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DOE OSTI2022

Determination of the Structures of Lignin Subunits and Nanoparticles in Solution by Small‐Angle Neutron Scattering: Towards Improving Lignin Valorization

Abstract Lignin nanoparticles (LNPs) are usually produced from lignin solution through supersaturation. The structure of the lignin in solution is still poorly understood due to structural variability of isolated lignins. Here, lignins were extracted from different plants to establish a general pattern of their structure in several lignin solvents. Lignin molecules (lignin subunits) and larger aggregates were observed in dimethyl sulfoxide (DMSO), ethylene glycol (EG) and 0.1 N NaOD solutions by small‐angle neutron scattering (SANS). It was proposed that the aggregates were composed of lignin subunits with a higher molecular weight and a higher ratio of the aliphatic to phenolic hydroxyl groups. The size, shape, and compactness are important factors that affect the uses of the LNPs, which were obtained from the SANS data for the first time. A discrepancy in the radius between SANS and DLS was discovered, pointing to a large hydration shell around the LNPs in aqueous solutions. The cytotoxicity of the corncob lignin, kraft lignin, and their LNPs were measured and compared.

Zhang, Xin↗

DOE OSTI2022

In‐operando crystallization study of zinc nitrate hexahydrate using zinc oxide nucleators

Abstract Supercooling (∆T Sup ) is one of the crucial problems in utilizing a phase change material (PCM), which has been attempted to overcome using nucleators possessing small lattice disregistry without comprehensive understanding of the nucleation phenomenon. Here, this work studies the interactions between nucleators and PCM via in‐operando direct visualization for the first time, to the best of our knowledge, to better understand the crystallization process during freezing of a PCM using zinc nitrate hexahydrate (ZNH) and a zinc oxide (ZnO) nucleator. According to our in‐operando study, freezing was randomly initiated by only a fraction of the nucleator particles during each thermal cycling. However, previously unresponsive nucleators also suddenly crystalized PCM when the propagating crystal encountered them, improving the crystal initiation and thereby ∆T Sup . Consequently, for equal wt% of ZnO, better nucleation behavior was obtained using uniformly distributed small nucleator particles throughout the PCM, as compared to either large or poorly distributed aggregated nucleators. DSC results using ZnO‐needle as nucleator confirmed a 38% and 33.3% lower ∆T Sup upon employing 5 wt% small (individual) particles (~4 μm on average), as compared to using equal wt% of small (aggregated) particle clusters (~200 μm) and large particles (~46 μm), respectively. Crystallization of ZNH caused additional hair‐like ZnO growth preferentially decorated along lateral faces of the original nucleator particles. The in‐operando studies are valuable tools to correlate inherent crystallization phenomena to the practical thermal energy storage properties of the system.

Chakraborty, Anirban↗

DOE OSTI2020

Lipids status and copper in a single astrocyte of the rat model for amyotrophic lateral sclerosis: Correlative synchrotron-based X-ray and infrared imaging

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease, causing death of motor neurons controlling voluntary muscles. The pathological mechanisms of the disease are only partially understood. The hSOD1-G93A ALS rat model is characterized by an overexpression of human mutated SOD1, causing increased vulnerability by forming intracellular protein aggregates, inducing excitotoxicity, affecting oxidative balance and disturbing axonal transport. In this study we followed the bio-macromolecular organic composition and compartmentalization together with trace metal distribution in situ in single astrocytes from the ALS rat model and compared them to the control astrocytes from nontransgenic littermates by simultaneous use of two synchrotron radiation-based methods: Fourier transform infrared microspectroscopy (SRFTIR) and hard X-ray fluorescence microscopy (XRF). Here we show that ALS cells contained more Cu, which colocalized with total lipids, increased carbonyl groups and oxidized lipids, thus implying direct involvement of Cu in oxidative stress of lipidic components without direct connection to protein aggregation in situ.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Ionic Liquid Facilitated Solvent‐Phase Polymerization of Ultrasmooth Coatings of Polycatecholamines

Mussel-inspired polycatecholamine coatings and films have proven to be versatile materials for surface modification. However, the progress of chemically modified coatings with tailored properties has been slow due to the lack of definitive evidence of their polymeric structure. Polycatecholamines form aggregates during polymerization, and their formation mechanism has been a subject of debate owing to their insolubility in traditional molecular solvents. Exploiting the capability of ionic liquids (ILs) to exhibit strong electrostatic interactions, herein, the first solution-phase polymerization approach is reported to achieve polymerization of four catecholamines – dopamine (DA), norepinephrine (NE), L-3,4-dihydroxyphenylalanine (L-DOPA), and adrenaline (AD). Kinetic control over the polymerization process in the solution phase enabled it to follow the process with 1 H NMR spectroscopy, revealing the formation of structural features of resulting complex heterogeneous and soluble polymers. The polymers are both covalent and associative in nature. Solution phase polymerization prevented the formation of large aggregates in the solution, thus facilitating the formation of coatings that are ultra-smooth and have root mean square roughness of the order of sub-nm to nm scale.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Preferred Void Orientation in Uniaxially Pressed PBX 9502

Ultra- and small-angle neutron scattering techniques were used to study the morphology of voids in directions parallel and perpendicular to the compaction plane of a uniaxially pressed cylinder of PBX 9502. Two-dimensional scattering patterns from samples cut parallel to the compaction plane had circular equal-intensity contours, implying that along this view the voids are circular or randomly oriented. Identical measurements of samples cut perpendicular to the compaction plane produced elliptical equal-intensity contours, indicating preferred orientation of voids. Analysis of the two dimensional scattering patterns confirmed that the voids are non-spherical with an average aspect ratio of 1.20, flattened so that the larger dimensions of the voids lie within the compaction plane. Model analysis of the combined ultra- and small-angle neutron scattering curves revealed that the PBX 9502 porosity is interconnected, in the form of aggregates comprised of non-spherical, primary voids. The volume dimension was found to be the same in both directions, indicating that the aggregate is randomly oriented throughout the sample, and that it is the primary voids that are preferentially oriented. Furthermore, void interfaces with the surrounding matrix were found to be rough or polydisperse, with a common roughness dimension or polydispersity in all directions.

42 ENGINEERING↗

DOE OSTI2023

Structural insights into the unique recognition module between α-synuclein peptide and nanobody

Nanobodies are single-domain fragments of antibodies with comparable specificity and affinity to antibodies. They are emerging as versatile tools in biology due to their relatively small size. Here, we report the crystal structure of a specific nanobody Nbα-syn01, bound to a 14 amino acid long peptide of α-synuclein (αSyn), a 140-residue protein whose aggregation is associated with Parkinson's disease. The complex structure exhibits a unique binding pattern where the αSyn peptide replaces the N-terminal region of nanobody. Recognition is mediated principally by extended main chain interaction of the αSyn peptide and specificity of the interaction lies in the central 48–52 region of αSyn peptide. Structure-guided truncation of Nbα-syn01 shows tighter binding to αSyn peptide and improved inhibition of α-synuclein aggregation. The structure of the truncated complex was subsequently determined and was indistinguishable to full length complex as the full-length form had no visible electron density for the N-terminal end. These findings reveal the molecular basis for a previously unobserved binding mode for nanobody recognition of α-synuclein, providing an explanation for the enhanced binding, and potential for an alternate framework for structure-based protein engineering of nanobodies to develop better diagnostic and therapeutic tools.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Long‐term changes in soil carbon and nitrogen fractions in switchgrass, native grasses, and no‐till corn bioenergy production systems

Cellulosic bioenergy is a primary land-based climate mitigation strategy, with soil carbon (C) storage and nitrogen (N) conservation as important mitigation elements. Here, we present 13 years of soil C and N change under three cellulosic cropping systems: monoculture switchgrass (Panicum virgatum L.), a five native grasses polyculture, and no-till corn (Zea mays L.). Soil C and N fractions were measured four times over 12 years. Bulk soil C in the 0–25 cm depth at the end of the study period ranged from 28.4 (± 1.4 se) Mg C ha −1 in no-till corn, to 30.8 (± 1.4) Mg C ha −1 in switchgrass, and to 34.8 (± 1.4) Mg C ha −1 in native grasses. Mineral-associated organic matter (MAOM) ranged from 60% to 90% and particulate organic matter (POM) from 10% to 40% of total soil C. Over 12 years, total C as well as both C fractions persisted under no-till corn and switchgrass and increased under native grasses. In contrast, POM N stocks decreased 33% to 45% across systems, whereas MAOM N decreased only in no-till corn and by less than 13%. Declining POM N stocks likely reflect pre-establishment land use, which included alfalfa and manure in earlier rotations. Root production and large soil aggregate formation explained 69% (p < 0.001) and 36% (p = 0.024) of total soil C change, respectively, and 60% (p = 0.020) and 41% (p = 0.023) of soil N change, demonstrating the importance of belowground productivity and soil aggregates for producing and protecting soil C and conserving soil N. Differences between switchgrass and native grasses also indicate a dependence on plant diversity. Soil C and N benefits of bioenergy crops depend strongly on root productivity and pre-establishment land use.

09 BIOMASS FUELS↗

DOE OSTI2020

Quantized Grain Boundary States Promote Nanoparticle Alignment During Imperfect Oriented Attachment

Oriented attachment (OA) has become a well-recognized mechanism for the growth of metal, ceramic, and biomineral crystals. While many computational and experimental studies of OA have shown that particles can attach with some misorientation then rotate to remove adjoining grain boundaries, the underlying atomistic pathways for this “Imperfect OA” process remain the subject of debate. In this paper, molecular dynamics and in situ TEM were used to probe the crystallographic evolution of up to 30 gold and copper nanoparticles during aggregation. It was found that Imperfect OA occurs because (1) grain boundaries become quantized when their size is comparable to the separation between constituent dislocations and (2) kinetic barriers associated with the glide of grain boundary dislocations are small. In support of these findings, TEM experiments show the formation of a single crystal aggregate after annealing 9 initially misoriented, agglomerated particles with evidence of dislocation slip and twin formation during particle/grain alignment. These observations motivate future work on assembled nanocrystals with tailored defects and call for a revision of Read-Shockley models for grain boundary energies in nanocrystalline materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Pressure–Modulated Luminescence Enhancement and Quenching in a Hydrogen–Bonded Organic Framework

Light emission in the solid state is central for illumination, sensing, and imaging applications. Unlike luminescence in dilute solutions, where the excited states are unimolecular in nature, intermolecular interaction plays a significant role in the quantum yield of solid-state luminophores, manifested as competing aggregation-caused quenching (ACQ) and aggregation-induced enhancement (AIE). Both effects are extensively studied in various systems; however, it remains unclear how their competition depends on molecular conformation and intermolecular stacking. Here the direct observation of pressure-modulated AIE-ACQ competition in a crystalline hydrogen-bonded organic framework (HOF) is reported. Using in situ spectroscopies and computational modeling, the intramolecular vibration and intermolecular π–π stacking directly responsible for the non-radiative decay of the excited state are identified. The extent of these two contributions is modulated by hydrostatic pressure and guest molecules in the HOF pores. Furthermore, this work demonstrates a physically neat model system to understand and control solid-state luminescence, and a potential material platform for piezoluminescent sensing.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

De Nive Quinquangula: Pentagonal Snowflake Metal Nanocrystals as an Example of Emergence Phenomenon in Nanotechnology Complex Systems

The formation of snowflakes (SFL) is one of the most captivating phenomena in nature. The fabrication of multimetallic gold (Au) nanoparticles containing copper (Cu) and iron (Fe) is reported, which adopt snowflake-like morphology after nanoparticle aggregation. The synthesis of these snowflake-like Au microcrystals occurs mainly by kinetic control. In this process, a surfactant-assisted salt reduction method is employed on a heated substrate. Here, the metal salts react within seconds to form nanoparticles. This process results in a hierarchical structure with pseudo-pentagonal symmetry and chiroptical activity. We discuss how large superstructures emerge from nanoparticle aggregation, resembling natural snowflakes. However, unlike ice snowflakes, which exhibit hexagonal symmetry, the Au snowflakes display pentagonal symmetry. It is proposed that the formation of these snowflake-like microcrystals is the result of the complexity involved in the crystal growth process and represents an example of the phenomenon of emergence, which has become very significant in several fields of modern science, including physics, biology, chemistry, economics, philosophy, and poetry. The term emergent is used to evoke the collective behavior of a large number of microscopic constituents that is qualitatively different than the behaviors of the individual constituents.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Modulating Energy Level on an A‐D‐A′‐D‐A‐Type Unfused Acceptor by a Benzothiadiazole Core Enables Organic Solar Cells with Simple Procedure and High Performance

Unfused‐ring acceptors (UFAs) have gained considerable research attention as they offer simple chemical structures through simplified synthesis methods, which would boost the commercialization of organic solar cells (OSCs). Recently, a new small molecule acceptor (SMA) named Y6 was reported, yielding high‐performance OSCs. Herein, the Y6‐like A‐DA′D‐A framework is developed to A‐D‐A′‐D‐A‐type backbone adopted in constructing UFAs. Two new Y6‐like UFAs are synthesized within four steps and the effect of noncovalent atoms at the central electron‐deficient core on material properties and device performances is studied. It is found that the introduction of fluorine atoms can bring larger red‐shift in the absorption spectra and better aggregation of the resulting UFA film states compared with those of oxygen atoms. Interestingly, the variations in the noncovalent interaction atoms induce different intermolecular charge transfer between donors and UFAs. When blended with another economical donor, PTQ10, F substitution at the benzothiadiazole ring is more effective than O substitution, leading to the increased short‐circuit current density ( J SC ) and higher efficiency of over 12%, among the best performances of UFA‐based OSCs. This contribution demonstrates the appropriate introduction of noncovalent interaction is a promising method for tuning energy levels, absorption, and aggregation of UFAs for high‐performance OSCs.

Yu, Han↗

DOE OSTI2021

Enabling AI-Accelerated Multiscale Modeling of Thrombogenesis at Millisecond and Molecular Resolutions on Supercomputers

We report the first congruent integration of HPC, AI, and multiscale modeling (MSM) for solving a mainstream biomechanical problem of thrombogenesis involving 6 million particles at record molecular-scale resolutions in space and at simulation rates of milliseconds per day. The two supercomputers, the IBM Summit-like AiMOS and our University’s SeaWulf, are used for scalability analysis of, and production runs with, the LAMMPS with our customization and AI augmentation and they attained optimal simulation speeds of 3,077 µs/day and 266 µs/day respectively. The long-time and large scales simulations enable the first study of the integrated platelet flowing, flipping, aggregating dynamics in one dynamically-coupled production run. The platelets’ angular and translational speeds, membrane particles’ speeds, and the membrane stress distributions are presented for the analysis of platelets’ aggregations.

Zhu, Yicong↗

DOE OSTI2023

A simple way to integrate distributed storage into a wholesale electricity market

Abstract Current plans to decarbonize the electric supply system imply that the generation from wind and solar sources will grow substantially. This growth will increase the uncertainty of system operations due to the inherent variability of these renewable sources, and as a result, more reserve capacity will be required to provide the ramping (flexibility) needed for reliable operations. This paper assumes that all of the increased uncertainty comes from wind farms on the grid, and it shows how distributed storage managed locally by aggregators can provide the ramping needed without introducing a separate market for flexibility. This can be accomplished when the aggregators minimize the expected daily cost of the energy purchased from the grid for their customers by submitting optimal bids into the wholesale market with high and low price thresholds for discharging and charging the storage. This model is illustrated using a stochastic multi-period security constrained optimal power flow together with realistic data for a reduction of the network in the Northeast Power Coordinating Council region of the United States. The results show that the bidding strategy for distributed storage provides ramping to the grid just as effectively as storage managed by a system operator.

Lamadrid, Alberto J.↗

DOE OSTI2023

Oxidation mechanism in a refractory multiple-principal-element alloy at high temperature

Refractory multiple-principal-element alloys (RMPEAs) are promising structural materials to enable increased power efficiency in high-temperature oxidation environments, but the oxidation behavior and microstructures of the oxides, especially at the beginning of the oxidation, have received limited attention. Here, the oxidation mechanism in an equimolar W-Mo-Ta-Nb-V was investigated at 1300 °C and compared with the equimolar W-Mo-Ta-Nb alloy without V. The oxide scale on WMoTaNbV after 1 min exposure is shown to be composed of a degradation layer at the interface of the alloy/oxide, an initial oxide transition layer, followed by the main phase aggregate oxide layer, and an outermost oxide layer. At the early stage of oxidation, the absorption of oxygen by the RMPEA substrate forms a solid solution. Vanadium accelerates the initial degradation process as it forms VO. The initial oxidation-induced degradation of RMPEA follows a sequence governed by the free energy change accompanied by local element segregation. Liquid V-Mo oxides aggregate in the intermediate oxide layer. The inward growth of the oxide scale is controlled by the local composition changes, the orientation of the substrate, the crystal structure, and physical properties such as melting points of the oxides.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Results of an interlaboratory study on the working curve in vat photopolymerization II: Towards a standardized method

The working curve measurement in photopolymer additive manufacturing is a ubiquitous measure of the cure depth of a printing resin as a function of radiant exposure of light. The fit parameters from this measurement (the depth of light penetration D p and the critical exposure E c ) are used to evaluate and report a resin’s printability, optimize processing parameters, and inform print and resin quality control. Despite its widespread use, the working curve lacks a standard measurement method. Here, following up on our paper “Results of an Interlaboratory Study on the Working Curve in Vat Photopolymerization” from last year, an interlaboratory study on the working curve was performed using calibrated, reproducible, bandpass filtered light sources. With these light sources, the variability between labs in measured working curves was dramatically reduced from the initial interlaboratory study. Aggregate data from this experiment produced reliable D p and E c measurements at 385 nm of 39.2 ± 3.7 µm and 12.3 ± 3.0 mJ cm −2 , respectively. At 405 nm the values of D p and E c are 69.3 ± 3.8 µm and 17.9 ± 2.3 mJ cm −2 , respectively. The results are agnostic to the thickness measurement tool utilized by participants, ensuring broad applicability across laboratories. We also tested the generalizability of the proposed method of using a filtered light source by filtering a commercial 405 nm light source and obtaining a working curve in agreement with the aggregate data from the interlaboratory study. This interlaboratory study provides a basis for a documentary standard for the working curve, so that the entire photopolymer additive manufacturing industry can share reproducible and interoperable working curve data.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Modeling occupancy-driven building loads for large and diversified building stocks through the use of parametric schedules

Building energy modeling provides a fundamental tool to assess the potential for energy efficiency to contribute to reducing world energy consumption and global emissions. Occupancy-related operations are a key source of uncertainty for building energy analysis, particularly for aggregated building stocks. At a district or city level, it is critical to estimate aggregated power load profiles for sizing power grid infrastructure, power plant capacity allocation, and energy efficiency measures. The stochastic nature of behavior-related operations complicates the creation of models that accurately capture building load profiles for entire building stocks. This research introduces a new methodology called parametric schedules to model occupancy-driven schedules for large and diverse building stocks. In contrast to computationally expensive methodologies proposed in the literature, our work does not use a recursive time-consuming step. Occupancy is estimated by the extrapolation of operation times directly from metered electric consumption data; occupancy-related schedules are stochastically assigned to each building model, guaranteeing diversity of operation times in the stock. Our procedure has been tested on a large, diversified data-set of 25,000 commercial buildings in Los Angeles, California. It proved to be able to adequately represent the stochastic schedules diversity of the stock and to refine the stock calibration process by 1%. This innovative approach represents a useful asset for utility companies, grid operators, urban planners, and balancing authorities, seeking to improve building stock modeling and better estimate the impact of energy conservation measures. – This work is part of a larger stock modeling tool called ComStock, which is under development by NREL.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

Short-term apartment-level load forecasting using a modified neural network with selected auto-regressive features

Residential electricity load profiles and their diversity have become increasingly important to realize the benefits of Smart or Transactive Energy Networks (TENs). An important element of TENs will be practical, accurate, and implementable residential load forecasting techniques. While there have been many approaches to short-term load forecasting, few have included forecasting for individual households, partly because the high volatility and idiosyncrasies present in individual household load data can pose significant challenges. In this study, we develop a Convolutional Long Short-Term Memory-based neural network with Selected Autoregressive Features (termed a CLSAF model) to improve short-term household electricity load forecasting accuracy by employing three strategies: autoregressive features selection, exogenous features selection, and a “default” state to avoid overfitting at times of high load volatility. We include aggregations of apartments to floor and building level, because utilities may favor transactive approaches that rely on aggregator models, e.g., a cluster of consumers as opposed to an individual. We demonstrate that the CLSAF model, by virtue of its enhanced feature representation and modest computational resources, can accomplish load forecasting in a multi-family residential building across three spatial granularities (individual apartment/household, floor, and building levels), with an accuracy improvement of up to 25% compared to a persistence model. We propose a data screening technique to characterize time-series electricity-load data. This technique is suitable for integration into a TEN ecosystem and allows one to estimate confidence levels of the load forecasts to optimize computational resources and the risks associated with uncertain forecasts.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Multiscale simulation of integrated energy system and electricity market interactions

Accelerating the deep decarbonization of the world's electric grids requires the coordination of complex energy systems and infrastructures across timescales from seconds to decades. Here, we present a new multiscale simulation framework that integrates process- and grid-centric modeling paradigms to better design, operate, and control integrated energy systems (IESs), which combine multiple technologies, in wholesale energy markets. Traditionally, IESs are analyzed with a process-centric paradigm such as levelized cost of electricity (LCOE) or annualized net revenue, ignoring important interactions with electricity markets. This framework explicitly models the complex interactions between an IES's bidding, scheduling, and control decisions and the energy market's clearing and settlement processes, while incorporating operational uncertainties. Through two case studies, we show the importance of understanding and quantifying complex resource-grid interactions. In case study 1, we demonstrate that optimized bidding from one resource shifts the profit distribution for all energy systems in the market. This result suggests new and more flexible IES technologies can disrupt the economics of all market participants, possibly leading to accelerated retirements of less flexible resources. Interestingly, the optimized bidding has little impact on grid-level aggregate statistics, such as total generation costs and renewable penetration rate. While aggregate modeling strategies may remain valid under some IES adoption scenarios for analysis focused on regional outcomes, direct comparisons of IES technologies at specific locations without considering these interactions may lead to misleading or incorrect conclusions. In case study 2, we consider the design and flexible operation of IESs that hybridize conventional generators with energy storage. Through a sensitivity analysis, we find that as the size of the storage system increases, the total number of start-ups for coal- and natural gas-based IESs reduced by 25% and 33.6%, and the total thermal generator ramping (i.e., mileage) reduced by 86.5% and 62.5%, respectively. This shows the primary benefit of storage may not be reduced operational costs (which do not change significantly) but fewer start-ups and less ramping, which may greatly simplify the design, operation, and control of carbon capture systems. The new modeling and optimization capabilities from this work enable the coupling of rigorous, dynamic process models with grid-level production cost models to quantitatively identify the nuanced interdependencies across these vast timescales that must be addressed to realize clean, safe, and secure energy production. Moreover, the proposed general multiscale simulation framework is applicable to all IES technologies and can be easily extended to consider other energy carriers (e.g., hydrogen, ammonia) and energy infrastructures (e.g., natural gas pipelines).

24 POWER TRANSMISSION AND DISTRIBUTION↗