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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS2008

Integrated Performance of Next Generation High Data Rate Receiver and AR4JA LDPC Codec for Space Communications

Low-density parity-check (LDPC) codes are the state-of-the-art in forward error correction (FEC) technology that exhibits capacity approaching performance. The Jet Propulsion Laboratory (JPL) has designed a family of LDPC codes that are similar in structure and therefore, leads to a single decoder implementation. The Accumulate-Repeat-by-4-Jagged- Accumulate (AR4JA) code design offers a family of codes with rates 1/2, 2/3, 4/5 and lengths 1024, 4096, 16384 information bits. Performance is less than one dB from capacity for all combinations.Integrating a stand-alone LDPC decoder with a commercial-off-the-shelf (COTS) receiver faces additional challenges than building a single receiver-decoder unit from scratch. In this work, we outline the issues and show that these additional challenges can be over-come by simple solutions. To demonstrate that an LDPC decoder can be made to work seamlessly with a COTS receiver, we interface an AR4JA LDPC decoder developed on a field-programmable gate array (FPGA) with a modern high data rate receiver and mea- sure the combined receiver-decoder performance. Through optimizations that include an improved frame synchronizer and different soft-symbol scaling algorithms, we show that a combined implementation loss of less than one dB is possible and therefore, most of the coding gain evidence in theory can also be obtained in practice. Our techniques can benefit any modem that utilizes an advanced FEC code.

Cheng, Michael K.↗
DOE OSTI2022

Long-term compost amendment modulates wheat genotype differences in belowground carbon allocation, microbial rhizosphere recruitment and nitrogen acquisition

The implementation of soil health-promoting practices, such as cover cropping and compost application, has important implications for nutrient cycling and management in agroecosystems. At the same time, plant belowground carbon (C) allocation patterns can influence nutrient cycling and availability in soil through changes to the microbial community, but the effects may depend on the crop genotype and management practices in place. We evaluated belowground C allocation patterns using 13 C labeling and root architecture in two genotypes of winter wheat (Triticum aestivum) with different levels of exudation and belowground allocation strategies in soils with contrasting compost amendment legacy (108.7 Mg ha -1 every 2 years over 10 years vs. no compost). We also measured microbial community structure and function in the rhizosphere and quantified uptake of residue-derived N from 15 N-labelled cover crop residues. We found an interactive effect between soil management and genotype, where in the no-compost soil, the high-exudation genotype (Snowmass) increased exudation by over 4-fold, while the low-exudate genotype (Byrd) increased only 2-fold. While we did not observe genotype differences in rhizosphere enzyme activity or dissolved N pools, residue N uptake was 1.8 times greater for Snowmass in the compost-amended soil. There were more rhizosphere microbial taxa associated with the high-exudate genotype (Snowmass); nine bacterial and seven fungal families were indicative of Snowmass, versus one bacterial and four fungal families for Byrd. Our results suggest that the high-exudation strategy can influence the rhizosphere microbial community, and lead to greater short-term residue N uptake in high SOM soil. By directly linking root architecture, exudation, microbial communities, and N mineralization and uptake dynamics, this work demonstrates that plasticity in root C allocation is genotype-specific and influences microbial communities and nutrient cycling depending on the soil health context.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Field Study of 120-volt Heat Pump Water Heaters in the Big Easy

To meet long-term goals for reducing carbon emissions and lessen the impacts of climate change, the U.S. plans to decarbonize its building stock, which includes the replacement of fossil fuel-burning end uses with energy efficient electric alternatives. As part of this strategy, the replacement of fossil fuel water heaters with heat pump water heaters (HPWH) has the potential to avoid substantial carbon emissions. An estimated 10-15 million single-family homes with fossil fuel water heaters do not have the electrical panel capacity to install a 240-volt, 30-amp HPWH. For these homes, a technology recently introduced to the market, the 120-volt plug-in HPWH, can provide energy efficient electrification of water heating without an expensive panel and wiring retrofit. This paper presents the results of an ongoing 120-volt HPWH field study conducted in 17 homes in New Orleans, LA. Key installation scenarios are profiled for retrofitting from gas-fired water heaters to 120-volt HPWHs, accounting for space, air volume, air temperature, condensate drainage, and electrical. Each HPWH had its surrounding air temperature, relative humidity, inlet and outlet water temperature, flow, and energy consumption monitored. Using these data, hot water delivery and energy efficiency performance were analyzed based on home characteristics. Hot water run outs were investigated to understand how hot water usage, inlet water temperature, and surrounding air temperature impact the HPWH’s ability to meet load. From these results, best practices for 120-volt HPWH siting, sizing, and installation were developed. In addition, results are explored further to add insight for electrification policies and product development.

heat pump water heater, 120-volt, Residential buil↗
DOE OSTI2025

Mechanically and electrically tunable Rashba-Edelstein effect in ferroelectric semiconductors, CsGe⁢𝑋 3 (𝑋 = I, Br, Cl)

The ability of materials to convert charge current into spin current is fundamental to many spintronics applications. One means of realizing this conversion is via Rashba-Edelstein effect (REE). Using density functional theory simulations, we predict that REE can be induced in the recently discovered family of semiconducting ferroelectrics, CsGe⁢𝑋 3 (𝑋 = I, Br, Cl). The effect is quantified through Rashba-Edelstein coefficients, 𝜒 𝑥⁢𝑦 =−𝜒 𝑦⁢𝑥 , which are nonzero in valence and conduction bands. The largest values, obtained for CsGeI 3 , are 3.45 × 10 10 $\frac{ℏ}{Λ cm}$ and 0.97 × 10 10 $\frac{ℏ}{Λ cm}$ in the conduction and valence bands, respectively. The values are comparable to, and sometimes exceed, those of other inorganic materials, although the maximal values occur away from the band edges. The coefficients' sign couples to the direction of spontaneous polarization, offering opportunities for nonvolatile spin current manipulation via external electric field. Furthermore, these coefficients are highly tunable through strain engineering owing to strain-induced variations in spin textures and energy isosurfaces. Specifically, 𝜒 in the valence band of CsGeI 3 is enhanced to 3.61 × 10 10 $\frac{ℏ}{Λ cm}$ under 5% biaxial strain. Given this potential, we synthesized CsGeI 3 to validate our simulation structure and found excellent agreement between experiment and simulation, thereby allowing extrapolation of our findings to practically significant temperatures. Furthermore, our study identifies promising materials for nonvolatile, multifunctional spintronic applications.

Electronic structure↗
DOE OSTI2020

Crystallography of Reactive Intermediates

Metal–ligand (M–L) multiply bonded complexes hold a central place in inorganic chemistry and catalysis: From fundamental and historical perspectives, these species have played a critical role in the articulation of important bonding principles (i.e. the vanadyl ion in the development of molecular orbital theory); from a practical perspective, these species are critical intermediates in a variety of chemical reactions (i.e. N 2 and O 2 reduction, H 2 O oxidation, and C–H functionalization). For many high-valent, early metal complexes, overlap of ligand-based electrons with vacant π-symmetry orbitals leads to strong M–L multiple bonds. The stability of these species enables straightforward characterization with a suite of standard spectroscopic and diffraction-based experiments. Mid- and late-transition metal complexes, with attendant higher d-electron counts, often support more reactive M–L multiply bonded fragments. The reactivity of these species simultaneously renders them attractive intermediates for catalysis but challenging synthetic targets to observe and characterize. A number of important strategies have been advanced to enable experimental characterization of mid- to late-metal–ligand multiply bonded species. Synthetic manipulation of the coordination geometry and ligand donicity, as well as introduction of sterically encumbering ligands, have each emerged as powerful methods to tame the inherent reactivity of kinetically labile M–L multiple bonds. While these efforts have resulted in families of well-characterized complexes and provided critical insights regarding structure and bonding, the synthetic derivatization required to stabilize M–L fragments of interest often obviates the substrate functionalization activity relevant to catalysis. Photochemical synthesis of reactive species provides a conceptually attractive strategy to generate reactive M–L fragments under conditions compatible with time-resolved or cryogenic steady-state characterization, and photogeneration has enabled observation of a number of reactive M–L fragments. The suite of tools available to characterize photogenerated reactive species is often more limited than typical for kinetically stabilized complexes and structural characterization is typically not possible. Recently, photocrystallographic experiments, in which reactive M–L multiply bonded intermediates are generated within single-crystal matrices, have been advanced as a strategy to interrogate the structures of reactive intermediates in C–H functionalization. Lastly, this Comment describes the historical antecedents to these experiments, highlights examples of photocrystallographic characterization of reactive intermediates, and discusses future opportunities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

From Cation Order to Disorder: Unlocking Ion Transport Pathways in Li–Zn–Zr–Cl Halospinels

Lithium metal chloride halospinels of the general formula Li 2 MCl 4 are a promising class of earth-abundant ion conductors for all-solid-state batteries. However, poor roomtemperature ionic conductivity has historically limited their use in practical applications. Here, we substitute Zr 4+ into Li 2 ZnCl 4 along the series Li 2−2x/3 Zn 1−x Zr 2x/3 Cl 4 (x = 0, 0.1, 0.3, 0.4, 0.6, 0.9, and 1.0) to understand how cation disorder and vacancy tuning impact ion transport in “normal” halospinels. Aliovalent Zr 4+ substitution increases ionic conductivity by nearly 5 orders of magnitude, from 1.320(3) × 10 −9 S cm −1 in Li 2 ZnCl 4 to 6.74(1)× 10 −5 S cm −1 for x = 0.6. Average and local structure characterization through synchrotron X-ray diffraction (SXRD) and neutron pair distribution function (nPDF) analysis reveal that Zr 4+ redistributes the Zn 2+ and Li + sublattices into previously unoccupied interstitial sites, which form new low-energy hopping pathways that facilitate ion transport. We rationalize the dramatic rearrangement of the cation local structure by considering the coordination preferences of the cations and the potential electrostatic penalties incurred by the higher-valent Zr 4+ cations. This work delivers an atomistic understanding of substitution-induced cation disorder and ion transport properties in a new family of earth-abundant halospinels.

Cardoza, Abby M. [Colorado School of Mines, Golden↗
DOE OSTI2025

Phonon Olympics: Phonon property and lattice thermal conductivity benchmarking from open-source packages

Three widely used open-source packages for determining phonon properties and lattice thermal conductivities (ALAMODE, phono3py, and ShengBTE) are benchmarked by teams of expert users and the package developers. The phonons for Ge, RbBr, monolayer MoSe 2 , and AlN are modeled at zero temperature, and they scatter through three-phonon and phonon-isotope processes, with thermal conductivities obtained from the linearized Peierls–Boltzmann transport equation with input from density functional theory calculations. Over a wide range of temperatures, the thermal conductivities calculated by the teams fall within at most ±15% of their mean values for each of the four materials. The phonon frequencies, obtained from the harmonic force constants, do not show large differences between the calculations, indicating that the modal heat capacities and group velocities are not responsible for the thermal conductivity variations. It is the lifetimes associated with three-phonon scattering, obtained from the cubic force constants, that drive the variations. The many decisions required to calculate the cubic force constants (e.g., supercell size, atomic displacement, neighbor cutoff, and application of symmetries) make identification of the precise origin of the thermal conductivity variations challenging. The calculated thermal conductivities do not generally show agreement with experimental measurements, which is attributed to the limitations of the density functional theory calculations. Guidance for the development of best practices is provided, which will help to standardize protocols needed for building thermal conductivity databases. The results provide a baseline for future benchmarking of other packages and more advanced calculations.

McGaughey, Alan J. H. [Carnegie Mellon Univ., Pitt↗
DOE OSTI2021

A Machine Learning Approach for the Prediction of Formability and Thermodynamic Stability of Single and Double Perovskite Oxides

Perovskite oxides continue to attract huge interest due to their fascinating and wide-ranging properties for diverse applications. The tunability of these properties may be further enhanced by increasing their compositional complexity via double perovskite-ordered configurations containing multiple cations. In this work, we focus on an exhaustive chemical space of single and double oxide perovskites and optimally explore this space to identify novel compositions that are likely to form stable compounds. Critically, we examine the relationship between formability, the practical ability to synthesize a compound, and stability, the thermodynamic preference to form the structure. Our formability and stability training data sets were enumerated from the available experimental literature and in-house density functional theory computations and contained 1505 and 3469 examples, respectively, representing state-of-the-art in the current open literature in perovskite and double perovskite compounds. Subsequently, cross-validated and highly accurate machine learning classification models are built using these training data sets and employed to screen for novel stable oxide perovskites. The study identifies (1) atomic features relevant to prediction of formability and stability in perovskite and double perovskite compounds, (2) the importance of including energy contributions due to local structural relaxations going beyond the high symmetry perovskite phase, and (3) 437,828 double perovskite compounds that are likely to be stable and 891,188 compounds that are likely to be formable. From the intersection of this large chemical space of formable and stable oxide perovskites, 414 compositions are identified as the most promising candidates for future experimental synthesis of novel oxide perovskites. The developed models may be generalized and have implications beyond perovskite discovery if applied to other families of compounds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Synthesis of Zn2NbN3 ternary nitride semiconductor with wurtzite-derived crystal structure

Binary III-N nitride semiconductors with wurtzite crystal structure such as GaN and AlN have been long used in many practical applications ranging from optoelectronics to telecommunication. The structurally related ZnGeN2 or ZnSnN2 derived from the parent binary compounds by cation mutation (elemental substitution) have recently attracted attention, but such ternary nitride materials are mostly limited to II-IV-N2 compositions. This paper demonstrates synthesis and characterization of zinc niobium nitride (Zn2NbN3) – a previously unreported II2-V-N3 ternary nitride semiconductor. The Zn2NbN3 thin films are synthesized using a one-step adsorption-controlled growth, and a two-step deposition/annealing method that suppresses the loss of Zn and N. Measurements indicate that this sputtered Zn2NbN3 crystalizes in cation-disordered wurtzite-derived structure, in contrast to chemically related rocksalt-derived Mg2NbN3 compound, also synthesized here for comparison using the two-step method. The estimated wurtzite lattice parameter ratio of Zn2NbN3 is 1.55, and the optical absorption onset is at 2.1 eV. Both of these values are lower compared to published Zn2NbN3 computational values of c/a = 1.62 and Eg = 3.5 - 3.6 eV. Additional theoretical calculations indicate that this difference is due to cation disorder in experimental samples, suggesting a way to tune the structural parameters and the resulting properties of heterovalent ternary nitride materials. Overall, this work expands the wurtzite family of nitride semiconductors to include Zn2NbN3, and suggests that related II2-V-N3 and other ternary nitrides should be possible to synthesize.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Realizable hyperuniform and nonhyperuniform particle configurations with targeted spectral functions via effective pair interactions

The capacity to identify realizable many-body configurations associated with targeted functional forms for the pair correlation function $g_2(r)$ or its corresponding structure factor $\textit{S(k)}$ is of great fundamental and practical importance. While there are obvious necessary conditions that a prescribed structure factor at number density ρ must satisfy to be configurationally realizable, sufficient conditions are generally not known due to the infinite degeneracy of configurations with different higher-order correlation functions. A major aim of this paper is to expand our theoretical knowledge of the class of pair correlation functions or structure factors that are realizable by classical disordered ensembles of particle configurations, including exotic “hyperuniform” varieties. We first introduce a theoretical formalism that provides a means to draw classical particle configurations from canonical ensembles with certain pairwise-additive potentials that could correspond to targeted analytical functional forms for the structure factor. This formulation enables us to devise an improved algorithm to construct systematically canonical-ensemble particle configurations with such targeted pair statistics, whenever realizable. As a proof of concept, we test the algorithm by targeting several different structure factors across dimensions that are known to be realizable and one hyperuniform target that is known to be nontrivially unrealizable. Our algorithm succeeds for all realizable targets and appropriately fails for the unrealizable target, demonstrating the accuracy and power of the method to numerically investigate the realizability problem. Subsequently, we also target several families of structure-factor functions that meet the known necessary realizability conditions but are not known to be realizable by disordered hyperuniform point configurations, including $\textit{d}$-dimensional Gaussian structure factors, $\textit{d}$-dimensional generalizations of the two-dimensional one-component plasma (OCP), and the $\textit{d}$-dimensional Fourier duals of the previous OCP cases. Moreover, we also explore unusual nonhyperuniform targets, including “hyposurficial” and “antihyperuniform” examples. In all of these instances, the targeted structure factors are achieved with high accuracy, suggesting that they are indeed realizable by equilibrium configurations with pairwise interactions at positive temperatures. Remarkably, we also show that the structure factor of nonequilibrium perfect glass, specified by two-, three-, and four-body interactions, can also be realized by equilibrium pair interactions at positive temperatures. In this work, our findings lead us to the conjecture that any realizable structure factor corresponding to either a translationally invariant equilibrium or nonequilibrium system can be attained by an equilibrium ensemble involving only effective pair interactions. Our investigation not only broadens our knowledge of analytical functional forms for $g_2(r)$ and $\textit{S(k)}$ associated with disordered point configurations across dimensions but also deepens our understanding of many-body physics. Moreover, our work can be applied to the design of materials with desirable physical properties that can be tuned by their pair statistics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Robust scalable initialization for Bayesian variational inference with multi-modal Laplace approximations

Predictive modeling typically relies on Bayesian model calibration to provide uncertainty quantification. Variational inference utilizing fully independent (“mean-field”) Gaussian distributions are often used as approximate probability density functions. This simplification is attractive since the number of variational parameters grows only linearly with the number of unknown model parameters. However, the resulting diagonal covariance structure and unimodal behavior can be too restrictive to provide useful approximations of intractable Bayesian posteriors that exhibit highly non-Gaussian behavior, including multimodality. High-fidelity surrogate posteriors for these problems can be obtained by considering the family of Gaussian mixtures. Gaussian mixtures are capable of capturing multiple modes and approximating any distribution to an arbitrary degree of accuracy, while maintaining some analytical tractability. Unfortunately, variational inference using Gaussian mixtures with full-covariance structures suffers from a quadratic growth in variational parameters with the number of model parameters. The existence of multiple local minima due to strong nonconvex trends in the loss functions often associated with variational inference present additional complications, These challenges motivate the need for robust initialization procedures to improve the performance and computational scalability of variational inference with mixture models. In this work, we propose a method for constructing an initial Gaussian mixture model approximation that can be used to warm-start the iterative solvers for variational inference. The procedure begins with a global optimization stage in model parameter space. In this step, local gradient-based optimization, globalized through multistart, is used to determine a set of local maxima, which we take to approximate the mixture component centers. Around each mode, a local Gaussian approximation is constructed via the Laplace approximation. Finally, the mixture weights are determined through constrained least squares regression. The robustness and scalability of the proposed methodology is demonstrated through application to an ensemble of synthetic tests using high-dimensional, multimodal probability density functions. Here, the practical aspects of the approach are demonstrated with inversion problems in structural dynamics.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Nanoengineering of 2D MBenes for energy storage applications: A review

2D transition metal borides (MBenes), a flourishing member of the 2D nanomaterial family, show great potential in a number of study areas. MBenes have received increasing attention thanks to their excellent electrical conductivity, structural and mechanical properties, and chemical stability, which have captivated researchers and sparked further exploration. Extensive theoretical and experimental investigations have unveiled its remarkable potential as electrode materials for electrochemical storage applications, making MBenes a subject of great interest. Despite the growing interest and numerous studies conducted, there is a lack of a comprehensive and systematic appraisal of MBenes' applications in electrochemical energy storage systems. Here, in light of this, firstly, we provide an overview of the current progress in the fabrication and characterization of MAB phases and MBenes. For the synthesis of MBenes, the following fabrication techniques were discussed; liquid-phase exfoliation, solid-state mechanical exfoliation, chemical vapor deposition, high-pressure chemical vapor deposition, microwave-assisted chemical etching, and ultrasound-assisted chemical etching methods. Then, we delve into the captivating potential of MBenes, specifically in the realm of energy storage applications and their role in enhancing electrochemical storage capabilities. The discussion encompasses their application in lithium-ion, lithium-sulfur, and lithium-selenide batteries, supercapacitors and other energy storage systems, providing a comprehensive perspective on their contributions to the energy landscape. Finally, a brief but significant summary of the challenges and opportunities of MBenes in practical applications was summarized. The present review provides a guide and scientific motivation for creating and developing advanced MBene-based nanomaterials, addressing the growing demand for cutting-edge energy storage systems.

25 ENERGY STORAGE↗
DOE OSTI2022

A Mountaintop View Requires Minimal Sorting: A Faster Contour Tree Algorithm

Consider a scalar field f : M → R, where M is a triangulated simplicial mesh in R d . A level set, or contour, at value v is a connected component of f –1 (v). As v is changed, these contours change topology, merge into each other, or split. Contour trees are concise representations of f that track this contour behavior. The vertices of these trees are the critical points of f, where the gradient is zero. The edges represent changes in the topology of contours. It is a fundamental data structure in data analysis and visualization, and there is significant previous work (both theoretical and practical) on algorithms for constructing contour trees. Suppose M has n vertices, N facets, and t critical points. A classic result of Carr, Snoeyink, and Axen (2000) gives an algorithm that takes O(n log n+Nα(N)) time (where α(·) is the inverse Ackermann function). A further improvement to O(t log t + N) time was given by Chiang et al. All these algorithms involve a global sort of the critical points, a significant computational bottleneck. Unfortunately, lower bounds of Ω(t log t) also exist. We present the first algorithm that can avoid the global sort and has a refined time complexity that depends on the contour tree structure. Intuitively, if the tree is short and fat, we get significant improvements in running time. For a partition of the contour tree into a set of descending paths, P, our algorithm runs in O($\Sigma$ pϵP |p| log |p| + tα(t) + N). This is at most O(t log D + N), where D is the diameter of the contour tree. Moreover, it is O(tα(t) + N) for balanced trees, a significant improvement over the previous complexity. Our algorithm requires numerous ideas: partitioning the contour tree into join and split trees, a local growing procedure to iteratively build contour trees, and the use of heavy path decompositions for the time complexity analysis. There is a crucial use of a family of binomial heaps to maintain priorities, ensuring that any comparison made is between comparable nodes of the contour tree. We also prove lower bounds showing that the $\Sigma$ pϵP |p| log |p| complexity is inherent to computing contour trees.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Tuning the Solvation and Solubility Properties of Molecularly Heterogeneous Nonionic Deep Eutectic Solvents via Interface Organization

Common separation techniques, such as liquid− liquid extraction, are usually used for extractions and purifications due to their industrial scalability and affordability. However, these well-established practices are hindered by low selectivity and challenges in recovering solutes and solvents. Deep eutectic solvents (DES), a fairly new type of solvent, have the potential to overcome these issues. DESs are binary mixtures whose physical properties can be tuned by selecting the appropriate precursors to facilitate and/or enhance processes such as extraction. A promising DES for selective separations is formed when lauric acid (LA) is mixed with N-methylacetamide (NMA). This LA-NMA DES has a heterogeneous microscopic structure that can solvate compounds with completely different polarities. This study explores how forming an organized structure on the mesoscale affects the solubility of nonpolar solutes in nonionic DESs. To this end, the molecular and mesoscale structures and their effect on the solubility and solvation properties are evaluated for the LA-NMA DES and two new DESs with slight chemical variations in their precursors. It is observed that the organization of the nonpolar DES domains and, consequently, of their interfaces directly relates to the solubility of nonpolar compounds. Specifically, correctly selecting the DES precursors that form organized nonpolar domains leads to an organized interface in which the nonpolar solutes are solvated, thereby increasing the solubility. Additionally, enhanced dissolution power was observed in a completely different DES with mesoscale order in its molecular structure and composed of menthol and lauric acid. The latter result further validates the proposed tunability of the DES dissolution power through organized interfaces, extending it beyond a specific DES family and opening the possibility of new extraction-tailored designer solvents.

Extraction↗
DOE OSTI2021

Mica filled polyetherketoneketones for material extrusion 3D printing

Polyetherketoneketone (PEKK) has superior physical properties to most available thermoplastics compatible with material extrusion-based 3D printing, including analogs in the polyaryletherketone (PAEK) family. To date, the performance of fused filament fabrication (FFF) compatible PEKK has been detailed primarily as a function of varying the isomer ratios composing the co-polymer structure. The strategy to form blends or composites with PEKK for FFF is attractive for further tailoring of performance in application, yet has received limited attention. Here, we report the integration of three grades of mica platelets into PEKK at 10% and 30% mass loadings to generate an array of filament feedstocks that were then used to print objects with a simple FFF machine. The effects of mica coating chemistry and surface treatment on the compatibility with PEKK and resulting properties are described. Mica fillers at both loadings have only subtle influence on the FFF relevant melt rheological properties inherent to PEKK. Pigment micas at high loadings can lower the melting temperature of PEKK (up to 19 ºC) without shifting its glass transition temperature and inhibit much of the undesirable crystallization occurring during processing with unfilled PEKK. The printed composites were effectively cold crystallized post-printing, affording crystalline fractions up to 90% relative to unfilled PEKK with increased dimensional stabilities. All micas, when used as fillers in low and high relative PEKK crystallinities, significantly increased the tensile modulus (as high as 126% or to 7.31 GPa) of parts in correlation to the loading. Furthermore, the underlying microstructural features of a printed composite were compared to unfilled PEKK by use of a high-resolution helical micro-computed tomography instrument. Practically, pigment micas can confer a wide range of rich colors to 3D-printed PEKK.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Serendipita Fungi Modulate the Switchgrass Root Transcriptome to Circumvent Host Defenses and Establish a Symbiotic Relationship

The fungal family Serendipitaceae encompasses root-associated lineages with endophytic, ericoid, orchid, and ectomycorrhizal lifestyles. Switchgrass is an important bioenergy crop for cellulosic ethanol production owing to high biomass production on marginal soils otherwise unfit for food crop cultivation. The aim of this study was to investigate the host plant responses to Serendipita spp. colonization by characterizing the switchgrass root transcriptome during different stages of symbiosis in vitro. For this, we included a native switchgrass strain, Serendipita bescii, and a related strain, S. vermifera, isolated from Australian orchids. Serendipita colonization progresses from thin hyphae that grow between root cells to, finally, the production of large, bulbous hyphae that fill root cells during the later stages of colonization. We report that switchgrass seems to perceive both fungi prior to physical contact, leading to the activation of chemical and structural defense responses and putative host disease resistance genes. Subsequently, the host defense system appears to be quenched and carbohydrate metabolism adjusted, potentially to accommodate the fungal symbiont. In addition, prior to contact, switchgrass exhibited significant increases in root hair density and root surface area. Furthermore, genes involved in phytohormone metabolism such as gibberellin, jasmonic acid, and salicylic acid were activated during different stages of colonization. Both fungal strains induced plant gene expression in a similar manner, indicating a conserved plant response to members of this fungal order. Understanding plant responsiveness to Serendipita spp. will inform our efforts to integrate them into forages and row crops for optimal plant–microbe functioning, thus facilitating low-input, sustainable agricultural practices.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Large‐Scale 2D Perovskite Nanocrystals Photodetector Array via Ultrasonic Spray Synthesis

Abstract 2D perovskite (PVSK) single crystals have received significant attention due to their unique optical and optoelectronic properties. However, current synthesis methods face limitations, particularly in large‐area fabrication, which remain critical barriers to practical applications. In this study, the synthesis of red/green/purple‐blue‐colored 2D PVSK nanocrystals over a large area (4‐inch wafer) and the fabrication of high‐performance photodetector arrays are presented via a facile yet efficient spray‐coating approach with a liquid‐bridge transport effect. The photodetector array achieves 100% working yield, high photo‐responsivity (1.5 × 10 6 A W −1 ) and specific‐detectivity (1.1 × 10 16 Jones) with competitive photomapping characteristics. An intelligent vision system for automatic shape recognition is further demonstrated with a recognition rate exceeding 90%. This study provides significant advances in the scalable synthesis of nanoscale 2D PVSK crystals, their integration into large‐area optoelectronic devices, and their potential use in artificial‐intelligence systems.

Lee, Yoon Ho [Davidson School of Chemical Engineer↗
DOE OSTI2023

Disorder, interactions, and their interplay in novel narrow-gap Dirac materials and Weyl semimetals

Progress of the modern day condensed matter physics is to a large extent driven by the synthesis of new materials, advances in their experimental characterization and theoretical description. Recent discoveries of novel gapless Weyl semimetals, such as NaBi,CdAs, and BiTe-based films, in which magnetic dopants essentially suppress the gap, have added to the family of graphene and topological insulators actively investigated over the past decade. With the field of novel semimetals rapidly maturing, its focus necessarily shifts from demonstrations of the feasibility of such materials to their quantitative characterization. While the transport and optical properties of graphene and topological insulators are well captured within the picture of free non-interacting electrons, gapless 3D Weyl semimetals and narrow-gap 2D semiconductors with Dirac spectrum are known to be extremely susceptible to disorder and electron-electron interactions. This susceptibility obscures the manifestations of nontrivial band structure -- like quantum anomalous Hall effect -- of the new topological materials. Among particular projects to be addressed are: 1) optical conductivity of 3D gapless Dirac fermions in the presence of smooth disorder, 2) interplay of disorder and Coulomb interactions in the spectral properties of such fermions, 3) formation and structure of the impurity band with Coulomb supercritical clusters, 4) Coulomb interaction-driven renormalization of the electron spectrum and of the transport response in the presence of strong magnetic field, 5) instanton approach to the disorder-induced fluctuation states in zero-gap 3D materials, and 6) the role of disorder in quantum anomalous Hall effect. The proposal relies upon the investigators' previous broad expertise in interacting and disordered electron systems. The methods to be employed include perturbative diagrammatic technique, non-perturbative instanton and self-consistent approximations, hydrodynamics of electron liquid. Both analytical as well as numerical approaches are to be employed. The anticipated broader outcome of the proposal includes gaining an in-depth understanding of the interplay of the disorder and interactions under the conditions when this interplay has the most dramatic impact on observables. Traditionally, interaction effects are among the most challenging and interesting problems of condensed matter physics. Similarly, disordered systems typically present very difficult but extremely rich problems in the description of various materials. Importantly, understanding the spectral and transport properties of such materials not only presents the fundamental objective, but is also of particular interest for many applications, such as computation, memory, optics, plasmonics. In particular realization of the quantum anomalous Hall effect may lead to the development of low-power-consumption electronics. Indeed, a major constraint for practical use of the quantum Hall effect is limited by the requirement of the quantizing magnetic field. At the same time, the quantum anomalous Hall effect samples exhibit non-dissipative edge quantum transport in a zero magnetic field.

36 MATERIALS SCIENCE↗