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At least 199 records · Page 11

Transient Chemo‐Mechanical Model of Lithium Plating Impacted by External Pressure

Abstract Lithium anodes show great promise in commercial applications, but are hindered by lithium plating and dendrite growth which cause safety concerns during long‐term cell operation. Stack pressure is experimentally observed to improve cell lifetime; however, the relationship between stress and lithium deposition has remained difficult to elucidate. In this work, a transient, 3D, finite‐element model of the evolution of a lithium anode due to stripping and plating is developed. The evolution of a microscale protrusion on the anode surface is tracked over one charge‐discharge cycle with respect to stack pressure and lithium yield strength. Lithium plastic deformation, nonconformal anode‐separator contact, and separator porosity effects are accounted for. Over the course of several hours of stripping/plating, the anode surface evolves to a similar morphology under pressure regardless of the initial conditions due to lithium plastic deformation and hardening. The rate of this evolution highly depends on the applied pressure and assumed lithium yield strength.

25 ENERGY STORAGE↗

Establishment of computerized numerical databases on thermophysical and other properties of molten as well as solid materials and data evaluation and validation for generating recommended reliable reference data

The Center for Information and Numerical Data Analysis and Synthesis, (CINDAS), measures and maintains databases on thermophysical, thermoradiative, mechanical, optical, electronic, ablation, and physical properties of materials. Emphasis is on aerospace structural materials especially composites and on infrared detector/sensor materials. Within CINDAS, the Department of Defense sponsors at Purdue several centers: the High Temperature Material Information Analysis Center (HTMIAC), the Ceramics Information Analysis Center (CIAC) and the Metals Information Analysis Center (MIAC). The responsibilities of CINDAS are extremely broad encompassing basic and applied research, measurement of the properties of thin wires and thin foils as well as bulk materials, acquisition and search of world-wide literature, critical evaluation of data, generation of estimated values to fill data voids, investigation of constitutive, structural, processing, environmental, and rapid heating and loading effects, and dissemination of data. Liquids, gases, molten materials and solids are all considered. The responsibility of maintaining widely used databases includes data evaluation, analysis, correlation, and synthesis. Material property data recorded on the literature are often conflicting, diverging, and subject to large uncertainties. It is admittedly difficult to accurately measure materials properties. Systematic and random errors both enter. Some errors result from lack of characterization of the material itself (impurity effects). In some cases assumed boundary conditions corresponding to a theoretical model are not obtained in the experiments. Stray heat flows and losses must be accounted for. Some experimental methods are inappropriate and in other cases appropriate methods are carried out with poor technique. Conflicts in data may be resolved by curve fitting of the data to theoretical or empirical models or correlation in terms of various affecting parameters. Reasons (e.g. phase transitions) must be found for unusual dependence or any anomaly. Such critical evaluation involves knowledge of theory, experience in measurement, familiarity with metallurgy (microstructural behavior) and not inconsiderable judgment. An examination of typical data compiled and analyzed by CINDAS shows that the thermal conductivity of a material reported in the literature may vary by a factor of two of more; the range of reported values increases as temperature increases reflecting the difficulty of high temperature measurements. Often only estimates of melt behavior are available, despite the importance of melt properties in modeling, welding, or other solidification processes. There may be only a few measurements available for properties such as kinematic viscosity, even for widely used materials such as stainless steel. In the face of such a paucity of existing data and in a national environment where too few new data are being generated it is nonetheless the responsibility of CINDAS to select and disseminate recommended values of a wide variety of thermophysical properties.

Ho, C. Y.↗

Evidence for an Early Formation of Serenitatis Basin at 4.25 Ga Shifts Lunar Chronology

Troctolite sample 76535, collected in Serenitatis basin during Apollo 17, formed at least 50 km deep, experienced maximum shock pressures of 6 GPa, and has a 40 Ar/ 39 Ar excavation age of 4.25 Ga. Previous work attributed 76535 to the South Pole-Aitken (SPA) basin, presumably dating the SPA-impact and constraining lunar bombardment history. Here we use the iSALE-2D shock-physics code and gravity inversion modeling to determine if instead the Serenitatis impact event excavated 76535. We find nearly 140,000 km 3 of material (∼2% of near-surface ejecta) matching the depth and pressure constraints of 76535 is displaced to the surface during crater collapse of a Serenitatis-like impact event. We conclude that the Serenitatis impact event possibly excavated 76535, redefining its age to 4.25 Ga, 300 My older than the consensus age based on Apollo 17 samples. This finding would provide an important anchor point where lunar chronology where bombardment flux is especially uncertain.

Bjonnes, Evan [Lawrence Livermore National Laborat↗

A Vertically Resolved Canopy Improves Chemical Transport Model Predictions of Ozone Deposition to North Temperate Forests

Abstract Dry deposition is the second largest tropospheric ozone (O 3 ) sink and occurs through stomatal and nonstomatal pathways. Current O 3 uptake predictions are limited by the simplistic big‐leaf schemes commonly used in chemical transport models (CTMs) to parameterize deposition. Such schemes fail to reproduce observed O 3 fluxes over terrestrial ecosystems, highlighting the need for more realistic treatment of surface‐atmosphere exchange in CTMs. We address this need by linking a resolved canopy model (1D Multi‐Layer Canopy CHemistry and Exchange Model, MLC‐CHEM) to the GEOS‐Chem CTM and use this new framework to simulate O 3 fluxes over three north temperate forests. We compare results with in situ measurements from four field studies and with standalone, observationally constrained MLC‐CHEM runs to test current knowledge of O 3 deposition and its drivers. We show that GEOS‐Chem overpredicts observed O 3 fluxes across all four studies by up to 2×, whereas the resolved‐canopy models capture observed diel profiles of O 3 deposition and in‐canopy concentrations to within 10%. Relative humidity and solar irradiance are strong O 3 flux drivers over these forests, and uncertainties in those fields provide the largest remaining source of model deposition biases. Flux partitioning analysis shows that: (a) nonstomatal loss accounts for 60% of O 3 deposition on average; (b) in‐canopy chemistry makes only a small contribution to total O 3 fluxes; and (c) the CTM big‐leaf treatment overestimates O 3 ‐driven stomatal loss and plant phytotoxicity in these temperate forests by up to 7×. Results motivate the application of fully online vertically explicit canopy schemes in CTMs for improved O 3 predictions.

Vermeuel, Michael P. [Department of Soil, Water, a↗

Spatio-spectral optical fission in time-varying subwavelength layers

Transparent conducting oxides are highly doped semiconductors that exhibit favourable optical features compared with metals, including reduced material losses, tuneable electronic and optical properties, and enhanced damage thresholds. Recently, the photonic community has renewed its attention towards these materials, recognizing their remarkable nonlinear optical properties in the near-infrared spectrum. The exceptionally large and ultrafast change in the refractive index, which can be optically induced in these compounds, extends beyond the boundaries of conventional perturbative analysis and makes this class of materials the closest approximation to a time-varying system. Here we report the spatio-spectral fission of an ultrafast pulse trespassing a thin film of aluminium zinc oxide with a non-stationary refractive index. By applying phase conservation to this time-varying layer, our model can account for both space and time refraction and explain, in quantitative terms, the spatial separation of both spectrum and energy. Our findings represent an example of extreme nonlinear phenomena on subwavelength propagation distances, which provides new insights into transparent conducting oxides’ transient optical properties. This can be critical for the ongoing research on photonic time crystals, on-chip generation of non-classical states of light, integrated optical neural networks, ultrafast beam steering and frequency-division multiplexing.

integrated optics↗

Laser Measurements and Modeling of Shock Tunnel Freestream Velocity and Multispecies Thermal Nonequilibrium

Coherent anti-Stokes Raman scattering (CARS) and nitric oxide molecular tagging velocimetry (NO-MTV) were used to characterize the freestream in Sandia’s Hypersonic Shock Tunnel (HST) using a burst-mode laser operated at 100 kHz. Experiments were performed at nominal freestream velocities of 3 and 4 km/s using both air and N 2 test gas. The CARS diagnostic provides nonequilibrium characterization of the flow by measuring vibrational and rotational temperatures of N 2 and O 2 , which are compared to NO temperatures from separate laser absorption experiments. Simultaneous, collinear freestream velocities were measured using NO MTV along with pitot pressure measurements. Furthermore, this extensive freestream dataset is compared to nonequilibrium CFD that is capable of modeling species-specific, vibrational temperatures throughout the nozzle expansion. Significant nonequilibrium between vibrational and rotational temperatures was measured at each flow condition. N 2 exhibits the most nonequilibrium, followed by O 2 and NO. The CFD model captures this trend, although it consistently overpredicts N 2 and O 2 vibrational temperatures. At 3 km/s, the modeled NO nonequilibrium is underpredicted, whereas it is overpredicted at 4 km/s. Good agreement is seen between CFD and the velocity and rotational temperature measurements. Experiments with water added to the test gas yielded no discernable difference in vibrational relaxation.

Aerodynamics↗

Mind the gap: Bridging the divide between AI aspirations and the reality of autonomous microscopy

What does materials science look like in the “Age of Artificial Intelligence?” Each material’s domain—synthesis, characterization, and modeling—has a different answer to this question, motivated by unique challenges and constraints. This work focuses on the tremendous potential of autonomous characterization within electron microscopy. We present our recent advancements in developing domain-aware, multimodal models for microscopy analysis capable of describing complex atomic systems. We then address the critical gap between the theoretical promise of autonomous microscopy and its current practical limitations, showcasing recent successes while highlighting the necessary developments to achieve robust, real-world autonomy.

2D materials↗

Investigation of an octupole breathing mode of 208 Pb as a resolution to the elliptical-to-triangular azimuthal anisotropy puzzle in ultracentral relativistic heavy ion collisions

Relativistic heavy ion collisions provide a unique opportunity to probe the nuclear structure by taking an instantaneous snapshot of the colliding nuclei and converting it into momentum anisotropies of final emitted hadrons. A long-standing puzzle of too large a ratio of the elliptical-to-triangular (𝑣 2 -to-𝑣 3 ) anisotropies in ultracentral 208 Pb + 208 Pb collisions at the Large Hadron Collider (LHC) cannot be solved simply by hydrodynamic simulations with initial conditions containing the spherical or certain deformed shape of 208 Pb. Here, in this Letter, using the iEBE-VISHNU relativistic viscous hydrodynamic hybrid model simulations with the TR⁢ENTo initial condition, we show that a dynamic octupole deformation—a shape-breathing mode of 208 Pb —could potentially solve the 𝑣2-to-𝑣3 puzzle and simultaneously describe the 𝑣 3 ⁡{4} data measured in experiment. Our results highlight the unique capability of capturing transient collective properties of nuclei on yoctosecond (10 −24 s) timescales, unfeasible with low-energy nuclear reactions.

Xu, Hao-jie [Huzhou University, Zhejiang (China)] ↗

Transforming E-Waste Into Strategic Resources: Techno-Economic Analysis of Gallium and By-products Recovery from LEDs via Bioleaching

The growing demand for gallium in optoelectronics and renewable energy applications raises concerns about supply security and production sustainability. This study evaluates the techno-economic feasibility of recovering gallium and by-products (copper and nickel) from waste GaN-based LEDs via bioleaching. A process flowsheet encompassing transportation, robotic disassembly, ball milling, bioleaching, solvent extraction/electrowinning, and refining was modeled. Based on mass balance analysis, more than 53 tons of LED waste are required annually to yield 1 kg of gallium alongside substantial copper and nickel co-products. Preliminary techno-economic analysis (TEA) shows an average total cost (ATC) of 6.84 USD/kg metal when costs are allocated by mass-weighted economic value (market price) fraction, corresponding to 6.75 USD/kg for copper, 15.91 USD/kg for nickel, and 470.95 USD/kg for gallium. For gallium, direct operational costs account for more than 70% of the cost. Monte Carlo simulations further quantify cost uncertainties under market price fluctuations. This work represents the first TEA of gallium recovery from GaN-based LEDs and highlights potential pathways for future cost reduction.

36 MATERIALS SCIENCE↗

Spontaneously formed phonon frequency combs in van der Waals solid CrGeTe 3 and CrSiTe 3

Optical phonon engineering through nonlinear effects has been utilized in ultrafast control of material properties. However, nonlinear optical phonons typically exhibit rapid decay due to strong mode-mode couplings, limiting their effectiveness in temperature or frequency sensitive applications. Here we report the observation of long-lived nonlinear optical phonons through the spontaneous formation of phonon frequency combs in the van der Waals material CrXTe 3 (X=Ge, Si) using high-resolution Raman scattering. Unlike conventional optical phonons, the highest A g mode in CrGeTe 3 splits into equidistant, sharp peaks forming a frequency comb that persists for hundreds of oscillations and survives up to 200K. These modes correspond to localized oscillations of Ge 2 Te 6 clusters, isolated from Cr hexagons, behaving as independent quantum oscillators. Introducing a cubic nonlinear term to the harmonic oscillator model, we simulate the phonon time evolution and successfully replicate the observed comb structure. Similar frequency comb behavior is observed in CrSiTe 3 , demonstrating the generalizability of this phenomenon. Our findings demonstrate that Raman scattering effectively probes high-frequency nonlinear phonon modes, offering insight into the generation of long-lived, tunable phonon frequency combs with potential applications in ultrafast material control and phonon-based technologies.

36 MATERIALS SCIENCE↗

Paleotribological models using preserved fossil tissue properties reveal functional significance of Eurasian mammoth dental evolution

Eurasian mammoths (Mammuthus) underwent substantial modifications in molar morphology as later-diverging species evolved progressively thinner enamel and increased enamel crest complexity. These features have been hypothesized to reduce whole-tooth wear and extend dental longevity as increasingly graze-dominated diets evolved within the lineage. This hypothesis has yet to be directly tested. Here, in this study, we developed an in-silico wear model using experimentally derived wear rates from fossil and extant proboscidean dental tissues. The models revealed that shifts in tissue topology do not affect whole-tooth wear rate, as inverse trends in lamellar frequency and enamel thickness preserve a consistent surface enamel area fraction; the determining factor of wear. Rather, topological shifts produce a wear-emergent secondary occlusal surface with greater numbers of triturating crests that create a regular, low-relief, file-like shearing pavement. These changes in occlusal architecture likely directly impacted the mastication capacity of Mammuthus dentitions, facilitating their dietary expansion to incorporate fibrous, lower-nutrient graze.

Dental wear↗

Recent Tropical Cyclone Outer Size Increases in the Western North Atlantic

The outer size of a tropical cyclone (TC) plays a pivotal role in its impact through a modulation of wind duration, rainfall extent and storm surge. While global and basin scale trends in TC size have been examined previously, whether there have been regional changes over time remains unclear. Here, using a suite of observations and reanalyses, we detect an increasing TC outer size over the western North Atlantic during 1979–2022. Over the western subtropical North Atlantic where the largest changes are found, the area-averaged increase in the radius of 17 ms -1 winds is about 7.5% over this period. Analysis of the large-scale environment reveals that the air-sea thermodynamic state has become more favorable for storm intensification, and thereby expansion, over that region. Further, numerical model simulations link changes in the environment with those in storm size, and suggest a combination of natural variability and external forcing in driving them.

Balaguru, Karthik [Pacific Northwest National Labo↗

Database and deep-learning scalability of anharmonic phonon properties by automated brute-force first-principles calculations

Understanding the anharmonic phonon properties of crystal compounds—such as phonon lifetimes and thermal conductivities—is essential for investigating and optimizing their thermal transport behaviors. These properties also impact optical, electronic, and magnetic characteristics through interactions between phonons and other quasiparticles and fields. In this study, we develop an automated first-principles workflow to calculate anharmonic phonon properties and build a comprehensive database encompassing more than 6500 inorganic compounds. Utilizing this dataset, we train a graph neural network model to predict thermal conductivity values and spectra from structural parameters, demonstrating a scaling law in which prediction accuracy improves with increasing training data size. High-throughput screening with the model enables the identification of materials exhibiting extreme thermal conductivities—both high and low. The resulting database offers valuable insights into the anharmonic behavior of phonons, thereby accelerating the design and development of advanced functional materials.

Ohnishi, Masato [University of Tokyo (Japan); Inst↗

Describing Point Defect Topology in 2D Energy Materials Through Computer Vision

Point defects such as vacancies and impurity atoms strongly impact the performance of 2D materials. Traditional efforts often rely on manual detection, a process that is time-intensive, prone to human error, and challenging to scale. Here we leverage machine learning (ML) methods to identify and quantify vacancies within 2D transition metal carbides (Ti3C2, MXenes), aiming to expedite detection while improving accuracy. MXenes exhibit valuable defect-defined electrochemical properties, but we currently lack statistical understanding of defect topology needed to fully harness these materials. Here we employ a convolutional neural network for semantic segmentation of experimental MXene images, opening an opportunity to conduct a rigorous statistical study on defect hierarchy while investigating local relaxation in the lattice. We show how the integration of ML can yield fundamental insight into point defects, providing a powerful tool that will play an increasingly crucial role in the future of materials science. ML is often not just a matter of straightforward application, and pretrained models proved ineffective in this case. Instead, we trained our own neural network (NN) and applied data augmentation techniques and fine-tuning to the training dataset. Since labeled microscopy data is often scarce, we developed training data from a previously published wide-frame MXene image, using customized Gaussian fitting to locate atomic positions. Our trained model was then applied to a large dataset of experimental images, enabling a statistical study of defect configurations across three samples prepared with different HF etchant concentrations (5%, 9.1%, and 12.5%), as shown in Fig. 1. This also allowed us to investigate local strain around vacancies, though we find that we are limited by the precision of measurements using high-angle annular dark field (HAADF) images, as shown in Fig. 2. This study demonstrates how ML enables large-scale, quantitative analysis of atomic defects - an otherwise infeasible task with traditional methods. While our NN was specialized for Ti3C2 MXenes, the pipeline we developed provides a foundation for future ML models tailored to other materials. Ultimately, we envision embedding the NN onto the microscope to give real-time feedback to the user. To make this a reality, continued work is necessary to fully understand the NN's capabilities and limitations. This study gets one step closer to our goals of automated experimentation moving away from traditional methods of manual labeling. As ML capabilities advance, we hope to continue adapting and applying these techniques in microscopy.

2D materials↗

Atmospheric System Research Workshop Report: New Directions in Atmospheric Ice Processes Research

Atmospheric ice processes are critical for precipitation production, cloud dynamics, and radiative properties and contribute to uncertainties in Earth’s energy budget and hydrological cycle, yet they remain poorly understood. To address this, ASR convened a 2.5-day workshop with 28 experts in laboratory measurements, field observations, and cloud modeling. The primary goal was to identify key knowledge gaps and prioritize future directions in atmospheric ice processes research. The outcomes of this workshop are expected to inform ASR and prompt improvements in cloud and Earth system models (ESMs) by advancing the fundamental understanding of ice processes.

54 ENVIRONMENTAL SCIENCES↗

An entropy-based debiasing approach to quantifying experimental coverage for novel applications of interest in the nuclear community

This manuscript proposes a novel information-theoretic approach to the quantification of experimental relevance, i.e., coverage, to achieve optimal data assimilation results for nuclear engineering applications. Specifically, this work posits the need for a new metric, called coverage (q C ) of an application’s quantity of interest, i.e., eigenvalue or power peaking for an advanced reactor concept, defined herein as the theoretically maximum achievable reduction in the quantity’s uncertainty given measurements from a pool of experiments in a manner that is independent of the data assimilation procedure employed. Currently, reduction in a quantity’s uncertainty is strongly biased by the underlying assumptions of the assimilation procedure to account for the under-determined nature of such problems and the similarity criterion employed to identify relevant experiments. To address this challenge, this work has developed a coverage metric, q C , based on mutual information, which establishes a new conceptual framework for assessing coverage, one that is independent of the model parameters and responses degree of variations in both the experimental and application domains, i.e., linear vs non-linear, and their prior uncertainty distributions, i.e., Gaussian vs. non-Gaussian. The q C is an entropic measure capable of addressing coverage for general nonlinear problems with non-Gaussian uncertainties and inclusive of the measurement uncertainties from multiple experiments. Numerical experiments from manufactured analytical problems as well as a set of benchmarks from the ICSBEP handbook are employed to demonstrate its theoretical and practical performance as compared to the c k -based experiment selection methodology, commonly employed in the neutronic community. The manuscript then employs other well-known adaptations to existing data assimilation methodologies for nonlinear and non-Gaussian problems capable of achieving the coverage posited by q C .

Bayesian data assimilation↗

Dynamic behavior of molecular Pd-acetate trimers and dimers in heterogeneous vinyl acetate synthesis

Vinyl acetate monomer (VAM) is a crucial intermediate in the production of various polymers. While molecular Pd-acetate trimers and dimers, such as Pd 3 (OAc) 6 and K 2 Pd 2 (OAc) 6 , are known to form on potassium acetate (KOAc)-promoted PdAu catalysts during heterogeneous VAM synthesis, their mechanistic role remains unclear. Here, we study the dynamics of different Pd-acetate species by utilizing in situ and operando crystallographic and spectroscopic characterizations combined with computational modeling on monometallic Pd model catalysts. The promoter-free catalyst expectedly shows low catalytic activity and VAM selectivity, corresponding to the complete reduction of Pdn(OAc) 2n species to form Pd 0 and PdC x nanoparticles. Conversely, noticeable quantities of K n Pd 2 (OAc) n+4 species remain on the KOAc-promoted catalyst, leading to smaller nanoparticle formation with 10 times the activity and double the selectivity for VAM. This study reveals that molecular Pd-acetate trimers and dimers are significant indicators of catalytic performance and highlights their structurally dynamic nature in heterogeneous vinyl acetate chemistry.

Jacobs, Hunter P. [Rice Univ., Houston, TX (United↗

Optimized Carbon Fiber Intermediate Development to Enable High-Volume Manufacturing of Lightweight Automotive Composites

The ongoing pursuit of improved fuel economy and reduced greenhouse gas emissions has resulted in sustained interest for lightweight materials technologies. In this context, carbon fiber composites have captured the imagination of automotive engineers due to the potential to achieve substantial mass reduction when compared to traditional steel construction. That stated, the use of carbon fiber composites in automotive has been limited for the most part to premium supercars and other derivative platforms. In these cases, manufacturing costs are less of an obstacle to implementation, and the performance benefits of carbon fiber have enabled production of structures offering more than 50% weight savings. In practice, translating these low-volume demonstrations onto high-volume vehicle platforms has remained challenging. This can be attributed to several factors, with the absence of suitable high throughput production methodologies being a key impediment. To date, structural, crash critical components have relied upon manufacturing techniques born out of the aerospace industry. This has created a disconnect between automotive production systems that are accustomed to manufacturing multiple parts per minute and the aerospace technologies that have cycle times in the order of hours. Consequently, the focus of this project is the development of manufacturing process technology for carbon fiber composites that can support a mainstream vehicle program at an assumed throughput of 100,000 vehicles per year. In practice, this translates to a part-to-part cycle time of less than 3 minutes. Project participation included contributions from a broad range of academic, industrial and national lab partners. The primary scope of work, being the development of new carbon fiber epoxy compounds that are stable at room temperature and suited to high throughput automated processing. For project management, the work streams were divided into six key areas, with the lead organization in parentheses. • Carbon fiber/epoxy materials formulation development and scale up (Dow) • Simulation of discontinuous near isotropic meso-structure intermediates (Purdue) • Simulation of mechanical performance of compression molded components (Purdue) • Meso-Scale morphological analysis and correlation with structural performance (UTK) • Paint and adhesion durability analysis (MSU) • Demonstrator part design, prototype production, and validation testing (Ford). The primary goal at the commencement of the project was development of a chopped carbon fiber sheet molding compound (SMC) that offered a three times improvement in tensile modulus over a comparable glass-based SMC. In addition to meeting mechanical performance targets, the resin kinetics were modified to achieve a processing cycle time of less than 3 minutes. Other critical-to-quality (CTQ) specifications were also stipulated to account for a broad range of materials and processing characteristics. To achieve the above, staff scientists at Dow Chemical created an extensive series of new epoxy blends for testing and validation. Throughout this development, a key challenge was attaining material performance goals without impacting processing behavior and paintability of finished components. The latter required a new internal mold release system being developed by Dow that was designed to complement the kinetics of the rapid cure epoxy. As a complement to work studies at the industrial partners, the teams from academia executed a series of analytical and experimental studies to investigate potential factors influencing CF-SMC performance. Unit cell models were developed to capture the meso-scale representations of the fiber matrix architecture. Results of this analysis and subsequent morphological investigations led to the design of a novel composite derivative comprising carbon fiber platelets embedded in an epoxy matrix; the platelet size and aspect ratio playing significant role in final composite properties. This approach was a departure from previous research in CF-SMC development whereby bulk filamentization or disassembly of the carbon fiber rovings had been considered the most effective means of achieving both fiber wet through and wet-out. As the course of the academia studies progressed, the aspect ratio of the fiber constituents was further optimized before finalizing material attributes and processing conditions. For the purposes of technology validation, the Ford team led a work stream devoted to the design, fabrication and testing of demonstration components. The carbon fiber SMC material has the potential to displace numerous stampings and castings on an automotive structure but ultimately vehicle closure applications were selected to showcase the abilities of the CF-SMC to achieve both mass reduction and business case for large complex structures. Using target properties established by the Dow staff scientists, the complete closure system for a full-size sedan decklid and a mid-size wagon liftgate were engineered. Prototypes for both applications were fabricated using production representative processing methods to allow for physical testing and performance validation of the CF-SMC structures. Following completion of a testing program that concluded with a FMVSS301 55 mph offset rear crash, the CF-SMC formulation was declared by the Ford team to have met all engineering requirements. To summarize, the joint development activities during this project led to significant technical breakthroughs and achievement of all milestones. The result was the development of a novel, tack-free carbon fiber molding compound that is suited to automated processing. This combined room temperature stability, fast cure kinetics, and internal mold release system facilitates cycle times that are conducive to high-volume production. The VORAFUSE M6400 successfully passed technology validation at Ford and is now eligible for consideration on future production commercial vehicle programs.

36 MATERIALS SCIENCE↗