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DOE OSTI2022

Strain Engineering: A Pathway for Tunable Functionalities of Perovskite Metal Oxide Films

Perovskite offers a framework that boasts various functionalities and physical properties of interest such as ferroelectricity, magnetic orderings, multiferroicity, superconductivity, semiconductor, and optoelectronic properties owing to their rich compositional diversity. These properties are also uniquely tied to their crystal distortion which is directly affected by lattice strain. Therefore, many important properties of perovskite can be further tuned through strain engineering which can be accomplished by chemical doping or simply element substitution, interface engineering in epitaxial thin films, and special architectures such as nanocomposites. In this review, we focus on and highlight the structure–property relationships of perovskite metal oxide films and elucidate the principles to manipulate the functionalities through different modalities of strain engineering approaches.

36 MATERIALS SCIENCE↗

DOE OSTI2020

What fuel properties enable higher thermal efficiency in spark-ignited engines?

The Co-Optimization of Fuels and Engines (Co-Optima) initiative from the US Department of Energy aims to co-develop fuels and engines in an effort to maximize energy efficiency and the utilization of renewable fuels. Many of these renewable fuel options have fuel chemistries that are different from those of petroleum-derived fuels. Because practical market fuels need to meet specific fuel-property requirements, a chemistry-agnostic approach to assessing the potential benefits of candidate fuels was developed using the Central Fuel Property Hypothesis (CFPH). The CFPH states that fuel properties are predictive of the performance of the fuel, regardless of the fuel's chemical composition. In order to use this hypothesis to assess the potential of fuel candidates to increase efficiency in spark-ignition (SI) engines, the individual contributions towards efficiency potential in an optimized engine must be quantified in a way that allows the individual fuel properties to be traded off for one another. This review article begins by providing an overview of the historical linkages between fuel properties and engine efficiency, including the two dominant pathways currently being used by vehicle manufacturers to reduce fuel consumption. Then, a thermodynamic-based assessment to quantify how six individual fuel properties can affect efficiency in SI engines is performed: research octane number, octane sensitivity, latent heat of vaporization, laminar flame speed, particulate matter index, and catalyst light-off temperature. The relative effects of each of these fuel properties is combined into a unified merit function that is capable of assessing the fuel property-based efficiency potential of fuels with conventional and unconventional compositions.

42 ENGINEERING↗

DOE OSTI2025

Circadian clock control of ribosome composition promotes rhythmic translation and termination fidelity

Ribosome composition is dynamic, shifting with cell state and stress, but whether it varies with circadian time is unknown. Here, we uncover circadian clock-driven changes in ribosome composition in Neurospora crassa . Mass spectrometry of ribosomes across circadian time identified six ribosomal proteins and one associated factor under clock control. Rhythms in eL31 abundance were validated in purified ribosomes, and deletion of el31 disrupted translation rhythms in nearly half of rhythmically translated mRNAs. N. crassa eL31 promotes circadian control of translation termination and impacts elongation fidelity while maintaining Mg homeostasis, a key determinant of translational accuracy. These findings reveal that the circadian clock reprograms ribosome composition to orchestrate rhythmic translation and fidelity, temporally expanding the proteome beyond the static genome to align cellular function with time of day.

circadian clock↗

DOE OSTI2022

System and method for monitoring a reactor system using optical fiber based sensors

A method of monitoring operation of a reactor system includes causing a chemical reaction to occur within an assembly of the reactor system, and measuring a chemical composition of one or more reactants of the chemical reaction with spatial resolution at a plurality of points along a path within the assembly using a sensor system structured to implement distributed sensing. The sensor system includes an optical fiber sensing member provided at least partially within the assembly, wherein the optical fiber sensing member comprises a functionalized optical fiber based sensor device structured to exhibit a change in one or more optical properties in response to changes in the chemical composition of the one or more reactants.

Chen, Peng K.↗

DOE OSTI2023

Graphene oxide exposure alters gut microbial community composition and metabolism in an in vitro human model

Graphene oxide (GO) nanomaterials have unique physicochemical properties that make them highly promising for biomedical, environmental, and agricultural applications. Despite the increasing interest and the use of GO, assessments of its nanotoxicity have largely not interrogated its potential impact on the gut microbiome. This study addresses an important knowledge gap by investigating the impact of GO exposure- both at low (25 ppm) and high (250ppm) doses and fed (nutrient rich) and fasted (nutrient deplete) conditions- on the gut microbial community structure and function, using an in vitro human colon bioreactor model. 16S rRNA amplicon sequencing revealed that GO exposure resulted in a restructuring of community composition. 25 ppm GO induced a marked decrease in the Bacteroidota phylum and increased the ratio of Firmicutes to Bacteroidota (F/B). Untargeted metabolomics on the supernatants indicated that 25 ppm GO impaired microbial utilization and metabolism of substrates (amino acids, carbohydrate metabolites) and reduced production of beneficial microbial metabolites such as 5-hydroxyindole-3-acetic acid and GABA. Exposure to 250 ppm GO resulted in community composition and metabolome profiles that were very similar to the controls that lacked both GO and digestive enzymes, suggesting that high concentrations of GO may interact with digestive enzymes to form protein coronas, causing their depletion in the gut environment. Differential abundance analyses revealed that 3 genera from the phylum Bacteroidota (Bacteroides, Dysgonomonas, and Parabacteroides) were more abundant after 250 ppm GO exposure, irrespective of feed state. Integrative correlation network analysis indicated that the phylum Bacteroidota showed strong positive correlations to multiple microbial metabolites including GABA and 3-indoleacetic acid, are much larger number of correlations compared to other phyla. These results show that GO exposure has a significant impact on gut microbial community composition and metabolism and different mechanisms are at play for low and high GO concentrations.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Tough and circular glass fiber composites via a tailored dynamic boronic ester interface

Glass fiber reinforced polymer (GFRP) composites are valued for their strength and cost-effectiveness. However, traditional GFRPs often face challenges for end-of-life recycling due to their non-depolymerizable thermoset matrices, and long-term performance due to inadequate interfacial adhesion, which can lead to fiber–matrix delamination. Here, in this work, we have designed dynamic fiber–matrix interfaces to allow tough and closed-loop recyclable GFRPs by utilizing a vitrimer, derived from upcycled polystyrene-b-poly(ethylene-co-butylene)-b-polystyrene (SEBS) with boronic ester (S-Bpin) and amine-based diol crosslinker. The boronic ester groups in S-Bpin form dynamic covalent bonds with the naturally present hydroxyl groups on the unsized GF surface, which eliminates the need for fiber sizing and enables facile closed-loop recyclability of both the fibers and the vitrimer matrix. The resulting strong fiber–matrix interface, depicted by the Raman mapping, leads to a 552% increase in-plane shear toughness (6.2 ± 0.3 MJ m -3 ) and 27% ultimate tensile strength (361 ± 89.2 MPa) compared to those of the conventional epoxy-based matrix (0.95 ± 0.05 MJ m -3 and 264 ± 59.7 MPa, respectively). The network rearrangement through dynamic boronic ester exchange enables fast thermoformability and repairability of micro-cracks at elevated temperatures. Additionally, both the matrix and composite demonstrate strong adhesion to various surfaces including steel and glasses exhibiting ≥6 MPa lap shear strength, which expands their suitability for diverse industrial applications. The readily created dynamic interface between boronic ester functionalized vitrimer and neat GFs presents a promising strategy for developing closed-loop recyclable, multifunctional structural materials, offering a sustainable alternative to non-recyclable thermoset GFRPs and contributes to a circular economy in composite materials.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Synergistic Integration of Chemo-Resistive and SERS Sensing for Label-Free Multiplex Gas Detection

Practical sensing applications such as real-time safety alerts and clinical diagnoses require sensor devices to differentiate between various target molecules with high sensitivity and selectivity, yet conventional devices such as oxide-based chemo-resistive sensors and metal-based surface-enhanced Raman spectroscopy (SERS) sensors usually do not satisfy such requirements. In this report a label-free, chemo-resistive/SERS multimodal sensor based on a systematically assembled 3D cross-point multifunctional nanoarchitecture (3D-CMA), which has unusually strong enhancements in both “chemo-resistive” and “SERS” sensing characteristics is introduced. 3D-CMA combines several sensing mechanisms and sensing elements via 3D integration of semiconducting SnO 2 nanowire frameworks and dual-functioning Au metallic nanoparticles. It is shown that the multimodal sensor can successfully estimate mixed-gas compositions selectively and quantitatively at the sub-100 ppm level, even for mixtures of gaseous aromatic compounds (nitrobenzene and toluene) with very similar molecular structures. This is enabled by combined chemo-resistive and SERS multimodal sensing providing complementary information.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Shifting Defect Self-Regulation via Disordered Vacancies in Hollow Tin Perovskites

Tin(II)-based hybrid halide perovskites typically suffer from severe self-doping behavior as a result of facile oxidation of Sn(II) to Sn(IV), leading to high carrier densities (holes) and metallic-like conductivities that limit their applications. In this contribution, we describe how substituting the large ethylenediammonium cation for methylammonium in the intentionally defective “hollow” perovskite family, MA 1−x en x Sn 1−0.7x I 3−0.4x (MA = methylammonium, en = ethylenediammonium), where 0 ≤ x ≤ 0.38, effectively minimizes the intrinsic self-doping behavior. The use of a solvent-free, mechanochemical synthesis route further circumvents oxidative side reactions typical in solution processing, enabling more precise control and understanding of both composition and defect chemistry. Dark and time-resolved microwave conductivity measurements of these materials as a function of “x” reveal two regimes of conductivity suppression: at low x incorporation (x ≤ 0.15), the carrier density decreases by an order of magnitude via defect-mediated charge compensation, while higher substitution (0.15 < x ≤ 0.38) greatly reduces the carrier mobility. At these lower substitution levels, the observations suggest that intrinsic equilibrium tin vacancies are compensated instead by ionic defects in lieu of mobile holes. For the higher substitution levels, the less mobile carriers exhibit long recombination lifetimes, consistent with polaron-mediated transport. These findings establish a strategy for relatively low iodine chemical potential synthesis and defect-driven control of the carrier concentration in tin halide perovskites, advancing the rational discovery of dopable hybrid semiconductors.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Product Characteristics and Synergy Study on Supercritical Methanol Liquefaction of Lignocellulosic Biomass and Plastic

Bio-oil originating from lignocellulosic biomass (LCB) is a potential next-generation fuel because of its abundant, renewable, and sustainable resources compared to other types. However, these bio-oils are typically of low quality compared to petroleum-derived oils due to their low calorific value, high acidity, and oxygen content. This work intends to provide a feasible method for producing hydrocarbon-rich oils by supercritical methanol (scMeOH) coliquefaction of LCB and plastic waste. Both rice straw (RS) and linear low-density polyethylene (LLDPE) are coliquefied under 300 °C for 60 min in scMeOH at various RS/LLDPE mass ratios of 2:1, 1:1, and 1:2. Positive effects were found in terms of oil yield and fuel quality, such as higher hydrocarbons content and calorific value. The oil yield increased from 26.72 to 30.07 wt % with LLDPE addition of 67%. Around 79.15–92.24% of the oil was hydrocarbons, phenols, ketones, and diverse functional group compounds. The complex compounds led to various degrees of the synergetic effect on oil chemical compositions. Among various RS/LLDPE ratios in this work, RS/LLDPE of 1:2 was supposed to be an optimal ratio for hydrocarbon-rich fuel production because it presented the highest oil yield of 30.07 wt % and quality-high oil with 71.42% hydrocarbons. In addition, scMeOH coliquefaction of LCB and plastic waste shows a synergetic effect on the improvement of carbon and hydrogen contents in solid products. These results indicate that scMeOH coliquefaction of LCB with plastic is a feasible and promising means to improve fuel quality and also to realize the thermal recycling of plastic wastes.

09 BIOMASS FUELS↗

DOE OSTI2021

Distribution of Bound and Free Water in Anatomical Fractions of Pine Residues and Corn Stover as a Function of Biological Degradation

Biomass quality is influenced by water’s abundance, distribution, and status in relation to other chemical species within the polymer matrix. Water interacts with polymers that make up the cell walls, and these interactions govern the physical and chemical changes that occur during the storage and preprocessing of biomass feedstocks. Time-domain nuclear magnetic resonance (TD-NMR) was employed to explore variations in the physical constraints of water within the lignocellulosic microstructure in distinct anatomical fractions of biomass and as a function of biological degradation. The Carr–Purcell–Meiboom–Gill sequence, when combined with knowledge of the chemical composition and physical structure of pine residues and corn stover anatomical fractions, gives an accurate measurement of the bound and free water. In this work, the impacts of storage and biological degradation were investigated to elucidate changes in the status and distribution of water within distinct plant tissues. We also investigate how degradation during storage affects water interactions in different pine residues (e.g., bark, branch, and needle) and corn stover (e.g., cob, leaf, and stalk) anatomical fractions using transverse relaxation times (T2). As demonstrated herein, TD-NMR provides quantitative data on lignocellulosic biomass–water interactions within anatomical fractions, which can further aid in the investigation of preprocessing effects on feedstock quality. Our findings suggest that biological heating enhances biomass–water interactions at the cellular and macromolecular scale. In addition, analysis of three-dimensional scanning electron microscopy reconstructions indicates that surface roughness wavelengths align with microscale roughness, suggesting that pine forestry residue and corn stover particles have primarily hydrophobic exterior surfaces. Furthermore, this study offers multiscale insights into understanding the microstructure, wettability, and chemical environment that dictate diffusion, enzyme access, and recalcitrance of lignocellulosic biomass.

09 BIOMASS FUELS↗

DOE OSTI2024

A Straightforward Model for Quantifying Local pH Gradients Governing the Oxygen Evolution Reaction

The production and consumption of protons by an electrocatalyst will, under certain conditions, generate localized microenvironments with properties distinct from those of the bulk solution. These local properties are particularly impactful for reactions involving proton-coupled electron transfer, where the generation of locally basic or acidic environments may significantly influence the energy efficiency and reaction selectivity of the electrocatalyst. Whereas local pH environments have been observed and characterized in reductive half-reactions, including the CO 2 reduction and hydrogen evolution reactions, the incompatibility of conventional techniques and materials has limited studies in oxidative half-reactions, including the oxygen evolution reaction (OER), which provides the reducing equivalents for solar-to-fuels electrolysis. With the straightforward parameters bulk pH, buffer composition and pK a , and mass transport, we develop a model for describing local pH as a function of current density regardless of the microscopic details of the mechanism. Using an acid-stable PbO x OER catalyst, we observe the formation and dissipation of pH gradients during the OER and validate the model with voltammetric and potentiometric studies. Here, the model predicts how local acidic environments can develop over a narrow OER current density window, thus providing further motivation for the development of OER catalysts that are stable to acid, even when operating in basic aqueous conditions. More generally, the model is not restricted to the OER and is useful for determining the onset of local pH gradients for other electrocatalytic reactions that involve the consumption or generation of protons in energy conversion reactions.

Anions↗

DOE OSTI2021

Experimental Constraints on Solid Nitride Phases in Rocky Mantles of Reduced Planets and Implications for Observable Atmosphere Compositions

Abstract Astronomical surveys have discovered thousands of transiting exoplanets, revealing that rocky planets are common in the galaxy. A planet's interior chemistry is frequently inferred by average density, described by mass‐radius (M‐R) relationships. However, M‐R relationships give rise to non‐unique interpretations of a planet's interior composition, an issue that limits our ability to characterize far‐away worlds. We present experimental and density functional theoretical results addressing the influence of an ultra‐reducing (oxygen‐poor) interior chemistry on rocky mantle phases and discuss the possible implications for atmospheric observables. We show that silicon carbide (SiC) and molecular nitrogen (N 2 ) react to form solid silicon nitride (γ‐Si 3 N 4 ) at high pressures and high temperatures in a laser‐heated diamond‐anvil cell, consistent with ab initio computations. Si 3 N 4 remains stable under extreme conditions and when quenched to ambient conditions. As SiC is a common compound found under very reducing conditions, these results indicate that nitrogen may form solid phases in an oxygen‐poor rocky planet. If, by sequestering nitrogen in a planet's mantle, the distribution of nitrogen between a planet's interior and atmosphere is altered (i.e., a nitrogen‐rich mantle and nitrogen‐poor atmosphere), these results indicate that there may be atmospheric observables connected to the mantle‐redox state of a rocky planet besides the oxygen‐containing phases ubiquitous in exoplanet literature.

Daviau, Kierstin↗

DOE OSTI2020

Linking electronic structure calculations to generalized stacking fault energies in multicomponent alloys

Abstract The generalized stacking fault energy is a key ingredient to mesoscale models of dislocations. Here we develop an approach to quantify the dependence of generalized stacking fault energies on the degree of chemical disorder in multicomponent alloys. We introduce the notion of a “configurationally-resolved planar fault” (CRPF) energy and extend the cluster expansion method from alloy theory to express the CRPF as a function of chemical occupation variables of sites surrounding the fault. We apply the approach to explore the composition and temperature dependence of the unstable stacking fault energy (USF) in binary Mo–Nb alloys. First-principles calculations are used to parameterize a formation energy and CRPF cluster expansion. Monte Carlo simulations show that the distribution of USF energies is significantly affected by chemical composition and temperature. The formalism is broadly applicable to arbitrary crystal structures and alloy chemistries and will enable the development of rigorous models for deformation mechanisms in high-entropy alloys.

Natarajan, Anirudh Raju (ORCID:0000000202529480)↗

DOE OSTI2024

Towards atom-level understanding of metal oxide catalysts for the oxygen evolution reaction with machine learning

Abstract Green hydrogen production is crucial for a sustainable future, but current catalysts for the oxygen evolution reaction (OER) suffer from slow kinetics, despite many efforts to produce optimal designs, particularly through the calculation of descriptors for activity. In this study, we develop a dataset of density functional theory calculations of bulk and surface perovskite oxides, and adsorption energies of OER intermediates, which includes compositions up to quaternary and facets up to (555). We demonstrate that per-site properties of perovskite oxides such as Bader charge or band center can be tuned through element substitution and faceting, and develop a machine learning model that accurately predicts these properties directly from the local chemical environment. We leverage these per-site properties to identify promising perovskites with high theoretical OER activity. The identified design principles and promising materials provide a roadmap for closing the gap between current artificial catalysts and biological enzymes such as photosystem II.

Chemistry↗

DOE OSTI2024

Asymmetric oligomerization state and sequence patterning can tune multiphase condensate miscibility

Endogenous biomolecular condensates, composed of a multitude of proteins and RNAs, can organize into multiphasic structures with compositionally distinct phases. This multiphasic organization is generally understood to be critical for facilitating their proper biological function. However, the biophysical principles driving multiphase formation are not completely understood. Here we use in vivo condensate reconstitution experiments and coarse-grained molecular simulations to investigate how oligomerization and sequence interactions modulate multiphase organization in biomolecular condensates. We demonstrate that increasing the oligomerization state of an intrinsically disordered protein results in enhanced immiscibility and multiphase formation. Interestingly, we find that oligomerization tunes the miscibility of intrinsically disordered proteins in an asymmetric manner, with the effect being more pronounced when the intrinsically disordered protein, exhibiting stronger homotypic interactions, is oligomerized. Our findings suggest that oligomerization is a flexible biophysical mechanism that cells can exploit to tune the internal organization of biomolecular condensates and their associated biological functions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Understanding KOtBu in atomic layer deposition – in situ mechanistic studies of the KNbO3 growth process

Functional coatings based on alkali metals have become increasingly attractive in the current shift towards sustainable technologies. While lithium-based compounds have a natural impact on batteries, other alkali metal compounds are important as replacements for toxic materials in a range of electronic devices. This is especially true for potassium, being a major component in e.g. K x Na 1-x NbO 3 (KNN) and KTa x Nb 1-x O 3 (KTN), with hope to replace Pb(Zr x Ti 1-x )O 3 (PZT) in piezo-/ferroelectric and electrooptic devices. ALD facilitates functional conformal coatings at deposition temperatures far below what is reported using other techniques and with excellent compositional control. The ALD growth of potassium-containing films using KO t Bu has, however, been unpredictable. Untraditional response to the pulse composition and precursor dose, severe reproducibility issues, and very high growth per cycle are some of the puzzling features of these processes. In this article, we shed light on the growth behavior of KO t Bu in ALD by in situ quartz crystal microbalance and Fourier transform infrared spectroscopy studies. We study the precursor's behavior in the technologically interesting KNbO 3 -process, showing how the potassium precursor strongly affects the growth of other cation precursors. We show that the strong hygroscopic nature of the intermediary potassium species has far-reaching implications throughout the growth. This helps not only to enhance the understanding of alkali metal containing compounds’ growth in ALD, but also to provide the means to control the growth of novel sustainable technological materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Using the optimal combined index weight ratio to improve the probability of anomaly detection in big area additive manufacturing

Big Area Additive Manufacturing (BAAM) of composites requires significant time, energy, and material, so it is critical to reduce production inefficiencies to make functional parts without multiple iterations. Statistical process control coupled with Principal Component Analysis (PCA) is a powerful technique that provides a quick, computationally inexpensive, and intuitive way for operators to detect defects that form in a manufacturing process without massive datasets. Recently, a combined index that is a weighted sum of the Hotelling's T 2 and squared residual error statistics has been proposed that can be monitored in one chart, improving interpretation accuracy and simplicity. However, the literature does not offer a formal method to optimise the weights. Here, we introduce two new approaches to the traditional weight selection approach using simulated and BAAM image data. Approach 1 uses a theoretically motivated optimum inspired by probabilistic principal component analysis. Approach 2 systematically varies the ratio of the weights to find the optimum. We show that approach 1 delivers optimal anomaly detection performance in select cases while approach 2 fares better in practice. Surprisingly, we also show that choosing a more complex PCA model has a minimal negative impact on anomaly detection performance compared to a more simplistic model.

3-dimensional printing↗

DOE OSTI2020

Effective pair potential for random fcc CoCrFeMnNi alloys

The single-phase equiatomic CoCrFeMnNi alloy is a random solid solution of five elements on the face-centered cubic lattice, whose pure constituents crystallize in very different structures and exhibit diverse magnetic properties. Due to the randomness of the alloy, 80% of nearest neighbor bonds are between unlike elements and thus the details of bonding in pure structures are less important. The elastic moduli of this alloy give rise to small Cauchy pressure C 12 - C 44 , which suggests that the dominant part of bonding may be described by a simple pair potential. We test this hypothesis by developing a long-range Lennard-Jones potential in which the equilibrium crystal structures of pure constituents are taken as reference. The standard mixing rules for regular solutions are then adopted to obtain parameters for bonds between unlike elements in the quinary system. The transferability of this potential to quaternary CoCrFeNi, ternary CoCrNi, and binary FeNi alloys is investigated and the predictions compared with experiments and density functional theory calculations. By sampling over a large number of random configurations, we investigate the effect of compositional randomness on misfit volumes, energies of point defects and stacking faults, and the dislocation friction stresses experienced by moving edge and screw dislocations.

Materials Science↗