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DOE OSTI2020

Energy Intensity Baselining and Tracking Guidance

Each company joining the U.S. Department of Energy’s (DOE’s) Better Buildings, Better Plants Program (Better Plants) commits to establishing an energy consumption and energy intensity (EI) baseline and to tracking its energy performance over a 10-year period against that baseline. The baseline must reflect a company’s energy consumption over a 12-month period, covering all its U.S.-based operations. Energy consumption is calculated by fuel type in terms of primary energy (also known as source energy). EI is broadly defined as the amount of energy consumed per unit of output produced. For this guidance document and for the program, the term energy performance represents an evaluation of a facility’s capacity to use energy efficiently. Metrics used to assess a facility’s energy performance can include EI, energy consumption, improvements in EI, etc. Establishing an energy baseline and tracking system is a critical first step in effectively managing energy use. Developing a baseline can help a company understand energy use within the corporation and give it a point of comparison to evaluate future efforts to improve energy performance. It can also support efforts to validate a company’s energy management activities, improve comparative analyses when using benchmarks, and help in predicting future energy needs. In addition, a company that normalizes its performance data can determine highly defensible measures of energy savings generated through implemented energy efficiency projects. Establishing a baseline and tracking energy performance is also a requirement for ISO 50001 certification. Although basic energy data can be collected through utility bills, most manufacturers will have to perform additional analyses to develop accurate and robust energy baselines and tracking systems. Energy is consumed in many ways within the manufacturing sector and can come from multiple sources. Energy is sometimes generated and sold to other parties or captured and reused on-site. External events can exert a significant impact on a facility or company’s energy use independent of any purposeful efforts to improve energy efficiency. Operational changes, such as production shifts—which may be inevitable for some companies over the 10-year period covered by the program—can also make a big difference in energy use. Since Better Plants asks companies to account for all their U.S.-based operations, mergers, acquisitions, and divestitures can also have significant implications for a company’s energy metrics. This document aims to demystify the sometimes complex baselining process. It devotes special attention to the task of normalizing and adjusting energy consumption to account for external factors, such as weather and production changes. A key recommendation is that companies use regression analysis to normalize their energy consumption data whenever possible. Regression analysis is a statistical technique that estimates the dependence of a variable (i.e., energy use in the context of Better Plants) on one or more independent variables such as ambient temperature, while controlling for the influence of other variables at the same time. A properly developed regression analysis can provide a reliable estimate of energy savings resulting from energy improvement strategies and projects by accounting for the effects of variables such as annual production levels and weather. DOE has developed a companion Energy Performance Indicator software tool (EnPI) to simplify the baselining process. This tool can run regression models, calculate changes in EI at the facility level, and automatically compile facility-level data into a corporate-wide metric. Note that although the relevant equations used to calculate EI are provided in this document, the EnPI tool will automatically perform most calculations for the user. Additionally, Better Plants Partners (Partners) can call on their Technical Account Manager (TAM) to help them establish a baseline and assist with the necessary calculations to track progress.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2017

Impact of media and antifoam selection on monoclonal antibody production and quality using a high throughput micro-bioreactor system

Monoclonal antibody production in commercial scale cell culture bioprocessing requires a thorough understanding of the engineering process and components used throughout manufacturing. It is important to identify high impact components early on during the lifecycle of a biotechnology-derived product. While cell culture media selection is of obvious importance to the health and productivity of mammalian bioreactor operations, other components such as antifoam selection can also play an important role in bioreactor cell culture. Silicone polymer-based antifoams were known to have negative impacts on cell health, production, and downstream filtration and purification operations. High throughput screening in micro-scale bioreactors provides an efficient strategy to identify initial operating parameters. Here, we utilized a micro-scale parallel bioreactor system to study an IgG1 producing CHO cell line, to screen Dynamis, ProCHO5, PowerCHO2, EX-Cell Advanced, and OptiCHO media, and 204, C, EX-Cell, SE-15, and Y-30 antifoams and their impacts on IgG1 production, cell growth, aggregation, and process control. This study found ProCHO5, EX-Cell Advanced, and PowerCHO2 media supported strong cellular growth profiles, with an IVCD of 25-35 3 106 cells-d/ mL, while maintaining specific antibody production (Qp> 2 pg/cell-d) for our model cell line and a monomer percentage above 94%. Antifoams C, EX-Cell, and SE-15 were capable of providing adequate control of foaming while antifoam 204 and Y-30 noticeably stunted cellular growth. This work highlights the utility of high throughput micro bioreactors and the importance of identifying both positive and negative impacts of media and antifoam selection on a model IgG1 producing CHO cell line.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2019

Improving Energy Efficiency of Air Separation via Hollow Fiber Sorbents

This report summarizes the work performed under the Department of Energy’s National Energy Technology Laboratory (DOE-NETL) Advanced Energy Systems Program award number DE-FE0026163 Improving Energy Efficiency of Air Separation via Hollow Fiber Sorbents. The overall objective of the project was to develop technology to produce oxygen for use in coal gasification processes at a significantly lower cost than that of the commercial state-of-the-art technology. The focus of the project was development and optimization of hollow fiber sorbents for use in a pressure swing adsorption (PSA) process for producing oxygen from air. The key technical advancement under this program was the development of a hollow fiber sorbent capable of producing oxygen in a PSA process. PSAs produce oxygen by using a beaded zeolite material (typically lithium exchanged zeolites or LiX) that selectively adsorb nitrogen over oxygen. For a fiber to adsorb nitrogen, LiX needed to be integrated into a polymer fiber and then activated at over 350C to remove residual moisture. After screening multiple materials and process techniques, Matrimid/LiX hollow fibers were produced that were able to withstand the activation and had crystalline nitrogen capacity close to pure LiX crystals. The fibers were dual layer fibers with a barrier layer isolating the hollow bore from the LiX embedded layer. The barrier layer was formed from an Ultem® based solution. The hollow bore was intended for encapsulating phase change materials to ensure isothermal PSA operation. Modeling work from the project suggested that the benefits of this additional complexity were marginal, thus the team fabricated non-hollow fibers comprised of Matrimid and LiX. The Matrimid/LiX fibers were loaded into a module and tested on a bench scale PSA unit. The fibers were able to separate oxygen from air, but the purity and recovery were lower than expected and lower than traditional beaded LiX zeolites, although modeling results suggested that the bed sizes for fiber sorbents could be half the size of a beaded LiX bed. Additional work will be needed to understand the shortfall and to produce fiber sorbent modules with performance equal to the targets set for this program. In addition to producing fibers, modeling work was carried out at both the fiber level and process level to guide both fiber sorbent development and to determine the optimal process conditions for a PSA using fiber sorbents. A 2D hollow fiber model was developed in gPROMS Model Builder. This model was based on literature data for mass transfer and other parameters. This model used a basic single bed PSA process to determine important fiber properties and process conditions for achieving high oxygen recovery. The preliminary 2D fiber model was a valuable tool, however, for step-out technologies, such as a PSA process with fiber sorbents, intelligent optimization and plant control was needed to effectively determine minimum power designs. Therefore, a gPROMS Process Builder-based optimization tool was developed with an “Automated Cycle Optimizer” model that was able to determine optimal cycle conditions for a fiber sorbent PSA. The results from the optimizer were used in the final power analysis. Flow sheet analysis and techno-economic analysis (TEA) was carried out to determine a lower power solution versus the baseline case. The original project scope suggested that the fiber sorbent PSA could be used to debottleneck a cryogenic air separation plant (cryo-ASU) with the combined plant having lower power than a standalone cryo-ASU. However, early flowsheet analysis showed that the PSA/cryo-ASU concept would not lead to a lower power solution. However, further flowsheet analysis suggested that an oxygen PSA combined with a nitrogen PSA could have lower power versus state-of-the-art air separation technology. Work concluded with the TEA showing a fiber sorbent oxygen PSA combined with an advanced nitrogen PSA could be up to 8% lower power versus the base case cryo-ASU. Overall, there is significant potential remaining for the zeolite hollow fiber sorbent concept, and this project successfully identified -- and ultimately remedied -- many technical challenges associated with scale-up.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2020

Deep neural network improves the estimation of polygenic risk scores for breast cancer

Polygenic risk scores (PRS) estimate the genetic risk of an individual for a complex disease based on many genetic variants across the whole genome. Here, we compared a series of computational models for estimation of breast cancer PRS. A deep neural network (DNN) was found to outperform alternative machine learning techniques and established statistical algorithms, including BLUP, BayesA, and LDpred. In the test cohort with 50% prevalence, the Area Under the receiver operating characteristic Curve (AUC) were 67.4% for DNN, 64.2% for BLUP, 64.5% for BayesA, and 62.4% for LDpred. BLUP, BayesA, and LPpred all generated PRS that followed a normal distribution in the case population. However, the PRS generated by DNN in the case population followed a bimodal distribution composed of two normal distributions with distinctly different means. This suggests that DNN was able to separate the case population into a high-genetic-risk case subpopulation with an average PRS significantly higher than the control population and a normal-genetic-risk case subpopulation with an average PRS similar to the control population. This allowed DNN to achieve 18.8% recall at 90% precision in the test cohort with 50% prevalence, which can be extrapolated to 65.4% recall at 20% precision in a general population with 12% prevalence. Interpretation of the DNN model identified salient variants that were assigned insignificant p values by association studies, but were important for DNN prediction. These variants may be associated with the phenotype through nonlinear relationships.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

TAILORED BIOBLENDSTOCKS WITH LOW ENVIRONMENTAL IMPACT TO OPTIMIZE MCCI ENGINES

The overall objective of the project is to develop and demonstrate a microalgae bio-blendstock with greater than 60% greenhouse gas reduction potential relative to petroleum diesel, that can reduce sooting propensity, increase cetane number and improve engine thermal efficiency relative to a baseline diesel engine operating on conventional fuel. Specific objectives include: (1) development of a new framework for both LCA and TEA that explicitly considers temporal variation in productivity and the frequency of crop loss; (2) determination of how fuel compounds that can be produced from the algal biomass can be ‘bio-tailored’ based on the species composition and biological production process, and subsequent processing via HTL to biocrude, and upgrading of the biocrude; (3) execution of a feedback loop (algae production  biocrude refining  combustion optimization  feedback to refining stage), for optimization of fuels for MCCI combustion; (4) optimization of MCCI combustion and emissions performance, accounting first for the biological processes that dictate the chemical composition of biocrude oil, and second for the subsequent chemical processes that comprise mixing controlled compression ignition combustion; (6) simulation of MCCI engine combustion processes to demonstrate the incorporation of relevant fuel chemistry that captures the specific impacts of optimized algal fuels.

09 BIOMASS FUELS↗

DOE OSTI2017

Basic Energy Sciences Roundtable: Opportunities for Basic Research for Next-Generation Quantum Systems

For decades, scientists have predicted that devices based on “quantum phenomena” will be able to store and manipulate information to provide radical new approaches for computing, communication, and sensing. However, only recently have quantum phenomena been incorporated into technologies for next-generation computers, sensors, and detectors that demonstrate performance characteristics rivaling those of their conventional counterparts. These devices clearly demonstrate the enormous potential for future quantum-based technologies. The novel quantum device capabilities currently envisioned include enhanced resolution in imaging, sensors, and detectors; advanced cryptography for more secure communication; and significantly larger computational capabilities at speeds far greater than those possible in classical computing. However, realizing these advances requires a detailed understanding of how quantum systems (including quantum materials or assemblies of trapped ions and electrons) behave, accurate knowledge of how to integrate the components into complex systems, and precise control of the structures. In this context, creating and controlling quantum states within molecules and materials offer exciting scientific opportunities for fundamental research, as well as for enabling next-generation quantum-based technologies. Numerous questions remain, ranging from how quantum interactions may enable innovation through the creation of novel quantum systems, to how these new quantum technologies can advance our understanding of matter and chemistry at the most fundamental levels. To address these questions and identify priority research opportunities (PROs), the US Department of Energy (DOE) Office of Basic Energy Sciences (BES) convened a roundtable of experts in quantum materials and quantum systems encompassing the fields of physics, chemistry, materials synthesis science, device engineering, detector technology, and atomic-scale characterization techniques. This group of experimentalists and theorists met on October 30–31, 2017, to explore scientific research opportunities in this rapidly moving field, in which BES support can play a key role in advancing and utilizing quantum information science (QIS). The goals of this roundtable were to define the unique roles for BES in this active research field and to provide input on future research directions, forming the basis for a coordinated, long-term research effort that will enable major advances in quantum-based science and technology. BES is uniquely positioned to advance this field because of its long history of fundamental research support for both materials and chemical sciences, along with its construction and operation of world-class scientific user facilities. Fundamental research in this area is strongly coupled to DOE efforts in scientific computing, high-energy physics, and accelerator/detector research and related to activities in “Beyond Moore’s Law” computing, next-generation semiconductor materials, and exascale computing.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2023

Development and Bench-Scale Testing of a Novel Biphasic Solvent-Enabled Absorption Process for Post-Combustion Carbon Capture (Final Technical Report)

A new class of biphasic solvents was developed, and the concept of the enabled carbon dioxide (CO 2 ) absorption process was tested for post-combustion carbon capture in our previous lab-scale research. The primary goals of this project were to advance the development of the novel biphasic CO 2 absorption process (BiCAP) and validate its technical advantages by testing the integrated technology at a 40 kWe bench-scale with actual coal-derived flue gas in a power plant environment. The project was led by the University of Illinois at Urban-Champaign (UIUC), and Trimeric Corporation served as a sub-awardee providing support in basic design and techno-economic studies. To achieve the project goals and objectives, solvent management studies, process modeling and optimization, bench-scale equipment design, construction and testing, and technical, economic and environmental assessments have been conducted. The two top-performing biphasic solvents developed in our previous research were used in this project. Biphasic solvent emissions and control were investigated in the laboratory. The emissions of the biphasic solvents from the absorber were comparable to or lower than the reference 30 wt% monoethanolamine (MEA) solution, while they could be more effectively removed in the water wash column. Lab-scale testing of solvent degradation reclamation has revealed that vacuum distillation was feasible for biphasic solvent reclamation. Aspen Plus models were used to optimize the BiCAP, and a CO 2 stripping configuration introducing a secondary cold solvent feed to the stripper was identified to be the most energy efficient. A 40 kWe bench-scale, integrated BiCAP system was successfully designed, fabricated, and installed at the UIUC’s Abbott Power Plant. Parametric testing with synthetic flue gas has demonstrated that the two biphasic solvents required a more than 40% lower heat duty for CO 2 desorption as compared to the reference MEA tested on the same bench-scale skid. Slipstream testing with actual coal flue gas for a total of 31 days in two test campaigns has further demonstrated stable operation of the bench-scale skid. During the first campaign targeting 90% CO 2 removal, the heat duty averaged at 2,183 MJ/tonne of CO 2 captured and during the second campaign targeting 95% removal, the heat duty averaged at 2,450 MJ/tonne of CO 2 captured. A techno-economic analysis has revealed that for integration of the BiCAP into a 650-MWe pulverized coal-fired power plant, the parasitic power loss was reduced by ~20%, and the cost of CO 2 capture was reduced by ~21% ($36.3/tonne on a December 2018 dollar basis) compared to the U.S. Department of Energy (DOE)’s baseline Case B12B. As progression from this bench-scale development effort, a new project “Engineering-Scale Testing of the Biphasic Solvent Based CO 2 Absorption Capture Technology at a Covanta Waste-to-Energy Facility” was awarded by the DOE, launched in February 2023, to allow the team to further test the technology and demonstrate its technical and economic advantages at a pilot scale.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2016

Effective Exploration of New 760°C-Capability Steels for Coal Energy

Cost effective and high performance alloys that are capable of operating at 760 °C or higher for extended periods of time under a very aggressive environment are critically required for the design and development of advanced ultrasupercritical (AUSC) boilers and steam turbines. Finely dispersed Laves phase precipitates have been shown by Takeyama and co-workers to be a viable strengthening mechanism in high temperature austenitic steels. There is currently no straightforward theory that can predict what other intermetallic phases can serve as potent precipitation-strengthening phases for steels; thus we employed a highly effective dual-anneal diffusion multiple (DADM) approach to screen for viable strengthening precipitates over a wide range of compositions. From the Fe-Co-Cr-Ni-Mo DADMs, the Fe-Cr-Mo based Chi phase was identified as a new strengthening phase for high temperature ferritic steels; and from the Fe-Mn-Cr-Nb-Ni-Mo-FeAl DADMs, the Laves phase was identified as a viable strengthening precipitate in Fe-Mn and Fe-Ni based austenitic steels. After identification of viable strengthening phases from the DADMs that covered compositions in the basic ternary and quaternary systems, we employed computation thermodynamics to perform multicomponent alloy design and optimization. For the new the Chi-phase strengthened steels, we performed thermodynamic calculations to vary the volume fraction of the Chi phase and introduced Nb and carbon to promote the formation of stable carbides for grain size control during solution heat treatment. For the Fe-Ni-Mn based austenitic steels, we performed extensive parametric optimization of compositions in order to reduce the expensive Ni content, add Cr and Al for oxidation resistance, and balance the alloying contents (Ni, Mn, Cr, Al, Mo) to suppress the ferritic phase and promote the austenitic matrix phase. Four steels (two ferritic + two austenitic) were designed and tested. The two Chi-phase strengthened ferritic steels exhibited excellent oxidation resistance and good creep-rupture strength at moderate temperatures, considering their ferritic matrix that usually results in lower creep resistance than austenitic steels. These steels showed brittleness and sample-to-sample variability in ductility. The low ductility might be due to the macro segregation during solidification or the significant grain growth during the solution heat treatments. We believe there is no inherent brittleness based on the chemistry of the steels. The creep-rupture performance of the steels is comparable to the 9Cr steels. Due to their ferritic matrix, the new Chi-phase strengthened ferritic steels may not be suited for the 760 °C AUSC applications, but they are very good candidates for intermediate temperature applications due to their outstanding oxidation resistance and high strength. Further study is required to find the source of low and highly variable ductility. We believe the compositions of the Chi-phase strengthened steels are not inherently brittle. The Chi-phase strengthened ferritic steels may also be excellent candidates for intermediate-temperature and room-temperature cast stainless steels, thus we highly recommend further investigations. The two Mn-containing austenitic steels based on the Laves phase showed good ductility, excellent oxidation resistance (slightly inferior to the two ferritic steels) at high temperatures and moderate creep strength. The creep-strength of the two austenitic steels based on the Larson-Miller parameters is higher than that of the traditional 316 stainless steels, but lower than the alumina-forming alloys (AFAs) developed at Oak Ridge National Laboratories. We do not recommend high priority in further studying these compositions unless higher Cr alloys are required for hot-corrosion resistance.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2020

Tailored Bioblendstocks with Low Environmental Impact to Optimize MCCI Engines

09 BIOMASS FUELS↗

DOE OSTI2021

Atomic Force Microscopy and Infrared Nanospectroscopy of COVID-19 Spike Protein for the Quantification of Adhesion to Common Surfaces

The COVID-19 pandemic has claimed millions of lives worldwide, sickened many more, and has resulted in severe socio-economic consequences. As society returns to normal, understanding the spread and persistence of SARS CoV-2 on commonplace surfaces can help to mitigate future outbreaks of coronaviruses and other pathogens. We hypothesize that such an understanding can be aided from studying the binding and interaction of viral proteins with non-biological surfaces. Here, we propose a methodology for investigating the adhesion of the SARS CoV-2 spike glycoprotein on common inorganic surfaces such as aluminum-, copper-, iron-, silica-, and ceria-oxides as well as metallic gold. Quantitative adhesion was obtained from the analysis of measured forces at the nanoscale using an atomic force microscope operated under ambient conditions. Without imposing further constraints on the measurement conditions, our preliminary findings suggest that spike glycoproteins interact with similar adhesion forces across the majority of the metal oxides tested with the exception to gold, for which attraction forces ~10 times stronger than all other materials studied were observed. Ferritin, which was used as a reference protein, was found to exhibit similar adhesion forces as SARS CoV-2 spike protein. Further, this study results show that glycoprotein adhesion forces for similar ambient humidity, tip shape, and contact surface are non-specific to the properties of metal oxide surfaces, which are expected to be covered by a thin water film. The findings suggest that at ambient conditions glycoprotein adhesion to metal oxides is primarily controlled by the water capillary forces and they depend on the surface tension of the liquid (water). We discuss further strategies warranted to decipher the intricate nanoscale forces for improved quantification of the adhesion.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2016

Single-Amino Acid Modifications Reveal Additional Controls on the Proton Pathway of [FeFe]-Hydrogenase

The proton pathway of [FeFe]-hydrogenase is essential for enzymatic H2 production and oxidation and is composed of four residues and a modeled water molecule. Recently, a computational analysis of this pathway revealed that the solvent-exposed residue of the pathway (Glu282) could form hydrogen bonds to two residues outside of the pathway (Arg286 and Ser320), implicating that these residues could function in regulating proton transfer. Substituting Arg286 with leucine eliminates hydrogen bonding with Glu282 and results in a 2.5-fold enhancement in H2 production activity, suggesting that Arg286 serves an important role in controlling the rate of proton delivery. In contrast, substitution of Ser320 with alanine reduces the rate approximately 5-fold, implying that it either acts as a member of the pathway or influences Glu282 to enable proton transfer. Interestingly, QM/MM and molecular dynamics calculations indicate that Ser320 does not play an electronic or structural role. QM calculations also estimate that including Ser320 in the pathway does not significantly change the barrier to proton movement, providing further support for its role as a member of the proton pathway. While further studies are needed to quantify the role of Ser320, collectively, these data provide evidence that the enzyme scaffold plays a significant role in modulating the activity of the enzyme, demonstrating that the rate of intraprotein proton transfer can be accelerated, particularly in a non-biological context. This work was supported by the DOE Great Lakes Bioenergy Research Center (DOE BER Office of Science, DE-FC02-07ER64494). In addition, support from the DOE Office of Science Early Career Research Program through the Office of Basic Energy Sciences (WJS, BGP, SR) is gratefully acknowledged. Computational resources were provided at W. R. Wiley Environmental Molecular Science Laboratory (EMSL), a national scientific user facility sponsored by the Department of Energy’s Office of Biological and Environmental Research located at Pacific Northwest National Laboratory, and a portion of the research was performed using PNNL Institutional Computing at Pacific Northwest National Laboratory. Pacific Northwest National Laboratory is operated by Battelle for the U.S. Department of Energy.

catalysis↗

DOE OSTI2019

De novo design of programmable inducible promoters

Abstract Ligand-responsive allosteric transcription factors (aTF) play a vital role in genetic circuits and high-throughput screening because they transduce biochemical signals into gene expression changes. Programmable control of gene expression from aTF-regulated promoter is important because different downstream effector genes function optimally at different expression levels. However, tuning gene expression of native promoters is difficult due to complex layers of homeostatic regulation encoded within them. We engineered synthetic promoters de novo by embedding operator sites with varying affinities and radically reshaped binding preferences within a minimal, constitutive Escherichia coli promoter. Multiplexed cell-based screening of promoters for three TetR-like aTFs generated with this approach gave rich diversity of gene expression levels, dynamic ranges and ligand sensitivities and were 50- to 100-fold more active over their respective native promoters. Machine learning on our dataset revealed that relative position of the core motif and bases flanking the core motif play an important role in modulating induction response. Our generalized approach yields customizable and programmable aTF-regulated promoters for engineering cellular pathways and enables the discovery of new small molecule biosensors.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Structures of Neisseria gonorrhoeae MtrR-operator complexes reveal molecular mechanisms of DNA recognition and antibiotic resistance-conferring clinical mutations

Abstract Mutations within the mtrR gene are commonly found amongst multidrug resistant clinical isolates of Neisseria gonorrhoeae, which has been labelled a superbug by the Centers for Disease Control and Prevention. These mutations appear to contribute to antibiotic resistance by interfering with the ability of MtrR to bind to and repress expression of its target genes, which include the mtrCDE multidrug efflux transporter genes and the rpoH oxidative stress response sigma factor gene. However, the DNA-recognition mechanism of MtrR and the consensus sequence within these operators to which MtrR binds has remained unknown. In this work, we report the crystal structures of MtrR bound to the mtrCDE and rpoH operators, which reveal a conserved, but degenerate, DNA consensus binding site 5′-MCRTRCRN4YGYAYGK-3′. We complement our structural data with a comprehensive mutational analysis of key MtrR-DNA contacts to reveal their importance for MtrR-DNA binding both in vitro and in vivo. Furthermore, we model and generate common clinical mutations of MtrR to provide plausible biochemical explanations for the contribution of these mutations to multidrug resistance in N. gonorrhoeae. Collectively, our findings unveil key biological mechanisms underlying the global stress responses of N. gonorrhoeae.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Genomics-enabled analysis of specialized metabolism in bioenergy crops: Current progress and challenges

Plants produce a staggering diversity of specialized small molecule metabolites that play vital roles in mediating environmental interactions and stress adaptation. This chemical diversity derives from dynamic biosynthetic pathway networks that are often species-specific and operate under tight spatiotemporal and environmental control. A growing divide between demand and environmental challenges in food and bioenergy crop production have intensified research on these complex metabolite networks and their contribution to crop fitness. High-throughput omics technologies provide access to ever-increasing data resources for investigating plant metabolism. However, the efficiency of using such system-wide data to decode the gene and enzyme functions controlling specialized metabolism has remained limited; due largely to the recalcitrance of many plants to genetic approaches and the lack of ‘user-friendly’ biochemical tools for studying the diverse enzyme classes involved in specialized metabolism. With emphasis on terpenoid metabolism in the bioenergy crop switchgrass as an example, this review aims to illustrate current advances and challenges in the application of DNA synthesis and synthetic biology tools for accelerating the functional discovery of genes, enzymes and pathways in plant specialized metabolism. These technologies have accelerated knowledge development on the biosynthesis and physiological roles of diverse metabolite networks across many ecologically and economically important plant species and can provide resources for application to precision breeding and natural product metabolic engineering.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Investigation of Superluminescent Diodes for Smart Lighting Systems. Final Report

The solid-state lighting ecosystem has evolved very rapidly over the last few years, with significant improvements in the technical performance of light-emitting diodes (LEDs) and the commoditization of LED-based lighting fixtures. As the performance of conventional lighting products begins to saturate, there is growing market interest in “Lighting as a Service” applications that will leverage advanced systems to impart new functionalities to lighting and improve energy efficiency, human health, and productivity. These “Smart Lighting” systems will include high-performance light sources, specialized sensors, and dynamic controls to deliver high quality, energy efficient, color tunable lighting with customized spatial light delivery and integrated visible light communication capability. To achieve these capabilities, smart lighting systems will place greater demands on the performance of light sources. Highly efficient sources with additional functionalities compared to conventional LEDs, such as small form factor, large modulation bandwidth, and spatially coherent output beams, will be required. While laser diodes have been proposed as potential sources for smart lighting systems, they also exhibit several properties that pose challenges, such as temporal coherence, extremely high spatial coherence, and ultra-narrow linewidths. To address these issues, we propose an investigation of an alternative device architecture known as a superluminescent diode (SLD). SLDs are similar in form to ridge laser diodes and share many of the same characteristics, such as stimulated emission operation, spatially coherent output, small form factor, and the potential for large modulation bandwidth. However, the operating principle for SLDs is distinct from laser diodes in that SLDs lack a strong cavity feedback mechanism, resulting in spatially coherent but temporally incoherent light output. Thus, SLDs may address the issues with laser diodes for lighting, while simultaneously maintaining some of the desirable characteristics of both laser diodes and LEDs. The objectives of this proposal are to design, grow, and fabricate blue (450 nm) SLDs on polar c-plane and nonpolar m-plane free-standing GaN substrates, and to evaluate their potential as sources in smart lighting systems through basic device characterization and detailed investigations of their efficiency droop and modulation bandwidth. The primary scientific aims of this work are to understand the fundamental role of optical gain in the superluminescent (non-lasing) regime on efficiency droop and modulation bandwidth in III-nitride emitters and to understand the effects of higher optical gain on SLD performance by comparing polar c-plane and nonpolar m-plane SLDs. The University of New Mexico (UNM) will collaborate with Sandia National Laboratories (SNL) and the Center for Integrated Nanotechnologies to design, fabricate, grow, and characterize the SLDs. UNM will perform the design and epitaxial growth, while SNL will focus on the fabrication and device characterization. The novelty of the proposed work includes the first comprehensive theoretical and experimental investigations of efficiency droop and the first investigation of modulation bandwidth in GaN-based emitters operating in the superluminescent regime. Moreover, the comparison of c-plane and m-plane SLDs will enable the first analysis of the effects of higher optical gain on the device performance. The development of high-performance GaN-based SLDs may enable efficiency gains and improved functionality in next-generation smart lighting systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

Cineradiography System and Initial 3D-printed Brain Phantoms

Traumatic brain injury (TBI) is a significant cause of death in tactical, sport and civilian populations. According to the Center for Disease Control (CDC) report in 2016, TBI accounted for 227,000 hospitalizations and 60,000 related deaths. In the military, the prevalence of traumatic brain injuries is related to the type of conflict U.S. forces are involved in and are typically classified as mild traumatic brain injuries (mTBIs). Troops returning from Operation Enduring Freedom and Operation Iraqi Freedom had a TBI rate estimated at 15.2% to 22.8%; nearly 320,000 troops. These mTBIs were primarily blast-induced and often lacked any accompanying symptoms. Left untreated, these mild injuries have been linked to chronic disorders and cognitive alterations. One such disorder that has been frequently recorded in literature is chronic traumatic encephalopathy (CTE). CTE is a progressive neurodegenerative tauopathy resulting from repetitive mTBIs. The repetitive head injuries involved in sport, classified as mTBIs, has resulted in CTE development in athletes involved in contact sports. While the association between mTBIs and CTE has been pathologically verified, the mechanisms have yet to be identified. In order to better understand these mechanisms, the use of flash x-ray radiography is being considered.

42 ENGINEERING↗

DOE OSTI2018

Dynamic Model of Basic Oxygen Steelmaking Process Based on Multi-zone Reaction Kinetics: Model Derivation and Validation

A multi-zone kinetic model coupled with a dynamic slag generation model was developed for the simulation of hot metal and slag composition during the basic oxygen furnace (BOF) operation. The three reaction zones (i) jet impact zone, (ii) slag–bulk metal zone, (iii) slag–metal–gas emulsion zone were considered for the calculation of overall refining kinetics. In the rate equations, the transient rate parameters were mathematically described as a function of process variables. A micro and macroscopic rate calculation methodology (micro-kinetics and macro-kinetics) were developed to estimate the total refining contributed by the recirculating metal droplets through the slag–metal emulsion zone. The micro-kinetics involves developing the rate equation for individual droplets in the emulsion. The mathematical models for the size distribution of initial droplets, kinetics of simultaneous refining of elements, the residence time in the emulsion, and dynamic interfacial area change were established in the micro-kinetic model. In the macro-kinetics calculation, a droplet generation model was employed and the total amount of refining by emulsion was calculated by summing the refining from the entire population of returning droplets. A dynamic Fe{sub t}O generation model based on oxygen mass balance was developed and coupled with the multi-zone kinetic model. The effect of post-combustion on the evolution of slag and metal composition was investigated. The model was applied to a 200-ton top blowing converter and the simulated value of metal and slag was found to be in good agreement with the measured data. The post-combustion ratio was found to be an important factor in controlling Fe{sub t}O content in the slag and the kinetics of Mn and P in a BOF process.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Thermodynamic and Kinetic Roles of H2 in Structure Evolution of Urchin-like Co: A density functional theory study

Small gas molecules working as good capping agents play important roles in controlling the morphologies and surface structures of the metal nanocrystals. In present work, the thermodynamic and kinetic roles of H2 molecule played on the morphology of Co nanocrystal were systematically studied based on density functional theory (DFT). The Gibbs surface free energies (?) of Co(100), Co(110) and Co(111) under different hydrogen surface coverages were investigated by ab initio thermodynamics, based on which i) the phase diagrams of stable H coverage on each plane were obtained; ii) the morphology evolutions of the Co nanocrystals with various surface hydrogen coverages were further predicted by Wulff construction. It was revealed that addition of H2 could change the facet stability generating diverse morphological Co nucleus. The kinetic role of H2 was further explored by DFT during adatom Co surface diffusions under different H coverages (?H), which suggested that except for Co(100) at ?H of 0.56 ML, the surface H would hinder Co surface diffusions. The projected density of state (PDOS) gave a deeper insight that the electronic structures of the Co adatom could be alerted by addition of the surface H, which thereby affected its surface diffusion ability. X. Wang, N. Liu, Q. Zhang, X. Liang, and B. Chen were financially supported by the National Natural Science Foundation of China (No. 21476012, 21571012, and 91534201). D. Mei was supported by the US Department of Energy (DOE), Office of Science, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences & Biosciences. Pacific Northwest National Laboratory (PNNL) is a multiprogram national laboratory operated for DOE by Battelle. Computing time was granted by the facility user proposal grand challenge of computational catalysis of the William R. Wiley Environmental Molecular Sciences Laboratory (EMSL). EMSL is a national scientific user facility located at Pacific Northwest National Laboratory (PNNL) and sponsored by DOE’s Office of Biological and Environmental Research.

Nanocrystal Co, Surface free energy, Surface diffu↗