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DOE OSTI2023

OpenCSP v.1.0

SAND2024-08987O OpenCSP analyzes and improves the performance of optical mirrors that reflect sunlight and concentrate it onto a receiver. The algorithms in this library analyze the flow of light from an original source—such as the sun—reflecting off one or more mirrors, and onto a receiver, optical screen, or camera. OpenCSP also analyzes optical systems using other techniques, such as shape or slope comparison. The software calculates aggregate properties of the optical system, such as its efficiency, manufacturing error, pointing control error, expected performance, and other useful parameters. OpenCSP also includes high-level tools, such as Open SOFAST, a program that obtains high-resolution measurement of CSP mirrors, full heliostats, and other CSP collectors. OpenCSP supports producing meaningful output data to help CSP designers and field operators improve the performance of their systems. OpenCSP also includes classes and functions that support these calculations, including input utilities, analysis output libraries, geometric constraint analysis for drone flight planning, and more. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Brost, Randolph↗

DOE OSTI2025

Investigating Fast Scanning Calorimetry and Differential Scanning Calorimetry as Screening Tools for Thermoset Polymer Material Compatibility with Laser-Based Powder Bed Fusion

As additive manufacturing (AM) technology has developed and progressed, a constant topic of research in the area is expanding the library of materials to be used with these techniques. Among AM methods that utilize polymers, laser-based powder bed fusion (PBF-LB) has preferentially used thermoplastic polymers as its starting materials, but the deposition and material joining method employed in PBF-LB may also be compatible with powdered thermoset polymer precursors as feedstocks. To assess the compatibility of candidate thermosetting polymers and PBF-LB, characterization techniques and protocols that link fundamental material behavior to material behavior in the processing environment are needed. Therefore, the objectives of this work are to compare the curing behavior measured with two different calorimetry techniques that can operate in different heating rate regimes, differential scanning calorimetry (DSC) and fast scanning calorimetry (FSC), and to assess the capabilities of these techniques to act as materials screening tools for PBF-LB. A commercial polyester powder coating is used as a model material to evaluate the potential of obtaining complimentary information for material screening through a combination of calorimetry methods, and its non-isothermal curing behavior is measured at heating rates between 5 °C/min and 7500 °C/min. Curing exotherms are observed with both calorimetry techniques, and comparing the enthalpy associated with curing shows that incomplete curing occurs at higher heating rates, with relative conversion values of approximately 30%. The curing data are fit with two isoconversional models, Friedman and Starink, which show a reduced activation energy at higher heating rates as well, signifying a lower barrier to curing at the conditions used in the FSC experiments. Overall, the results of this work indicate that using these two calorimetry techniques as tiered screening tools can provide valuable information about how curing may proceed in PBF-LB and inform materials selection and design activities for additive manufacturing.

36 MATERIALS SCIENCE↗

DOE OSTI2021

High-throughput screening of multifunctional nanocoatings based on combinations of polyphenols and catecholamines

Biomimetic surface coatings based on plant polyphenols and catecholamines have been used broadly in a variety of applications. However, the lack of a rational cost-effective platform for screening these coatings and their properties limits the true potential of these functional materials to be unleashed. Here, we investigated the oxidation behavior and coating formation ability of a library consisting of 45 phenolic compounds and catecholamines. UV–vis spectroscopy demonstrated significant acceleration of oxidation and polymerization under UV irradiation. We discovered that several binary mixtures resulted in non-additive behavior (synergistic or antagonistic effect) yielding much thicker or thinner coatings than individual compounds measured by ellipsometry. To investigate the properties of coatings derived from new combinations, we used a miniaturized high-throughput strategy to screen 2,532 spots coated with single, binary, and ternary combinations of coating precursors in one run. We evaluated the use of machine learning models to learn the relation between the chemical structure of the precursors and the thickness of the nanocoatings. Formation and stability of nanocoatings were investigated in a high-throughput manner via discontinuous dewetting. 30 stable combinations (hits) were used to tune the surface wettability and to form water droplet microarray and spot size gradients of water droplets on the coated surface. No toxicity was observed against eukaryotic HeLa cells and Pseudomonas aeruginosa (strain PA30) bacteria after 24 h incubation at 37 C. The strategy introduced here for high-throughput screening of nanocoatings derived from combinations of coating precursors enables the discovery of new functional materials for various applications in science and technology in a cost-effective miniaturized manner.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Heuristic Computational Model for Predicting Lignin Solubility in Tailored Organic Solvents

Lignin is a random heteropolymer that has been extensively studied as a renewable source of aromatic precursors for high-value chemicals, biofuels, and bioplastics. A key challenge in lignin valorization is the structural and compositional heterogeneity of lignin feedstocks. Solvent-based approaches are commonly used to fractionate lignin to reduce this heterogeneity, but solvent selection can be challenging due to variability in lignin composition. In this work, we developed computational methods to predict good and poor organic solvents as a function of lignin composition. We analyzed 28 different linear pentamer structures, 18 from known libraries and 10 hypothetical polymers, and calculated their activity coefficients in 50 different organic solvents by using the conductor-like screening model for realistic solvents. We used these data to train a regression model that enabled the extensive investigation of the impact of solvent and monolignol compositions on predicted lignin solubility. The exhaustive exploration of solubility trends using model predictions revealed sets of solvents, identified using Kamlet–Taft parameters, that are predicted to promote lignin dissolution regardless of lignin composition. We further identified solvents expected to selectively isolate lignin fractions enriched in certain subunits. Furthermore, these results establish heuristic guidelines for solvent selection that can be used to tailor fractionation processes for lignin feedstocks of distinct composition or to design new processes that isolate fractions with higher proportions of selected subunits.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Novel ceramic capacitors with ultrahigh energy density and efficiency (Final Technical Report)

Antiferroelectric ceramics are a special class of material that have shown great potential as the dielectric in electrical capacitors due to their high energy- and power-density. During each charge-discharge cycle, the ceramic undergoes transformation to a ferroelectric phase and resumes its antiferroelectric phase. The hysteresis associated with the transitions leads to a mediocre energy efficiency and service lifetime of antiferroelectric capacitors and, hence, their almost absence in commercial products. Under the support of this research project, we first formulated a universal lattice-compatibility theory that included electrostatic polarization energy along with elastic energy and thermal energy to understand the origin of the hysteresis in antiferroelectric oxides. Guided by this compatibility theory, we conducted high-throughput density functional theory (DFT) calculations to assess chemical modifiers and their effect on crystal structures of 400+ PbZrO 3 -based compositions. Down-selected compositions were experimentally validated for their suppressed hysteresis and higher energy efficiency. The verified low-hysteresis compositions were then expanded to an antiferroelectric ceramic library with nearly 500 new compositions (more than 1,500 samples) using high-throughput experiments involving ceramic synthesis and property screening. The large quantity of data generated (theory and experimental) in these tasks were processed by machine-learning techniques and identified trends were fed to the next iteration. In the end, we successfully discovered four compositions with near-zero hysteresis, yielding a world-record energy efficiency of 98.2% at an energy density of 3.0 J/cm 3 . Furthermore, our antiferroelectric ceramic capacitor reaches 79.5 million charge-discharge cycles lifetime, a factor of 80 enhancement over previous antiferroelectric ceramics with large hysteresis. These research accomplishments have not only met the milestones set in the SOPO, but also led to two patent filings, three journal publications (one of them was in Advanced Materials, impact factor 29.4), and nine oral presentations at various venues. Through the course of the project, three postdocs, four Ph.D. students, and one M.S. student were trained. In short, our project established a new methodology in searching next-generation functional ceramics on the fundamental side and discovered several high-efficiency antiferroelectric compositions for capacitors on the applied side. Once fabricated into the multilayer form for commercial applications, these ceramic capacitors can potentially enable the high temperature high power density DC-link capacitors that are critical for the next generation inverters in electric vehicles. The project also significantly contributed to the nation’s workforce development in the STEM fields.

36 MATERIALS SCIENCE↗

DOE OSTI2023

A combinatorial droplet microfluidic device integrated with mass spectrometry for enzyme screening

Mass spectrometry (MS) enables detection of different chemical species with a very high specificity; however, it can be limited by its throughput. Integrating MS with microfluidics has a tremendous potential to improve throughput and accelerate biochemical research. In this work, we introduce Drop-NIMS, a combination of a passive droplet loading microfluidic device and a matrix-free MS laser desorption ionization technique called nanostructure-initiator mass spectrometry (NIMS). This platform combines different droplets at random to generate a combinatorial library of enzymatic reactions that are deposited directly on the NIMS surface without requiring additional sample handling. The enzyme reaction products are then detected with MS. Drop-NIMS was used to rapidly screen enzymatic reactions containing low (on the order of nL) volumes of glycoside reactants and glycoside hydrolase enzymes per reaction. MS “barcodes” (small compounds with unique masses) were added to the droplets to identify different combinations of substrates and enzymes created by the device. We assigned xylanase activities to several putative glycoside hydrolases, making them relevant to food and biofuel industrial applications. Overall, Drop-NIMS is simple to fabricate, assemble, and operate and it has potential to be used with many other small molecule metabolites.

47 OTHER INSTRUMENTATION↗

DOE OSTI2016

Identification of fuel cycle simulator functionalities for analysis of transition to a new fuel cycle

Dynamic fuel cycle simulation tools are intended to model holistic transient nuclear fuel cycle scenarios. As with all simulation tools, fuel cycle simulators require verification through unit tests, benchmark cases, and integral tests. Model validation is a vital aspect as well. Although compara-tive studies have been performed, there is no comprehensive unit test and benchmark library for fuel cycle simulator tools. The objective of this paper is to identify the must test functionalities of a fuel cycle simulator tool within the context of specific problems of interest to the Fuel Cycle Options Campaign within the U.S. Department of Energy s Office of Nuclear Energy. The approach in this paper identifies the features needed to cover the range of promising fuel cycle options identified in the DOE-NE Fuel Cycle Evaluation and Screening (E&S) and categorizes these features to facilitate prioritization. Features were categorized as essential functions, integrating features, and exemplary capabilities. One objective of this paper is to propose a library of unit tests applicable to each of the essential functions. Another underlying motivation for this paper is to encourage an international dialog on the functionalities and standard test methods for fuel cycle simulator tools.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2024

Barcoded overexpression screens in gut Bacteroidales identify genes with roles in carbon utilization and stress resistance

Abstract A mechanistic understanding of host-microbe interactions in the gut microbiome is hindered by poorly annotated bacterial genomes. While functional genomics can generate large gene-to-phenotype datasets to accelerate functional discovery, their applications to study gut anaerobes have been limited. For instance, most gain-of-function screens of gut-derived genes have been performed in Escherichia coli and assayed in a small number of conditions. To address these challenges, we develop Barcoded Overexpression BActerial shotgun library sequencing (Boba-seq). We demonstrate the power of this approach by assaying genes from diverse gut Bacteroidales overexpressed in Bacteroides thetaiotaomicron . From hundreds of experiments, we identify new functions and phenotypes for 29 genes important for carbohydrate metabolism or tolerance to antibiotics or bile salts. Highlights include the discovery of a d -glucosamine kinase, a raffinose transporter, and several routes that increase tolerance to ceftriaxone and bile salts through lipid biosynthesis. This approach can be readily applied to develop screens in other strains and additional phenotypic assays.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2016

High-throughput screening of coenzyme preference change of thermophilic 6-phosphogluconate dehydrogenase from NADP + to NAD +

Coenzyme engineering that changes NAD(P) selectivity of redox enzymes is an important tool in metabolic engineering, synthetic biology, and biocatalysis. Here we developed a high throughput screening method to identify mutants of 6-phosphogluconate dehydrogenase (6PGDH) from a thermophilic bacterium Moorella thermoacetica with reversed coenzyme selectivity from NADP + to NAD + . Colonies of a 6PGDH mutant library growing on the agar plates were treated by heat to minimize the background noise, that is, the deactivation of intracellular dehydrogenases, degradation of inherent NAD(P)H, and disruption of cell membrane. The melted agarose solution containing a redox dye tetranitroblue tetrazolium (TNBT), phenazine methosulfate (PMS), NAD + , and 6-phosphogluconate was carefully poured on colonies, forming a second semi-solid layer. More active 6PGDH mutants were examined via an enzyme-linked TNBT-PMS colorimetric assay. Positive mutants were recovered by direct extraction of plasmid from dead cell colonies followed by plasmid transformation into E. coli TOP10. By utilizing this double-layer screening method, six positive mutants were obtained from two-round saturation mutagenesis. The best mutant 6PGDH A30D/R31I/T32I exhibited a 4,278-fold reversal of coenzyme selectivity from NADP + to NAD + . Furthermore, this screening method could be widely used to detect numerous redox enzymes, particularly for thermophilic ones, which can generate NAD(P)H reacted with the redox dye TNBT.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2016

Large Scale Screening of Low Cost Ferritic Steel Designs For Advanced Ultra Supercritical Boiler Using First Principles Methods

Advanced Ultra Supercritical Boiler (AUSC) requires materials that can operate in corrosive environment at temperature and pressure as high as 760°C (or 1400°F) and 5000psi, respectively, while at the same time maintain good ductility at low temperature. We develop automated simulation software tools to enable fast large scale screening studies of candidate designs. While direct evaluation of creep rupture strength and ductility are currently not feasible, properties such as energy, elastic constants, surface energy, interface energy, and stack fault energy can be used to assess their relative ductility and creeping strength. We implemented software to automate the complex calculations to minimize human inputs in the tedious screening studies which involve model structures generation, settings for first principles calculations, results analysis and reporting. The software developed in the project and library of computed mechanical properties of phases found in ferritic steels, many are complex solid solutions estimated for the first time, will certainly help the development of low cost ferritic steel for AUSC.

36 MATERIALS SCIENCE↗

DOE OSTI2015

Acoustic transfer of protein crystals from agarose pedestals to micromeshes for high-throughput screening

An acoustic high-throughput screening method is described for harvesting protein crystals and combining the protein crystals with chemicals such as a fragment library. Acoustic droplet ejection (ADE) is an emerging technology with broad applications in serial crystallography such as growing, improving and manipulating protein crystals. One application of this technology is to gently transfer crystals onto MiTeGen micromeshes with minimal solvent. Once mounted on a micromesh, each crystal can be combined with different chemicals such as crystal-improving additives or a fragment library. Acoustic crystal mounting is fast (2.33 transfers s{sup −1}) and all transfers occur in a sealed environment that is in vapor equilibrium with the mother liquor. Here, a system is presented to retain crystals near the ejection point and away from the inaccessible dead volume at the bottom of the well by placing the crystals on a concave agarose pedestal (CAP) with the same chemical composition as the crystal mother liquor. The bowl-shaped CAP is impenetrable to crystals. Consequently, gravity will gently move the crystals into the optimal location for acoustic ejection. It is demonstrated that an agarose pedestal of this type is compatible with most commercially available crystallization conditions and that protein crystals are readily transferred from the agarose pedestal onto micromeshes with no loss in diffraction quality. It is also shown that crystals can be grown directly on CAPs, which avoids the need to transfer the crystals from the hanging drop to a CAP. This technology has been used to combine thermolysin and lysozyme crystals with an assortment of anomalously scattering heavy atoms. The results point towards a fast nanolitre method for crystal mounting and high-throughput screening.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2026

Benchtop Autonomous Electrochemical Characterization System for Combinatorial Thin-Film Solid Oxide Electrodes

The design of materials for electrochemical energy conversion is complicated by a vast search space of candidate materials and multifaceted property requirements: multicarrier conductivity, stability, and catalytic activity are all necessary but rarely intersect. Although self-driving laboratories are rapidly rising to address such material optimization problems, the required infrastructure for integrated, large-scale robotic facilities can be cost-prohibitive. Here we develop and evaluate a closed-loop measurement system for efficient screening of proton-conducting oxide electrodes for ceramic fuel cells and electrolyzers, building on top of an existing benchtop instrument and integrating techniques for rapid impedance measurement and automated analysis. This system exemplifies a “minimum viable” self-driving implementation that can deliver substantial benefits with relatively simple infrastructure. Combinatorial thin-film microelectrode libraries are characterized with a recently developed joint time-domain and frequency-domain impedance measurement technique, which provides an order-of-magnitude acceleration relative to conventional impedance spectroscopy. The distribution of relaxation times is extracted from impedance data and analyzed without human intervention. These results feed an active learning and Bayesian optimization process that learns to predict electrochemical impedance as a function of material composition, measurement temperature, oxygen partial pressure, and electrical bias, which further reduces the screening time by tenfold with optimized experimental sequences. We apply this system to Ba⁡(Co,Fe,Zr,Y)⁢O 3−𝛿 combinatorial libraries and evaluate its effectiveness for learning material property trends and optimizing expensive-to-evaluate properties such as activation energy. This offers insights into key methodological aspects of practical autonomous experimentation, including surrogate model validation, cost-aware acquisition functions, and high-throughput data interpretation. Our results demonstrate the efficacy of the system for rapidly gathering information, but also highlight real-world experimental challenges of thin-film degradation and numerical instability in surrogate models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2018

Reactor design and integration with product detection to accelerate screening of electrocatalysts for carbon dioxide reduction

Identifying new catalyst materials for complex reactions such as the electrochemical reduction of CO 2 poses substantial instrumentation challenges due to the need to integrate reactor control with electrochemical and analytical instrumentation. Performing accelerated screening to enable exploration of a broad span of catalyst materials poses additional challenges due to the long time scales associated with accumulation of reaction products and the detection of the reaction products with traditional separation-based analytical methods. The catalyst screening techniques that have been reported for combinatorial studies of (photo)electrocatalysts do not meet the needs of CO 2 reduction catalyst research, prompting our development of a new electrochemical cell design and its integration to gas and liquid chromatography instruments. To enable rapid chromatography measurements while maintaining sensitivity to minor products, the electrochemical cell features low electrolyte and head space volumes compared to the catalyst surface area. Additionally, the cell is operated as a batch reactor with electrolyte recirculation to rapidly concentrate reaction products, which serves the present needs for rapidly detecting minor products and has additional implications for enabling product separations in industrial CO 2 electrolysis systems. To maintain near-saturation of CO 2 in aqueous electrolytes, we employ electrolyte nebulization through a CO 2 -rich headspace, achieving similar gas-liquid equilibration as vigorous CO 2 bubbling but without gas flow. The instrument is demonstrated with a series of electrochemical experiments on an Au-Pd combinatorial library, revealing non-monotonic variations in product distribution with respect to catalyst composition. The highly integrated analytical electrochemistry system is engineered to enable automation for rapid catalyst screening as well as deployment for a broad range of electrochemical reactions where product distribution is critical to the assessment of catalyst performance.

47 OTHER INSTRUMENTATION↗

DOE OSTI2014

Narrowing the gap between the promise and reality of polyketide synthases as a synthetic biology platform

Engineering modular polyketide synthases (PKSs) has the potential to be an effective methodology to produce existing and novel chemicals. However, this potential has only just begun to be realized. We propose the adoption of an iterative design-build-test-learn paradigm to improve PKS engineering. We suggest methods to improve engineered PKS design by learning from laboratory-based selection; adoption of DNA design software and automation to build constructs and libraries more easily; tools for the expression of engineered proteins in a variety of heterologous hosts; and mass spectrometry-based high-throughput screening methods. Finally, lessons learned during iterations of the design-build-test-learn cycle can serve as a knowledge base for the development of a single retrosynthesis algorithm usable by both PKS experts and non-experts alike.

Poust, S↗

DOE OSTI2017

Kip, Version 1.0

This high-performance ray tracing library provides very fast rendering, compact code, type flexibility via C++ 'generic programming' techniques, and ease of use through an application programming interface (API) that functions independently of any GUI, on-screen display, or other enclosing application. Kip supports constructive solid geometry models based on any of several built-in shapes and operators and allows for new, user-defined shapes and operators. Additional features include basic texturing, input/output of models using a simple human-readable file format with full error checking and detailed diagnostics, and support for shared data parallelism. Kip is written in pure, ANSI Standard C++, is entirely platform independent, and is very easy to use, as it requires no build system, configuration or installation scripts, wizards, special preprocessing, makefiles, or external libraries.

Staley, Martin↗

DOE OSTI2012

Re-examining the Evidence in Radiation Dermatitis Management Literature: An Overview and a Critical Appraisal of Systematic Reviews

Purpose: To provide an overview and a critical appraisal of systematic reviews (SRs) of published interventions for the prevention/management of radiation dermatitis. Methods and Materials: We searched Medline, CINAHL, Embase, and the Cochrane Library. We also manually searched through individual reference lists of potentially eligible articles and a number of key journals in the topic area. Two authors screened all potential articles and included eligible SRs. Two authors critically appraised and extracted key findings from the included reviews using AMSTAR (the measurement tool for 'assessment of multiple systematic reviews'). Results: Of 1837 potential titles, 6 SRs were included. A number of interventions have been reported to be potentially beneficial for managing radiation dermatitis. Interventions evaluated in these reviews included skin care advice, steroidal/nonsteroidal topical agents, systemic therapies, modes of radiation delivery, and dressings. However, all the included SRs reported that there is insufficient evidence supporting any single effective intervention. The methodological quality of the included studies varied, and methodological shortfalls in these reviews might create biases to the overall results or recommendations for clinical practice. Conclusions: An up-to-date high-quality SR in the prevention/management of radiation dermatitis is needed to guide practice and direction for future research. We recommend that clinicians or guideline developers critically evaluate the information of SRs in their decision making.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2019

High‐quality genome‐scale metabolic modelling of Pseudomonas putida highlights its broad metabolic capabilities

Summary Genome‐scale reconstructions of metabolism are computational species‐specific knowledge bases able to compute systemic metabolic properties. We present a comprehensive and validated reconstruction of the biotechnologically relevant bacterium Pseudomonas putida KT2440 that greatly expands computable predictions of its metabolic states. The reconstruction represents a significant reactome expansion over available reconstructed bacterial metabolic networks. Specifically, i JN1462 (i) incorporates several hundred additional genes and associated reactions resulting in new predictive capabilities, including new nutrients supporting growth; (ii) was validated by in vivo growth screens that included previously untested carbon (48) and nitrogen (41) sources; (iii) yielded gene essentiality predictions showing large accuracy when compared with a knock‐out library and Bar‐seq data; and (iv) allowed mapping of its network to 82 P . putida sequenced strains revealing functional core that reflect the large metabolic versatility of this species, including aromatic compounds derived from lignin. Thus, this study provides a thoroughly updated metabolic reconstruction and new computable phenotypes for P . putida , which can be leveraged as a first step toward understanding the pan metabolic capabilities of Pseudomonas .

Microbiology↗

DOE OSTI2020

Graph-Directed Approach for Downselecting Toxins for Experimental Structure Determination

Conotoxins are short, cysteine-rich peptides of great interest as novel therapeutic leads and of great concern as lethal biological agents due to their high affinity and specificity for various receptors involved in neuromuscular transmission. Currently, of the approximately 6000 known conotoxin sequences, only about 3% have associated structural characterization, which leads to a bottleneck in rapid high-throughput screening (HTS) for identification of potential leads or threats. In this work, we combine a graph-based approach with homology modeling to expand the library of conotoxin structures and to identify those conotoxin sequences that are of the greatest value for experimental structural characterization. The latter would allow for the rapid expansion of the known structural space for generating high quality template-based models. Our approach generalizes to other evolutionarily-related, short, cysteine-rich venoms of interest. Overall, we present and validate an approach for venom structure modeling and experimental guidance and employ it to produce a 290%-larger library of approximate conotoxin structures for HTS. We also provide a set of ranked conotoxin sequences for experimental structure determination to further expand this library.

59 BASIC BIOLOGICAL SCIENCES↗