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DOE OSTI2023

Microwave-assisted synthesis of iron sulfide motifs for electrochemical applications

Abstract The syntheses of FeS 2 and Fe 3 S 4 nanomaterials were optimized using a novel facile, surfactant-free, and microwave-assisted, one-pot synthesis method, run under ambient and reasonably mild reaction conditions. Synthetic parameters, such as metal precursor salt identity, reaction time, reaction temperature, metal:sulfur molar ratios, and solvent combinations, were all systematically investigated and optimized. A series of FeS 2 (pyrite) samples was initially fabricated using thioacetamide (TAA) as the sulfur precursor to generate a distinctive, uniform octahedra-based morphology. Switching the sulfur precursor from TAA to L-cysteine resulted in a corresponding transformation in not only chemical composition from FeS 2 to an iron thiospinel structure, Fe 3 S 4 (otherwise known as greigite), but also an associated morphological evolution from octahedra to nanosheet aggregates. The study of these materials has enabled crucial insights into the formation mechanisms of these materials under a relatively non-conventional microwave-assisted setting. Furthermore, in separate experiments, multi-walled carbon nanotubes (MWNTs) and graphene were added in with underlying metal sulfide species to create conductive Fe–S/MWNT composites and Fe–S/graphene composites, respectively. The method of addition of either MWNTs or graphene was also explored, wherein an ‘ ex-situ ’ synthetic procedure was found to be the least disruptive means of attachment and immobilization onto iron sulfide co-reagents as a means of preserving the latter’s inherent composition and morphology. The redox acidity for the parent material and associated composites demonstrates the utility of our as-developed synthetic methods for creating motifs relevant for electrochemical applications, such as energy storage.

25 ENERGY STORAGE↗

DOE OSTI2023

Packetized Energy Management: Coordinating Transmission and Distribution (Final Report)

The project Packetized Energy Management (PEM): Coordinating Transmission and Distribution was part of the ARPA-E NODES program from 2015 to 2023. The high-level goal of the project was to develop and demonstrate novel, scalable, and impactful technologies related to the coordination of networked distributed energy resources (DERs). By demonstrating responsive means by which fleets of DERs could be coordinated to enhance grid operation and reliability, the U.S. could accelerate renewable integration and electrification efforts and meet decarbonization goals.

25 ENERGY STORAGE↗

DOE OSTI2020

Synthetic residential load models for smart city energy management simulations

The ability to control tens of thousands of residential electricity customers in a coordinated manner has the potential to enact system-wide electric load changes, such as reduce congestion and peak demand, among other benefits. To quantify the potential benefits of demand-side management and other power system simulation studies (e.g. home energy management, large-scale residential demand response), synthetic load datasets that accurately characterize the system load are required. This study designs a combined top-down and bottom-up approach for modelling individual residential customers and their individual electric assets, each possessing their own characteristics, using time-varying queueing models. The aggregation of all customer loads created by the queueing models represents a known city-sized load curve to be used in simulation studies. The three presented residential queueing load models use only publicly available data. An open-source Python tool to allow researchers to generate residential load data for their studies is also provided. The simulation results presented consider the ComEd region (utility company from Chicago, IL) and demonstrate the characteristics of the three proposed residential queueing load models, the impact of the choice of model parameters, and scalability performance of the Python tool.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Coupling between Emissive Defects on Carbon Nanotubes: Modeling Insights

Covalent functionalization of single-walled carbon nanotubes (SWCNTs) with organic molecules results in red-shifted emissive states associated with sp 3 -defects in the tube lattice, which facilitate their improved optical functionality, including single-photon emission. The energy of the defect-based electronic excitations (excitons) depends on the molecular adducts, the configuration of the defect, and concentration of defects. In this work, we model the interactions between two sp 3 -defects placed at various distances in the (6,5) SWCNT using time-dependent density functional theory. Calculations reveal that these interactions conform to the effective model of J-aggregates for well-spaced defects (>2 nm), leading to a red-shifted and optically allowed (bright) lowest energy exciton. H-aggregate behavior is not observed for any defect orientations, which is beneficial for emission. The splitting between the lowest energy bright and optically forbidden (dark) excitons and the pristine excitonic band are controlled by the single-defect configurations and their axial separation. These findings enable a synthetic design strategy for SWCNTs with tunable near-infrared emission.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2020

3,4‐Dicyanothiophene—a Versatile Building Block for Efficient Nonfullerene Polymer Solar Cells

Abstract In this contribution, a versatile building block, 3,4‐dicyanothiophene (DCT), which possesses structural simplicity and synthetic accessibility for constructing high‐performance, low‐cost, wide‐bandgap conjugated polymers for use as donors in polymer solar cells (PSCs), is reported. A prototype polymer, PB3TCN‐C66, and its cyano‐free analogue polymer PB3T‐C66, are synthesized to evaluate the potential of using DCT in nonfullerene PSCs. A stronger aggregation property in solution, higher thermal transition temperatures with higher enthalpies, a larger dipole moment, higher relative dielectric constant, and more linear conformation are exhibited by PB3TCN‐C66. Solar cells employing IT‐4F as the electron acceptor offer power conversion efficiencies (PCEs) of 11.2% and 2.3% for PB3TCN‐C66 and PB3T‐C66, respectively. Morphological characterizations reveal that the PB3TCN‐C66:IT‐4F blend exhibits better π–π paracrystallinity, a contracted domain size, and higher phase purity, consistent with its higher molecular interaction parameter, derived from thermodynamic calculations. Moreover, PB3TCN‐C66 offers a higher open‐circuit voltage and reduced energy loss than most state‐of‐the‐art wide‐bandgap polymers, without the need of additional electron‐withdrawing substituents. Two additional polymers derived from DCT also demonstrate promising performance with a higher PCE of 13.4% being achieved. Thus, DCT represents a versatile and promising building block for constructing high‐performance, low‐cost, conjugated polymers for application in PSCs.

Zhang, Bo↗

DOE OSTI2021

Introducing Low-Cost Pyrazine Unit into Terpolymer Enables High-Performance Polymer Solar Cells with Efficiency of 18.23%

Recently, a random ternary copolymerization strategy has become a promising and efficient approach to develop high-performance polymer donors for polymer solar cells (PSCs). Here, in this study, a low-cost electron-withdrawing unit, 2,5-bis(4-(2-ethylhexyl)thiophen-2-yl)pyrazine (PZ-T), is incorporated into the polymer backbone of PM6 as the third component, and three D-A 1 -D-A 2 type terpolymers PMZ-10, PMZ-20, and PMZ-30 are synthesized by the random copolymerization strategy, with the PZ-T proportion of 10%, 20%, and 30%, respectively. The terpolymers exhibit downshifted highest occupied molecular orbital energy levels than PM6, which is beneficial for obtaining higher open-circuit voltage (V oc ) of the PSCs with the polymer as a donor. Importantly, the PSCs based on PMZ-10:Y6 demonstrate efficient exciton dissociation, higher and balanced electron/hole mobilities, desirable aggregation, and high power conversion efficiency of 18.23%, which is the highest efficiency among the terpolymer-based PSCs so far. The results indicate that the ternary copolymerization strategy with PZ-T as the second A-unit is an efficient approach to further improve the photovoltaic performance and reduce the synthetic cost of the D-A copolymer donors.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Machine learning-informed and synthetic biology-enabled semi-continuous algal cultivation to unleash renewable fuel productivity

Abstract Algal biofuel is regarded as one of the ultimate solutions for renewable energy, but its commercialization is hindered by growth limitations caused by mutual shading and high harvest costs. We overcome these challenges by advancing machine learning to inform the design of a semi-continuous algal cultivation (SAC) to sustain optimal cell growth and minimize mutual shading. An aggregation-based sedimentation (ABS) strategy is then designed to achieve low-cost biomass harvesting and economical SAC. The ABS is achieved by engineering a fast-growing strain, Synechococcus elongatus UTEX 2973, to produce limonene, which increases cyanobacterial cell surface hydrophobicity and enables efficient cell aggregation and sedimentation. SAC unleashes cyanobacterial growth potential with 0.1 g/L/hour biomass productivity and 0.2 mg/L/hour limonene productivity over a sustained period in photobioreactors. Scaling-up the SAC with an outdoor pond system achieves a biomass yield of 43.3 g/m 2 /day, bringing the minimum biomass selling price down to approximately $281 per ton.

09 BIOMASS FUELS↗

NASA NTRS2018

Is Water Necessary for Life?

The universality of water as the solvent for life is usually justified by its role in supporting the rich organic chemistry. It has been pointed out, however, that even richer synthetic chemistry is possible in other organic solvents. Does it mean that water is not necessary for life? Here, other, essential criteria for solvent for life that have not been sufficiently considered are discussed. In biological systems, complex molecules are not only constantly synthesized but also degraded. Solvent-mediated degradation is essential for regulating cell content, preventing overcrowding and allowing for recycling organic material. Achieving a balance between synthetic and degradative processes is facile in water, but not in many other organic liquids. Thus, the so-called “water paradox” according to which water is both necessary to life and toxic to biopolymer synthesis might not be paradoxical at all. The machinery of life is based on non-covalent interactions that do not involve making or breaking chemical bonds. Their strength needs to be properly tuned. If they are too weak, there might be undesired response to natural fluctuations of physical or chemical parameters. If they are too strong, the kinetics and energetics of cellular processes could adversely influenced. The solvent must allow for balancing these interactions, which provides strong, universal constraints on the medium for life. Water influences non-covalent interactions mainly by two mechanisms. First, it reduces strong, electrostatic interactions between molecules, chemical groups or atoms carrying electric charge or dipole. Second, it induces the hydrophobic effect, the tendency to remove non-polar (hydrophobic) molecules and groups from direct contact with aqueous solution and, instead, interact with each other. In living systems, the hydrophobic effect is largely responsible for self-organization of molecules to more complex structures, such as aggregation of lipid molecules to form biological membranes and protein folding. Water exists as stable liquid in a large temperature range, and the hydrophobic effects are a consequence of the temperature insensitivity of essential properties of its liquid state. In summary, water accomplishes an amazing feat – it reduces strong interactions between dissolved species and simultaneously increases the strength of weak interactions, bringing all of them to the right range. Once we consider not only synthetic capabilities but also other required traits of the solvent for life, no viable alternative to water is currently known.

Life↗

DOE OSTI2024

Conjugated Zwitterionic Oligomers as Ligands on Perovskite Nanocrystals: Hybrid Structures with Tunable Interparticle Spacing

Conventional ligands for CsPbBr 3 perovskite nanocrystals (NCs), composed of polar, coordinating head groups (e.g., ammonium or zwitterionic) and aliphatic tails, are instrumental in stabilizing the NCs against sintering and aggregation. Nonetheless, the aliphatic (insulating) nature of these ligands represents drawbacks with respect to objectives in optoelectronics, and yet removing these ligands typically leads to a loss of colloidal stability. Here, in this paper, we describe the preparation of CsPbBr 3 NCs in the presence of discrete conjugated oligomers that were prepared by an iterative synthetic approach and capped at their chain ends with sulfobetaine zwitterions for perovskite coordination. Notably, these zwitterionic oligofluorenes are compatible with the hot injection and ligand exchange conditions used to prepare CsPbBr 3 NCs, yielding stable NC dispersions with high photoluminescence quantum yields (PLQY, >90%) and spectral features representative of both the perovskite core and conjugated ligand shell. Controlling the chain length of these capping ligands effectively regulated inter-NC spacing and packing geometry when cast into solid films, with evidence derived from both transmission electron microscopy (TEM) and grazing incidence X-ray scattering measurements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Photophysics of graphene quantum dot assemblies with axially coordinated cobaloxime catalysts

We report a study of chromophore-catalyst assemblies composed of light harvesting hexabenzocoronene (HBC) chromophores axially coordinated to two cobaloxime complexes. The chromophore-catalyst assemblies were prepared using bottom-up synthetic methodology and characterized using solid-state NMR, IR, and x-ray absorption spectroscopy. Detailed steady-state and time-resolved laser spectroscopy was utilized to identify the photophysical properties of the assemblies, coupled with time-dependent DFT calculations to characterize the relevant excited states. The HBC chromophores tend to assemble into aggregates that exhibit high exciton diffusion length (D = 18.5 molecule 2 /ps), indicating that over 50 chromophores can be sampled within their excited state lifetime. We find that the axial coordination of cobaloximes leads to a significant reduction in the excited state lifetime of the HBC moiety, and this finding was discussed in terms of possible electron and energy transfer pathways. By comparing the experimental quenching rate constant (1.0 × 10 9 s -1 ) with the rate constant estimates for Marcus electron transfer (5.7 × 10 8 s -1 ) and Förster/Dexter energy transfers (8.1 × 10 6 s -1 and 1.0 × 10 10 s -1 ), we conclude that both Dexter energy and Marcus electron transfer process are possible deactivation pathways in CoQD-A. No charge transfer or energy transfer intermediate was detected in transient absorption spectroscopy, indicating fast, subpicosecond return to the ground state. Finally, these results provide important insights into the factors that control the photophysical properties of photocatalytic chromophore-catalyst assemblies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Real-time deep-learning inversion of seismic full waveform data for CO 2 saturation and uncertainty in geological carbon storage monitoring

Deep-learning inversion has recently drawn attention in geological carbon storage research due to its potential of imaging and monitoring carbon storage in real time, significantly improving efficiency and safety of carbon storage operations. We present a deep-learning full waveform inversion method that after the neural network has been trained can image CO 2 saturation and its uncertainty in real time. Our deep-learning inversion method is based on the U-Net architecture with the neural network trained on pairs of synthetic seismic data and CO 2 saturation models. Accordingly, our training establishes a mapping relationship between seismic data and CO 2 saturation models and once fully trained directly estimates CO 2 saturation as a function of subsurface location. We further quantify uncertainties of CO 2 saturation estimates using the Monte Carlo dropout method and a bootstrap aggregating method. For this proof-of-concept study, the CO 2 training models and data are derived from the Kimberlina 1.2 model, a hypothetical 3D geological carbon storage model that is constructed based on various geological and hydrological data from the Southern San Joaquin Basin, California. We perform deep-learning inversion experiments using noise-free and noisy training and test data sets and compare the results. Our modelling experiments show that (1) the deep-learning inversion can estimate 2D distributions of CO 2 fairly well even in the presence of Gaussian random noise and (2) both CO 2 saturation imaging and uncertainty quantification can be done in real time. Our results suggest that the deep-learning inversion method can serve as a robust real-time monitoring tool for geological carbon storage and/or other time-varying reservoir/aquifer properties that result from injection, extraction, and/or other subsurface transport phenomena.

58 GEOSCIENCES↗

NASA NTRSDate not supplied

Understanding thermal stability in doped zirconia aerogels for high temperature applications

The high porosities and low densities of ceramic aerogels offer outstanding insulative performance in applications where weight is a critical factor. The high surface-to-volume ratios and specific surface areas provide extremely low thermal conductivity, but also contribute to rapid densification of the pore structure at elevated temperatures. This densification diminishes their favorable properties and inhibits use of aerogels in high temperature applications. The purpose of this work is the establishment of a design framework for thermally stable, highly porous materials. Here we will review our recent studies on the effects of synthetic parameters and dopant chemistry on the evolution of zirconia-based aerogels. The structural evolution was studied to 1200 °C using nitrogen physisorption, scanning and transmission electron microscopy, and x-ray diffraction. The role of dopant identity and concentration in thermal stability was elucidated. In context of the design framework, dopant chemistry is an aggregate for many closely related material properties, each of which may contribute to aerogel structural evolution. To develop a truly predictive design framework for ceramic-based aerogels, systematic and comprehensive evaluation of thermodynamic and kinetic properties must be performed in conjunction with studies on structural evolution.

aerogel↗

DOE OSTI2020

Energetic decomposition yields efficient bimetallic Cu MOF-derived catalysts

Metal–organic frameworks (MOFs) have recently emerged as efficient self-sacrificial templates to fabricate porous carbon-supported metal nanoparticles (NPs). Due to observed increased activity, catalysts containing bimetallic NPs represent an active frontier for heterogeneous catalyst development. A strategy to synthesize active catalysts with highly dispersed bimetallic metal/metal oxides within a porous carbon matrix via rapid MOF decomposition using dopants is presented in this paper. A 2,4,6-trinitrotoluene (TNT) additive enhances the rapid thermolysis of the metal-doped Cu-based MOFs to minimize particle aggregation. Catalyst characterization reveals that a secondary metal increases dispersion of both metals over the carbon composite support. The catalyst preparation method influences both the metal particle size and oxidation state. Catalytic performance shows increased rates for 4-nitrophenol reduction even with <1 wt% of added secondary metal. Among the synthesized catalysts, the Ni–CuO@C bimetallic catalyst exhibits outstanding activity. This synthetic strategy is useful for creating highly efficient, robust, non-noble metal catalysts for development of sustainable chemical processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Polymer nanoparticle photocatalysts realized in non-aqueous solvents

Colloidal organic nanoparticles (oNPs) have emerged as a promising category of photocatalyst, thanks to their long-lived surface-bound charges, electronic tunability, and strong absorption in the visible spectrum. Our previous research has established a direct correlation between charge generation in oNPs and their photocatalytic activity, highlighting their effectiveness as a framework for stable, long-lived free carriers. However, oNPs have been restricted to use only in aqueous environments as a result of being synthesized via either nano-emulsion or nano-precipitation procedures. Herein, we present a method for transferring oNP photocatalysts from water into polar non-aqueous solvents while retaining their long-term colloidal stability. We observed that the polymer chains in the solvent-transferred oNPs rearrange from a predominantly H-aggregate structure in water to a combination of H- and J-aggregate characteristics in N,N-dimethylformamide, suggesting a dynamic rearrangement in response to the new solvent environment. Importantly, transient absorption and time-resolved microwave conductivity measurements confirm that the solvent-transferred oNPs maintain their ability to generate free charges at an internal heterojunction. This development opens unique opportunities for eventually leveraging light-generated, long-lived electrons and holes in synthetic redox chemistry across diverse solvent environments, a direction that will be explored in future studies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1993

International collaboration in SAR ground data systems

A set of considerations that are pertinent to future international cooperation in the area of synthetic aperture radar (SAR) ground data systems are presented. The considerations are as follows: (1) success of future spaceborne SAR missions will require multi-agency and/or multi-national collaboration; (2) ground processing is typically performed by each agency for their user base; (3) international standards are required to achieve a uniform data product independent of the processing center; (4) to reduce the aggregate cost of the ground data systems, collaboration is required in design and development; (5) effective utilization of the data by an international user community; (6) commercialization of data products; and (7) security of data systems.

Curlander, John C.↗

DOE OSTI2024

Synthetic β-sheets mimicking fibrillar and oligomeric structures for evaluation of spectral X-ray scattering technique for biomarker quantification

Archetypical cross-β spines sharpen the boundary between functional and pathological proteins including β-amyloid, tau, α-synuclein and transthyretin are linked to many debilitating human neurodegenerative and non-neurodegenerative amyloidoses. An increased focus on development of pathogenic β-sheet specific fluid and imaging structural biomarkers and conformation-specific monoclonal antibodies in targeted therapies has been recently observed. Identification and quantification of pathogenic oligomers remain challenging for existing neuroimaging modalities. We propose two artificial β-sheets which can mimic the nanoscopic structural characteristics of pathogenic oligomers and fibrils for evaluating the performance of a label free, X-ray based biomarker detection and quantification technique. Highly similar structure with elliptical cross-section and parallel cross-β motif is observed among recombinant α-synuclein fibril, Aβ-42 fibril and artificial β-sheet fibrils. We then use these β-sheet models to assess the performance of spectral small angle X-ray scattering (sSAXS) technique for detecting β-sheet structures. sSAXS showed quantitatively accurate detection of antiparallel, cross-β artificial oligomers from a tissue mimicking environment and significant distinction between different oligomer packing densities such as diffuse and dense packings. The proposed synthetic β-sheet models mimicked the nanoscopic structural characteristics of β-sheets of fibrillar and oligomeric states of Aβ and α-synuclein based on the ATR-FTIR and SAXS data. The tunability of β-sheet proportions and shapes of structural motifs, and the low-cost of these β-sheet models can become useful test materials for evaluating β-sheet or amyloid specific biomarkers in a wide range of neurological diseases. By using the proposed synthetic β-sheet models, our study indicates that the sSAXS has potential to evaluate different stages of β-sheet-enriched structures including oligomers of pathogenic proteins.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Non-Intrusive Appliance Identification with Appliance-Specific Networks

The problem of noninstrusive load monitoring (NILM) is usually formulated as a single-channel blind source separation task, whose successful solution enable fast and convenient load identification and energy disaggregation. When applied at test time, NILM algorithms aim to identify the operating characteristics of individual appliances from an aggregate power measurement of the entire house. Recent advances in deep learning gave rise to many methods that mostly focus on learning a direct mapping from aggregate measurement to individual appliance power. However, these methods are not only computationally expensive, but they often suffer from overfitting and do not generalize very well. In this article, we propose a novel NILM method that leverages advances in statistical learning that have not been properly applied in this domain before. The proposed method consists of three stages: first, a Bayesian nonparametric learning-based approach for appliance state extraction; second, synthetic minority oversampling technique for data augmentation and mitigating the heavy imbalance in switching events; and third, appliance-specific lightweight long short-term memory networks for status classification for each appliance. Here, we adopt a “differential” input (the difference before and after the switching event) to reduce the complexity of network training and make the proposed method robust to multiappliance switching events. Experiments are conducted to demonstrate the effectiveness of the proposed method, achieving superior performance when compared to recent methods. An ablation study is conducted to demonstrate the effectiveness of each module of our method. Finally, we investigate the quality of generated synthetic samples.

42 ENGINEERING↗

DOE OSTI2020

Background Information on ARPA-E's REUSE Program (White Paper)

Under the REUSE Topic, ARPA-E seeks to fund the development of technologies to convert high-energy materials currently going to landfills to a high-energy content liquid product capable of displacing energy imports used for fuel or chemical production. The high-energy materials include plastics (#1-7 polymers, rubber, and composites) and paper. As discussed below, we estimate 30-34 MM ton plastic, 2-6 MM ton rubber, 18 MM ton of paper, and up to 0.1 MM ton composites are potentially available annually for this purpose. These numbers may be conservative based on changes in the plastic and paper export markets. ARPA-E anticipates deployment of multiple low-cost, simple, flexible, small-scale (100-500 ton per day) regional facilities using modular plants. This scale is consistent with the sources for high-energy materials, which include ~300 Material Recovery Facilities and industrial waste sources. The assumption is that such facilities can be more economical than the paradigm of large-scale facilities making purity products, due to cost for transporting and aggregating waste and the high operating costs (OPEX) and capital cost (CAPEX) for product purification. This document gives a brief technical review for multiple potential process technologies. The review is not intended to be comprehensive or limiting, only to provide an introduction to potential Applicants.

10 SYNTHETIC FUELS↗