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DOE OSTI2020

Eudicot Nutshells: Cell-Wall Composition and Biofuel Feedstock Potential

Nutshells are the recalcitrant and membranous layers that encompass and provide protection to the seed of a fruit. Rich in lignin, these are often waste products of the food industry and are a potential energy-dense feedstock for biorefineries to convert to biofuels. Here, assessing their potential requires an understanding of the relative amounts of cellulose, hemicelluloses, and lignin, the composition and structure of the lignin, and a saccharifiability assessment, all provided here. In the context of understanding the general character of phylogenetically diverse eudicot species, we provide a chemical analysis of the lignin in the shells of commonly eaten nuts and detail the chemical composition of their lignins. Particularly striking observations include the >40% levels of Klason lignins in the nutshells from macadamia, pecan, and Brazil nut and lignin compositions ranging from <1% syringyl (S) in macadamia to 77% S in pistachio and essentially 0% p-hydroxyphenyl (H) in mango to as high as 7.5% H in walnut. Novel units in the lignin polymer (such as the hydroxystilbenes recently discovered in macaúba and coconut shell lignins) were not evident in any of the samples, but the series provided such a range of compositions that it aided more detailed assignment.

NMR↗

DOE OSTI2022

Real-Time Monitoring of Gas-Phase and Dissolved CO 2 Using a Mixed-Matrix Composite Integrated Fiber Optic Sensor for Carbon Storage Application

Novel chemical sensors that improve detection and quantification of CO 2 are critical to ensuring safe and cost-effective monitoring of carbon storage sites. Fiber optic (FO) based chemical sensor systems are promising field-deployable systems for real-time monitoring of CO 2 in geological formations for long-range distributed sensing. Here, a mixed-matrix composite integrated FO sensor system was developed with a purely optical readout that reliably operates as a detector for gas-phase and dissolved CO 2 . A mixed-matrix composite sensor coating consisting of plasmonic nanocrystals and hydrophobic zeolite embedded in a polymer matrix was integrated on the FO sensor. The mixed-matrix composite FO sensor showed excellent reversibility/stability in a high humidity environment and sensitivity to gas-phase CO 2 over a large concentration range. This remarkable sensing performance was enabled by using plasmonic nanocrystals to significantly enhance the sensitivity and a hydrophobic zeolite to effectively mitigate interference from water vapor. The sensor exhibited the ability to sense CO 2 in the presence of other geologically relevant gases, which is of importance for applications in geological formations. A prototype FO sensor configuration which possesses a robust sensing capability for monitoring dissolved CO 2 in natural water was demonstrated. Reproducibility was confirmed over many cycles, both in a laboratory setting and in the field. More importantly, we demonstrated on-line monitoring capabilities with a wireless telemetry system, which transferred the data from the field to a website. The combination of outstanding CO 2 sensing properties and facile coating processability makes this mixed-matrix composite FO sensor a good candidate suitable for practical carbon storage applications.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Li Morphology Evolution during Initial Cycles in a Gel Composite Polymer Electrolyte

Understanding and controlling lithium morphology evolution and lithium dendrite formation and growth during cycling is one of the key challenges for high-energy lithium metal batteries. This challenge applies to liquid electrolyte batteries as well as solid-state and semi-solid-state batteries. Our current knowledge about the evolution of the Li morphology is mostly obtained from liquid electrolyte-based studies in a Li–Li symmetrical cell configuration. The knowledge obtained in such conditions may not readily transfer into solid-state or semi-solid-state batteries. In this work, Li morphology evolution during initial cycling in a full cell configuration with the LiNi 0.6 Co 0.2 Mn 0.2 O 2 (NMC 622) cathode and a semi-solid-state gel composite electrolyte is monitored via post-mortem photographs and scanning electron microscopy at multiple length scales. The gel composite electrolyte contains a cross-linked poly(ethylene oxide)-based polymer electrolyte, ceramic fillers, and a liquid plasticizer. The results show that severe surface pitting occurs as early as the second stripping cycle. Pit formation and continuous dissolution during the stripping process are the main cause of the Li surface roughening and dendrite growth mechanism in the model gel composite electrolyte. Comparing Li dendrite growth mechanisms in liquid, polymer, and ceramic solid electrolytes, the dendrite growth mechanism observed in this model electrolyte resembles that of the liquid electrolyte the most. This study suggests that strategies to control Li morphology and prevent dendrite growth in a gel composite electrolyte should be similar to strategies applicable to liquid electrolytes.

25 ENERGY STORAGE↗

DOE OSTI2025

Spray Manufacturing Thermal Insulation Composites

Cellulose-based thermal insulation materials present significant potential for modern green building applications due to their inherent carbon sequestration properties. However, traditional manufacturing of composites often results in the limited thermal insulation performance and embodied carbon footprint due to an increased density from material shrinkage and higher energy consumption during the water-based slurry drying process. Here, we report solvent spraying coupled with dry powder feedstock to manufacture highly porous silica/straw insulation composites. The manufactured composite exhibits negligible shrinkage with the density of 0.08 g/cm 3 , thermal conductivity of 27.8 mW/(m·K), flexural modulus of 3.1 MPa, and compressive modulus of 0.89 MPa. Additionally, the prepared composite demonstrates fire retardancy (burning rate of 0.5 mm/min) and recyclability (99%). Furthermore, this solvent-spraying strategy opens up opportunities of energy-efficient insulation materials for carbon-sequestration building sectors.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Heterogeneous Growth of UiO-66-NH 2 on Oxidized Single-Walled Carbon Nanotubes to Form “Beads-on-a-String” Composites

In this work we demonstrate a facile synthesis of UiO-66-NH 2 metal-organic framework (MOF)/oxidized single-walled carbon nanotubes (ox-SWCNTs) composite at room temperature. Acetic acid (HAc) was used as a modulator to manipulate the morphology of the MOF in these composites. With zirconium oxide-cluster (Zr) to 2-aminoteraphthalate linker (ATA) 1:1.42 ratio and acetic acid modulator, we achieved predominately heterogeneous MOF growth on the sidewalls of CNTs. Understanding the growth mechanism of these composites was facilitated by conducting DFT calculations to investigate the interactions between ox-SWCNTs and the MOF precursors. The synthesized composites combine both micro-porosity of the MOF and electrical conductivity of the SWCNTs. Gas sensing tests demonstrated higher response for UiO-66-NH 2 /ox-SWCNT hybrid toward dry air saturated with dimethyl methylphosphonate (DMMP) vapor compared to oxidized single-walled carbon nanotubes (ox-SWCNTs) alone.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Self-Sensing Composites via an Embedded 3D-Printed PVDF-MoS 2 Nanosensor for Structural Health Monitoring

Carbon fiber (CF)-reinforced epoxy composites are widely used in vehicle applications, where early damage detection is crucial for reliability and safety. To address this need, we developed a self-sensing epoxy/CF composite by embedding a PVDF-MoS 2 nanosensor via an embedded 3D printing method. By harnessing the intrinsic curing kinetics of epoxy, we tailored its rheological properties to optimize the embedded printing process, enabling precise and reliable support for sensor filaments without compromising the composite’s structural and functional integrity. Through comprehensive rheological and kinetic analysis, we established a quantitative relationship among curing temperature, conversion rate, and resulting yield modulus─defining a narrow processing window essential for successful sensor integration. Specifically, we identified that an epoxy yield modulus range of 180–294 Pa and a conversion rate below 10% are critical to support the PVDF-MoS 2 filament architecture. Here, this embedded 3D printing method produces complex and multimaterial PVDF-MoS 2 sensors within an epoxy matrix with minimal deformation and reduced postprocessing, which is scalable and adaptable for industrial applications. Under cyclic loading, the embedded sensors exhibited stable signals under constant loads and increased voltage signals in response to crack formation (17–35% higher) and catastrophic failure (1 order of magnitude higher), effectively capturing structural changes in real time. This study demonstrates the potential of PVDF-MoS 2 nanocomposite sensor materials for real-time structural health monitoring in epoxy–CF composite systems, enabling early detection of defects and stress anomalies, significantly reducing the risk of unexpected failures, and enhancing structural reliability.

PVDF-MoS2 sensor↗

DOE OSTI2021

Polyacrylonitrile Composites of Ag–Al–Si–O Aerogels and Xerogels as Iodine and Iodide Sorbents

Mechanically robust engineered sorbents were constructed by embedding Ag-loaded aerogels or xerogels in a polyacrylonitrile (PAN) matrix at 30 or 50 mass% loadings of gel in PAN. Here, the process for making the base gels as well as the composite materials is described herein, a technology that is very flexible for making hybrid sorbents using various inorganic or organic active sorbents. The PAN-gel composite materials were evaluated for iodine uptake in the form of gaseous iodine [I 2(g) ] at room temperature and at 150°C as well as iodide (I – ) at room temperature from simulated liquid nuclear wastes. The composites show high I 2(g) uptake and high I – uptake (= 93 mass%) in simulated liquid secondary waste spiked with 5 mg L -1 I – . These results demonstrate the utility of such a composite form for iodine removal from contaminated gas and liquid streams.

36 MATERIALS SCIENCE↗

DOE OSTI2020

A Nuclear Magnetic Resonance Study of Cation and Anion Dynamics in Polymer–Ceramic Composite Solid Electrolytes

Polymer–ceramic composite electrolytes are promising for the application of all-solid-state lithium-ion batteries with high energy density and improved safety. In this work, we employ temperature-dependent 7 Li and 19 F NMR to examine the chemical environment and the dynamics of Li + cation and triflate anion in poly(ethylene oxide) (PEO)–lithium triflate (LiTf) polymer electrolyte and a composite electrolyte containing 55 vol % doped lithium aluminum titanium phosphate (LICGC). The line shape analysis and spin–lattice relaxation (T 1 ) measurements suggest both the Li + cations and the Tf – anions reside in two distinct environment: a mobile environment and an immobile environment. In the semicrystalline state, a large ratio (>70%) of immobile Li + and Tf – is observed. In the melt state, the ratio of mobile cations and anions significantly increases. With the presence of LICGC ceramic, an increased ratio of immobile Li + and Tf – and reduced mobility of the mobile components are observed, indicating that the ceramic negatively impacts the transport of both the cations and the anions. NMR characterizations are corroborated by conductivity results, which reveal that the intrinsic ionic conductivity of the polymer phase of the composite electrolyte was only 0.15 of the ceramic-free polymer electrolyte at room temperature. These results shed light on the challenges inherent to composite electrolytes with the goal of achieving both enhanced Li + transference number and ionic conductivity.

25 ENERGY STORAGE↗

DOE OSTI2020

Exploring the First High-Entropy Thin Film Libraries: Composition Spread-Controlled Crystalline Structure

Thin films of two types of high-entropy oxides (HEOs) have been deposited on 76.2 mm Si wafers using combinatorial sputter deposition. In one type of the oxides, (MgZnMnCoNi)O x , all the metals have a stable divalent oxidation state and similar cationic radii. In the second type of oxides, (CrFeMnCoNi)O x , the metals are more diverse in the atomic radius and valence state, and have good solubility in their sub-binary and ternary oxide systems. Therefore, the resulting HEO thin films were characterized using several high-throughput analytical techniques. The microstructure, composition, and electrical conductivity obtained on defined grid maps were obtained for the first time across large compositional ranges. The crystalline structure of the films was observed as a function of the metallic elements in the composition spreads, that is, the Mn and Zn in (MgZnMnCoNi)O x and Mn and Ni in (CrFeMnCoNi)O x . The (MgZnMnCoNi)O x sample was observed to form two-phase structures, except single spinel structure was found in (MgZnMnCoNi)O x over a range of Mn > 12 at. % and Zn < 44 at. %, while (CrFeMnCoNi)O x was always observed to form two-phase structures. Composition-controlled crystalline structure is not only experimentally demonstrated but also supported by density function theory calculation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

High-Spatial-Resolution Quantitative Chemomechanical Mapping of Organic Composite Cathodes for Sulfide-Based Solid-State Batteries

Understanding the chemo-mechanical behaviors of electrodes, particularly at the electrode/electrolyte interfaces, is critical for improving the performance of all-solid-state batteries. However, due to the instability of electrolyte materials under ambient conditions, such characterizations are challenging, particularly for sulfide-based all-solid-state batteries. Herein, by combining time-of-flight secondary-ion mass spectroscopy (ToF-SIMS) and in-SEM nanoindentation measurements, a systematic quantitative investigation of the chemo-mechanical behaviors of pyrene-4,5,9,10-tetraone (PTO) /Li 6 PS 5 Cl composite cathodes is carried out. Chemical and quantitative mechanical information of the composite cathode were collected with high spatial resolution after developing and implementing an air-free characterization protocol. By directly connecting the Young’s modulus and hardness with the Li distribution in the composite cathode, a comprehensive chemo-mechanical mapping of the PTO/ Li 6 PS 5 Cl composite cathode has been established. Furthermore, this work improves our knowledge of the critical chemo-mechanical phenomena that occur at the cathode/electrolyte interfaces in all-solid-state batteries.

25 ENERGY STORAGE↗

DOE OSTI2020

Analyzing Wildland Fire Smoke Emissions Data Using Compositional Data Techniques

By conservation of mass, the mass of wildland fuel that is pyrolyzed and combusted must equal the mass of smoke emissions, residual char and ash. For a given set of conditions, these amounts are fixed. This places a constraint on smoke emissions data which violates statistical assumptions for many of the methods currently used to analyze these data such as linear regression, analysis of variance, and t-tests. These data are inherently multivariate and non-negative parts of a whole. This paper introduces the field of compositional data analysis to the emissions community and provides examples of appropriate statistical treatment of emissions data. It is shown that modified combustion efficiency should not be used as a predictor variable for other smoke emissions because it is not an independent variable. An alternative method based on compositional linear trends to estimate trace gas composition using CO and CO2 is presented. The data used in this paper resulted from projects the DOD/DOE/EPA Strategic 586 Environmental Research and Development Program projects RC-1648 and 1649. The senior 587 author appreciates the guidance and R scripts provided by Prof. Girty at San Diego State 588 University to estimate linear trends by perturbation. J. P.-A. was supported by the Spanish 589 Ministry of Science, Innovation and Universities under the project CODAMET (RTI2018-590 095518-B-C21, 2019-2021). The data used in this study have been previously published and are 591 available in the original publications. DRW conceived the initial manuscript (70 percent) and 592 performed the bulk of the data analysis. JPA provided statistical guidance and compositional data 593 expertise and contributed 20 percent of the manuscript. TJJ and HJ were extensively involved in 594 the study that provided the data. TJJ provide smoke emissions expertise and HJ provided 595 combustion expertise. The authors declare that they have no conflict of interest. The use of trade 596 or firm names in this publication is for reader information and does not imply endorsement by 597 the U.S. Department of Agriculture of any product or service.

simplex, compositional data analysis, balance, log↗

DOE OSTI2022

Carbon nanomaterials–polymer composites for perovskite solar cells: preparation, properties and applications

Perovskite solar cells (PSCs) are a rising star in the photovoltaic industry, which achieved an enormous breakthrough in terms of efficiency from an initial 3.8% in 2009 to 25.7% in 2021. Here, the major challenge to bring perovskite solar cells commercially available is the poor long-term device stability. The defects in perovskite and energy loss originating from charge recombination limit the efficiency of perovskite solar cells. Carbon–polymer composites, which feature superb electrical conductivity, outstanding carrier mobility, remarkable flexibility and superior heat and moisture stability, have attracted considerable attention to tackle these issues. With their multifunctional properties, carbon–polymer composites can play various roles in almost every component in the perovskite solar cell architecture. In this review article, recent progress concerning the utilization of carbon–polymer composites in different components in PSCs (i.e., perovskite additives, electrodes, encapsulation layers and charge transport layers) is comprehensively overviewed. Then, future research directions and opportunities toward high-performance perovskite solar cells utilizing carbon–polymer composites are presented.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Enhanced electrical conductivity in graphene–copper multilayer composite

For many years, researchers have been trying to make a material more conductive than silver by incorporating carbon nanotubes or graphene into copper to form a composite material. However, after a decade-long effort, only a few groups reported successful results, raising concerns about the feasibility of this composite approach. Here, we report our effort to validate the multilayer graphene–copper composite approach for improving electrical conductivity. We demonstrate that, with an estimated 0.008 vol. % graphene addition, copper’s electrical conductivity was improved to 104.2% of International Annealed Copper Standard (IACS) at room temperature. If the copper substrate used to make the multilayer composite is discounted using the parallel resistance model, the conductivity is calculated to be 185% IACS. This result could be further improved if the thickness of the copper layers can be further reduced.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Improving commercial truck fleet composition in emission modeling using 2021 US VIUS data

Commercial trucks are essential elements of the nation's supply chain system. Meanwhile, intensive truck movements contribute significantly to system externalities, such as energy use and air pollution. However, collecting detailed fleet composition and distribution of operational patterns remains a barrier to accurately accounting for these impacts. The recently released 2021 US Vehicle Inventory and Use Survey (US VIUS) fills a critical gap in understanding commercial truck fleet distributions, their operations, and business constraints at the national scale. This study aims to understand the latest US commercial vehicle fleet composition and operational characteristics using 2021 US VIUS data and calibrate the fleet inputs in regulatory emission models to assess the potential emission implications of the VIUS-derived fleet composition. The emission rates for commercial trucks and default fleet composition are collected from the U.S. EPA's MOtor Vehicle Emission Simulator (MOVES4). The 2021 US VIUS data is applied to improve fleet characteristics such as the long-haul fraction and the vehicle mileage accumulation rate. The study also investigates potential emission reduction benefits under various forecasted fleet electrification scenarios. The energy consumption and critical air pollutant rates by vehicle types are compared between MOVES4 and US VIUS fleets for both current and future scenarios to provide insights into the latest U.S. commercial vehicle fleet characteristics and their implications on energy and emissions. This study helps policymakers and practitioners advance the commercial fleet generation for emission models. It also deepens the understanding of the emission reduction potential of the commercial fleet under various fleet projections.

2021 US VIUS↗

DOE OSTI2021

Landscape-scale characterization of Arctic tundra vegetation composition, structure, and function with a multi-sensor unoccupied aerial system

The Arctic is experiencing some of the most rapid climate change on Earth, with strong impacts on tundra ecosystems that are characterized by high land-surface and vegetation heterogeneity. Previous studies have explored this complexity using satellite remote sensing, however these typically coarse spatial resolution data have generally missed sub-pixel heterogeneity, leaving critical gaps in our understanding of tundra vegetation dynamics from the community to landscape scales. To address these gaps, we collected very high-resolution (1-5 cm) optical, structural, and thermal data at three low-Arctic tundra sites on the Seward Peninsula, Alaska, using a multi-sensor unoccupied aerial system (UAS). We examined the application of these data to studying tundra vegetation dynamics, by quantifying (1) canopy height and thermoregulation (leaf-air temperature) of representative plant functional types (PFTs), (2) fine-scale patterns of vegetation composition across landscapes, and (3) impacts of fine-scale vegetation composition on landscape-scale variation of canopy height and thermoregulation. Our results show that deciduous tall shrubs (those that can potentially grow >2 m) had a strong cooling effect, with canopy temperatures significantly lower than local air temperatures and other PFTs. Increased cover of tall shrubs also had the potential to reduce the cover of low-stature PFTs across the landscape, potentially associated with their closed canopy (i.e., increased light competition) and strong thermoregulation. To understand the connections between fine-scale vegetation composition and large-scale ecosystem processes, we produced a random forest model which showed that fine-scale PFT composition accounted for 86.8% and 74.2% of the landscape-scale variation in canopy height and thermoregulation, respectively. These findings highlight the importance of spatially detailed characterization of tundra PFTs to improve our ecological understanding and model representation of tundra vegetation, also transcend our study to show the need for continued collection of similar datasets to better understand the impacts of surface heterogeneity on the mapping and modeling of tundra ecosystem dynamics, as well as assist with conservation management and biodiversity monitoring strategies.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Composite Power System Reliability with Renewables and Customer Flexibility

Composite Power System Reliability is defined as the computational procedure that quantifies the probability that the power system will perform the function of delivering electric power to customers adequately, on a continuous basis and with an acceptable quality. This definition leaves many details undefined and exemplifies the ambiguity in reliability analysis. The increasing deployment of wind and PV creates additional uncertainties that make reliability analysis a rather complex issue. Because of increased uncertainty the need for composite reliability analysis and utilization of results in power system planning is critical. New approaches are emerging for dealing with these problems from the operational point of view, including demand response programs, tapping on customer and distributed resource flexibility and new control approaches. The key question to be addressed is: how the new operational paradigms affect composite power system reliability. Here, this paper presents the ongoing work of the IEEE Composite System Reliability Task Force of the IEEE PES Reliability, Risk, Probability Application (RRPA) Subcommittee.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Mechanistic modeling of lifetime distribution of SiC/SiC composite claddings

Silicon carbide (SiC) fiber-reinforced SiC matrix (SiC/SiC) composites have emerged as a new material candidate for fuel claddings in light water reactors. Recent studies showed that the load capacity of SiC/SiC materials exhibits a considerable statistical variation. Therefore, reliability analysis plays a critical role in design of SiC/SiC composite claddings. Here, this paper presents a probabilistic model for the lifetime distribution of SiC/SiC composites. The model is anchored by a multiaxial stress-based failure criterion and subcritical damage accumulation mechanism. Based on the kinetics of subcritical damage growth, the lifetime distribution of a laboratory test specimen for any given loading history can be calculated. A finite weakest-link model is used to extrapolate the lifetime distribution of test specimens to full-length claddings. It is shown that the damage accumulation mechanism has a strong influence on the lifetime distribution of the cladding. This finding highlights the importance of understanding the static fatigue behavior of SiC/SiC composites. The present analysis also demonstrates an intricate length effect on the failure probability of the cladding, which is expected to play a crucial role in design extrapolation.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Development and Integration of Predictive Models for Manufacturing and Structural Performance of Carbon Fiber Composites in Automotive Applications (Final Report)

The goal of this project is to develop integrated, state-of-the-art, computational modeling tools based on an integrated computational materials engineering (ICME) methodology that are critically needed to enable structural carbon fiber (CF) applications in automobiles. These tools are designed to predict the manufacturing and structural performance of CF composites, including stochastic effects. During the first phase of the project, the manufacturing and structural performance tools, including a stochastic driver, were developed, calibrated, and validated against coupon and component level test results. For this project, from the manufacturing side, the development efforts were focused on high-pressure resin transfer molding (HP-RTM), a potentially game-changing manufacturing technology that is capable of reaching the 3-5-minute cycle time that is necessary for volume manufacturing of composites. On the structural performance side, the crashworthiness of CF structures was studied. Accordingly, computational tools were developed and validated. The resulting differences between the numerical predictions and the experimental results in the first phase of the project were required to be less than 15%. During the second phase of the project, the manufacturing and performance tools were integrated by mapping the manufacturing outcomes (e.g., fiber angles, residual stresses, degree of cure, and defects) into the structural models. Also, using the tools developed in this project, an automotive assembly currently manufactured in steel (2016 GM Malibu) was redesigned to be manufactured using advanced CF composites with the objective of comparing the performance of the CF assembly with the developed ICME model predictions. The weight, performance and cost of the CF assembly were compared with the baseline steel assembly as well. The CF underbody design was shown to be 30% lighter than the corresponding steel design. The CF underbody assembly withstood the side pole impact with less than half the intrusion for the steel assembly. Excellent correlations within 10% for both peak impact load and intrusion were observed between the numerical predictions and experimental results. Based on the cost models developed in the project, the cost increase per Kg saved was determined to be $22. The project team has prepared a total of 28 publications in various journals and conferences and broadly communicated the project results for the benefit of the composite industry. The project team has also prepared a total of 10 patent applications that were submitted to the US Patent and Trademark office.

36 MATERIALS SCIENCE↗