward a circular economy.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Harnessing biomimetic cryptic bonds to form self-reinforcing gels

Cryptic sites, which lay hidden in folded biomolecules, become exposed by applied force and form new bonds that reinforce the biomaterial. While these binding interactions effectively inhibit mechanical deformation, there are few synthetic materials that harness mechano-responsive cryptic sites to forestall damage. Here, we develop a computational model to design polymer gels encompassing cryptic sites and a lower critical solution temperature (LCST). LCST gels swell with a decrease in temperature, thereby generating internal stresses within the sample. The gels also encompass loops held together by the cryptic sites, as well as dangling chains with chemically reactive ends. A decrease in temperature or an applied force causes the loops to unfold and expose the cryptic sites, which then bind to the dangling chains. We show that these binding interactions act as “struts” that reinforce the network, as indicated by a significant decrease in the volume of the gel (from 44% to 80%) and shifts in the volume phase transition temperature. Once the temperature is increased or the deformation is removed, the latter “cryptic bonds” are broken, allowing the loops to refold and the gel to return to its original state. These findings provide guidelines for designing polymer networks with reversible, mechano-responsive bonds, which allow gels to undergo a self-stiffening behavior in response to a temperature-induced internal stress or external force. When applied as a coating, these gels can prevent the underlying materials from undergoing damage and thus, extend the lifetime of the system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

High-strength 3D printed poly(lactic acid) composites reinforced by shear-aligned polymer-grafted cellulose nanofibrils

This work demonstrates the application of pilot-scale surface functionalization of cellulose nanofibrils (CNFs) by aqueous grafting-through polymerization and subsequent spray drying in 3D printed poly(lactic acid) (PLA) composites. Grafted-CNF composites attain an ultimate tensile strength of 88 ± 3 MPa and a tensile modulus of elasticity of 7.8 ± 1.3 GPa in the printing direction at 20 wt% reinforcement loading. These increases, 42% and 139% over neat PLA, respectively, represent the strongest reported 3D printed CNF/PLA composite to date in the literature. The mechanisms behind these improvements are investigated by comparisons to neat PLA and unmodified spray-dried CNF/PLA controls using melt rheology, dynamic mechanical analysis, and assessment of the reinforcement dispersion. These experiments reveal that improved network formation and shear-induced alignment of the grafted CNFs facilitate the remarkable tensile properties of the printed composites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Cyclic olefin copolymer-based reinforced anion exchange membranes for water electrolyzers

Anion exchange membranes (AEMs) have emerged as a promising technology for water electrolysis in hydrogen production since they offer significant cost reduction in choices of electrocatalysts and bipolar plates. However, AEMs satisfying multiple requirements of high ionic conductivity, good chemical stability, robust mechanical properties, scalable synthesis, and low manufacturing costs are rare. Herein, we introduce quaternary ammonium functionalized cyclic olefin copolymers (COCs) as a new class of chemically stable and low-cost AEM materials. To further enhance the mechanical robustness, we prepared reinforced composite AEMs by impregnating the ionically functionalized COC into a mechanically robust matrix. The resulting reinforced composite membrane exhibits a high hydroxide conductivity of 127 mS cm −1 and excellent mechanical strength. In water electrolyzers, the MEA demonstrated outstanding performance, achieving a current density of 2.24 A cm −2 at 1.8 V, attributable to high conductivity, enhanced mechanical properties, and good alkaline stability of the composite membrane. These results indicate that the COC-based AEMs demonstrate good potential for application in AEM electrolyzers.

08 HYDROGEN↗
DOE OSTI2014

One-step fabrication of free-standing flexible membranes reinforced with self-assembled arrays of carbon nanotubes

Here, we report on a single step approach for fabricating free-standing polymer membranes reinforced with arrayed self-assembled carbon nanotubes (CNTs). The CNTs are self-assembled spontaneously by electrode-free DC dielectrophoresis based on surface charge templates. The electrical charge template is generated through the pyroelectric effect onto periodically poled lithium niobate ferroelectric crystals. A thermal stimulus enables simultaneously the self-assembly of the CNTs and the cross-linking of the host polymer. Examples of thin polydimethylsiloxane membranes reinforced with CNT patterns are shown.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2015

Fire resistance properties of ceramic wool fiber reinforced intumescent coatings

This research studied the effects of varied weight percentage and length of ceramic wool fiber (CWF) reinforcement to fire retardant performance of epoxy-based intumescent coating. Ten formulations were developed using ammonium polyphosphate (APP), expandable graphite (EG), melamine (MEL) and boric acid (BA). The mixing was conducted in two stages; powdered materials were grinded in Rocklabs mortar grinder and epoxy-mixed using Caframo mixer at low speed mixing. The samples were applied on mild steel substrate and exposed to 500°C heat inside Carbolite electric furnace. The char expansion and its physical properties were observed. Scanning electron microscopy (SEM) analyses were conducted to inspect the fiber dispersion, fiber condition and the cell structure of both coatings and chars produced. Thermogravimetric analyses (TGA) were conducted to study the thermal properties of the coating such as degradation temperature and residual weight. Fire retardant performance was determined by measuring backside temperature of substrate in 1-hour, 1000°C Bunsen burner test according to UL 1709 fire regime. The results showed that intumescent coating reinforced with CWF produced better fire resistance performance. When compared to unreinforced coating, formulation S6-15 significantly reduced steel temperature at approximately 34.7% to around 175°C. However, higher fiber weight percentage had slightly decreased fire retardant performance of the coating.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Development of high-speed reactive processing system for carbon fiber-reinforced polyamide-6 composite: In-situ anionic ring-opening polymerization

In order to manufacture carbon fiber-reinforced polyamide-6 (PA-6) composite, we optimized the reactive processing system. The in-situ anionic ring-opening polymerization of ε-caprolactam was utilized with proper catalyst and initiator for PA-6 matrix. The mechanical properties such as tensile strength, inter-laminar shear strength and compressive strength of the produced carbon fiber-reinforced PA-6 composite were measured, which were compared with the corresponding scanning electron microscope (SEM) images to investigate the polymer properties as well as the interfacial interaction between fiber and polymer matrix. Furthermore, kinetics of in-situ anionic ring-opening polymerization of ε-caprolactam will be discussed in the viewpoint of increasing manufacturing speed and interfacial bonding between PA-6 matrix and carbon fiber during polymerization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Reinforced dynamics for enhanced sampling in large atomic and molecular systems

A new approach for efficiently exploring the configuration space and computing the free energy of large atomic and molecular systems is proposed, motivated by an analogy with reinforcement learning. There are two major components in this new approach. Like metadynamics, it allows for an efficient exploration of the configuration space by adding an adaptively computed biasing potential to the original dynamics. Like deep reinforcement learning, this biasing potential is trained on the fly using deep neural networks, with data collected judiciously from the exploration and an uncertainty indicator from the neural network model playing the role of the reward function. Parameterization using neural networks makes it feasible to handle cases with a large set of collective variables. This has the potential advantage that selecting precisely the right set of collective variables has now become less critical for capturing the structural transformations of the system. Finally, the method is illustrated by studying the full-atom explicit solvent models of alanine dipeptide and tripeptide, as well as the system of a polyalanine-10 molecule with 20 collective variables.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Thermophysical Properties of Ti3SiC2 MAX Phase Composites with SiC Reinforcement

In the present work, dense (∼100%) Ti 3 SiC 2 composites (TSC) are processed along with 20 vol% of SiC reinforcement (TSC20) via spark plasma sintering at 1400°C, 40 MPa, 15 min, and dynamic vacuum environment. Thermal expansion of both the composites increases from RT to 1273 K and linear fitting of data yields coefficient of thermal expansion (CTE) of 9.4 × 10 −6 K −1 for TSC which decreases to 8.3 × 10 −6 K −1 for TSC20. With increase in temperature from RT to 773 K, specific heat for both TSC and TSC20 composites is observed to increase from 598-850 J.kg −1 .K −1 , whereas thermal diffusivity and thermal conductivity values decrease with testing temperature. SiC reinforcement in Ti 3 SiC 2 resulted in improved thermal diffusivity from 12.7 to 18.7 mm 2 .s −1 and thermal conductivity from ∼57 to ∼79 W.m −1 .K −1 at RT. However, with increase in temperature (773 K), thermal diffusivity and conductivity decrease, and values get closer for both TSC and TSC20 composites. Further extrapolation of thermal conductivity data showed cross-over at ∼973 K due to domination of phonon-phonon scattering and thus lower values of thermal conductivity for TSC20 than TSC. Therefore, reduced CTE and higher thermal conductivity of TSC20 make it a viable choice for applications in high temperatures.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Torrefaction of almond shell as a renewable reinforcing agent for plastics: techno-economic analyses and comparison to bioethanol process

Abstract In 2016, the US state of California alone produced nearly 3.5 billion kilograms of almonds, accounting for approximately 84% of the world’s almond production. This generated about 2.58 million metric tons (MTs) of almond residues. Almond shells are currently either burned to generate power or disposed of in landfill. Valorizing almond shells and hulls provides an opportunity to replace petroleum-derived products and divert organic material from landfill. Here we demonstrate a detailed techno-economic analysis (TEA) of an almond shell torrefaction process capable of utilizing the 520 000 MTs of almond shells produced annually in California. Our process also includes preprocessing the torrefied biomass to exploit it as a reinforcing agent for plastics. We further compared the revenue generated from the torrefied biomass and bioethanol derived from the same quantity of almond shells. We considered three different torrefaction facility scales to evaluate trade-offs between economies of scale at the facility and trucking costs to deliver almond shells. A facility that takes in 200 000 MT yr –1 of almond shells results in lower per-unit-output basis capital and operating cost relative to other smaller-scale torrefaction facilities, including 10 000 MT yr –1 and 50 000 MT yr –1 , considered for analysis in this study. The large-sale facility results in a minimum selling price (MSP) of the torrefied biomass of $311.4 MT –1 . An analogous TEA on converting almond residues into bioethanol is also investigated. The MSP of almond shell derived ethanol ($1.71 kg −1 ) is higher than that of corn ($0.48 kg −1 ) or cellulosic biomass ($0.88 kg −1 ) derived ethanol. Compared with the bioethanol route, the torrefied almond shells result in three times more revenue if utilized as a reinforcing agent for plastics.

Liu, Dupeng (ORCID:0000000269514064)↗
DOE OSTI2025

The influence of exposure to early-life adversity on agency-modulated reinforcement learning

Agency beliefs influence how humans learn from different contexts and outcomes. Research demonstrates that stressors, such as exposure to early-life adversity (ELA), are associated with both agency beliefs and learning, but how these processes interact remains unclear. The current study investigated whether exposure to ELA influences agency and interacts with reinforcement learning in adults. Replicating prior behavioral and computational work, ELA resulted in decreased learning, while increased adversity severity was associated with decreased latent agency beliefs. These findings suggest that exposure to adversity in childhood has a nuanced impact on reinforcement learning and agency beliefs in adulthood.

Neurosciences & Neurology↗