Solution structure and dynamics of the mitochondrial-targeted GTPase-activating protein (GAP) VopE b
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Smith, Kyle P.↗
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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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The Role of Fuels in Transforming Energy End-Use in Buildings and Industrial Processes
This book examines what role fuels have in the transformation of end-use in buildings and industrial processes. Energy efficient technologies are necessary to lower the carbon footprint for a transition towards clean energy in a sustainable manner. Efficient utilization of primary energy resources including renewables to support the current and future energy needs while targeting grid resiliency, energy and environmental security, at an affordable cost is of significant value. Analysis of configurations consisting of heat pumps, fuel driven thermal providers and power systems is presented. Sensitivity of electrical grid's carbon intensity towards carbon footprint in comparison with fuel driven technologies is necessary to recognize the true value proposition of currently available energy solutions for different end consumers. Similarly, the role of low carbon, zero carbon, and carbon negative fuels such as power to gas, power to liquid, hydrogen, biogas, etc. in conjunction with polygeneration technologies are discussed. Transformation of the primary energy resources from conventional fossil fuels to renewable fuels or electricity will have a significant impact on the overall carbon footprint of various end use sectors, including buildings. Hence, this book also examines two different scenarios focused on sensitivity of the pace of decarbonization of electrical grid and fuel supply on operational energy related carbon emissions.
Cheekatamarla, Praveen↗
Enhanced Dissolution of Platinum Group Metals Using Electroless Iron Deposition Pretreatment
In order to develop a new method for efficiently recovering platinum group metals (PGMs) from catalyst scraps, the authors investigated an efficient dissolution process where the material was pretreated by electroless Fe deposition. When Rh-loaded alumina powder was kept in aqua regia at 313 K (40 °C) for 30 to 60 minutes, the Rh hardly dissolved. Meanwhile, after electroless Fe plating using a bath containing sodium borohydride and potassium sodium tartrate as the reducing and complexing agents, respectively, approximately 60 pct of Rh was extracted by aqua regia at 313 K (40 °C) after 30 minutes. Furthermore, when heat treatment was performed at 1200 K (927 °C) for 60 minutes in vacuum after electroless plating, the extraction of Rh approached 100 pct for the same leaching conditions. The authors also confirmed that the Fe deposition pretreatment enhanced the dissolution of Pt and Pd. These results indicate that an effective and environmentally friendly process for the separation and extraction of PGMs from catalyst scraps can be developed utilizing this Fe deposition pretreatment.
36 MATERIALS SCIENCE↗
Influence of Laser Surface Texturing on Tribological Performance of Tool Steels
This paper deals with the influence of laser surface texturing on tribological performance of two different tool steels: (a) Böhler K100 produced by conventional production technology and (b) Böhler K390 Microclean{sup ®} produced by powder metallurgy. The surface of heat-treated tool steels was modified using three different texture patterns. Impact of laser surface texturing was analyzed after different treatments. Furthermore, selected samples were borided to evaluate the combined influence of laser surface texturing and boriding on tribological performance of surface-treated samples. The results show that boriding was not beneficial for wavy surface type, and the steel production technology had a certain influence on the spinning tool. The laser surface texturing had an effect on decreasing the coefficient of friction on the K100 tool steel; however, it did not influence the tribological performance of the K390 Microclean{sup ®} tool steel. Boriding process was efficient in decreasing the coefficient of friction for both steels. The low coefficient of friction values did not have a positive influence on the wear depth.
36 MATERIALS SCIENCE↗
Practical algorithms for multivariate rational approximation
We present two approaches for computing rational approximations to multivariate functions, motivated by their effectiveness as surrogate models for high-energy physics (HEP) applications. Our first approach builds on the Stieltjes process to efficiently and robustly compute the coefficients of the rational approximation. Our second approach is based on an optimization formulation that allows us to include structural constraints on the rational approximation (in particular, constraints demanding the absence of singularities), resulting in a semi-infinite optimization problem that we solve using an outer approximation approach. We present results for synthetic and real-life HEP data, and we compare the approximation quality of our approaches with that of traditional polynomial approximations.
97 MATHEMATICS AND COMPUTING↗
Anomalous diffusion of single metal atoms on a graphene oxide support
Recent studies of single-atom catalysts open up the prospect of designing exceptionally active and environmentally efficient chemical processes. The stability and durability of such catalysts is governed by the strength with which the atoms are bound to their support and their diffusive behaviour. Here we use aberration-corrected STEM to image the diffusion of single copper adatoms on graphene oxide. As a result, we discover that individual atoms exhibit anomalous diffusion as a result of spatial and energetic disorder inherent in the support, and interpret the origins of this behaviour to develop a physical picture for the surface diffusion of single metal atoms.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Modeling and analysis of synthetic liquid fuel production from CO 2 and nuclear energy using methanol-to-diesel process
Electrofuels (e-fuels) are synthetic fuels produced from carbon dioxide (CO 2 ) and electricity for blending with or replacing petroleum fuels. Nuclear energy is an attractive energy feedstock for e-fuel production because of its low environmental footprint and its ability to provide steady heat and power essential for e-fuels production. We modeled and evaluated the cost and environmental footprint of e-fuels production in the distillate range for three nuclear power scales, 100, 500, and 1000 MWe, through methanol and olefins intermediates leveraging commercial or high technology readiness level (TRL) processes. Compared to the commonly studied e-fuels from Fischer Tropsch process that has a distillate yield of <70% with the rest being low value naphtha, the proposed process via methanol intermediate increases the product selectivity with distillate yield of 96% and only 4% naphtha. The modeled process has a carbon conversion ratio of 98%, and a process energy efficiency of 56% relative to the total equivalent nuclear electricity input. The e-fuel plant economics and GHG emissions were estimated by considering CO 2 collected from ethanol plants adjacent to nuclear power plants. The estimated minimum fuel selling prices (MFSP) of e-fuel is in the range of $5.7-$9.1/gal depending on e-fuel plant scale, electricity cost, and CO 2 transportation distance. The corresponding e-fuels life cycle GHG emissions is estimated in the range of 5-6 gCO 2 e/MJ of liquid fuel using the R&D Greenhouse gases, Regulated Emissions, and Energy use in Technologies (R&D GREET) model.
10 SYNTHETIC FUELS↗
Transfer of microstructure pattern of CNTs onto flexible substrate using hot press technique for sensing applications
Graphical abstract: - Highlights: • Successfully transfer of microstructure patterned CNTs on PET substrate. • Demonstrate as resistor-based NH{sub 3} gas sensor in the sub-ppm range. • Excellent photodetector having instantaneous response and recovery characteristics. • An effective technique to grow and produce flexible electronic device. - Abstract: In this work, we report the successful and efficient transfer process of two- dimensional (2-D) vertically aligned carbon nanotubes (CNTs) onto polyethylene terephthalate (PET) substrate by hot pressing method with an aim to develop flexible sensor devices. Carbon nanotubes are synthesized by cold wall thermal chemical vapor deposition using patterned SiO{sub 2} substrate under low pressure. The height of the pattern of CNTs is controlled by reaction time. The entire growth and transfer process is carried out within 30 min. Strong adhesion between the nanotube and polyethylene terephthalate substrate was observed in the post-transferred case. Raman spectroscopy and scanning electron microscope (SEM) studies are used to analyze the microstructure of carbon nanotube film before and after hot pressing. This technique shows great potential for the fabrication of flexible sensing devices. We report for the first time, the application of patterned microstructure developed by this technique in the development of gas sensor and optoelectronic device. Surface resistive mode is used for detection of ammonia (NH{sub 3}) gas in the sub-ppm range. An impressive photoconducting response is also observed in the visible wavelength. The reproducibility of the sample was checked and the results indicate the possibility of use of carbon nanotube as gas sensor, photodetector, CCDs etc.
36 MATERIALS SCIENCE↗
Helical tomotherapy quality assurance with ArcCHECK
To design a quality assurance (QA) procedure for helical tomotherapy that measures multiple beam parameters with 1 delivery and uses a rotating gantry to simulate treatment conditions. The customized QA procedure was preprogrammed on the tomotherapy operator station. The dosimetry measurements were performed using an ArcCHECK diode array and an A1SL ion chamber inserted in the central holder. The ArcCHECK was positioned 10 cm above the isocenter so that the 21-cm diameter detector array could measure the 40-cm wide tomotherapy beam. During the implementation of the new QA procedure, separate comparative measurements were made using ion chambers in both liquid and solid water, the tomotherapy onboard detector array, and a MapCHECK diode array for a period of 10 weeks. There was good agreement (within 1.3%) for the beam output and cone ratio obtained with the new procedure and the routine QA measurements. The measured beam energy was comparable (0.3%) to solid water measurement during the 10-week evaluation period, excluding 2 of the 10 measurements with unusually high background. The symmetry reading was similarly compromised for those 2 weeks, and on the other weeks, it deviated from the solid water reading by ∼2.5%. The ArcCHECK phantom presents a suitable alternative for performing helical tomotherapy QA, provided the background is collected properly. The proposed weekly procedure using ArcCHECK and water phantom makes the QA process more efficient.
61 RADIATION PROTECTION AND DOSIMETRY↗
Multivariate analysis of gamma spectra to characterize used nuclear fuel
Abstract—The Multi-Isotope Process (MIP) Monitor provides an efficient approach to monitoring the process conditions in used nuclear fuel reprocessing facilities to support process verification and validation. The MIP Monitor applies multivariate analysis to gamma spectroscopy of reprocessing streams in order to detect small changes in the gamma spectrum, which may indicate changes in process conditions. This research extends the MIP Monitor by characterizing a used fuel sample after initial dissolution according to the type of reactor of origin (pressurized or boiling water reactor), initial enrichment, burn up, and cooling time. Simulated gamma spectra were used to develop and test three fuel characterization algorithms. The classification and estimation models employed are based on the partial least squares regression (PLS) algorithm. A PLS discriminate analysis model was developed which perfectly classified reactor type. Locally weighted PLS models were fitted on-the-fly to estimate continuous fuel characteristics. Burn up was predicted within 0.1% root mean squared percent error (RMSPE) and both cooling time and initial enrichment within approximately 2% RMSPE. This automated fuel characterization can be used to independently verify operator declarations of used fuel characteristics and inform the MIP Monitor anomaly detection routines at later stages of the fuel reprocessing stream to improve sensitivity to changes in operational parameters and material diversions.
Multivariate Analysis for Characterization of Used↗
A novel approach for critical heat flux enhancement during severe accident mitigation with removal of radioactive materials from the coolant
In this paper, a new system, which consists of mature and proven technologies, is suggested for simultaneous objectives in nuclear power plants: CHF enhancement and effective decontamination. It consists of multifunctional magnetic nanoparticles and a collector part. CHF enhancement for severe accident mitigation strategies like IVR-ERVC and core catcher is expected along with an efficient decontamination process of target radioactive nuclides, and through the collector part, where external magnetic fields are applied, working fluid can be effectively purified. The multifunctional magnetic nanoparticle possesses potentials to severe accident scenarios based on its distinct characteristics. Also, a nanofluid system is strongly affected by environments and state of the immersed particles; the CHF enhancement can be stably achieved in real applications with proper consideration and optimization.
Kam, Dong Hoon↗
Adaptive ensemble simulations of biomolecules
Recent advances in both theory and computational power have created opportunities to simulate biomolecular processes more efficiently using adaptive ensemble simulations. Ensemble simulations are now widely used to compute a number of individual simulation trajectories and analyze statistics across them. Adaptive ensemble simulations offer a further level of sophistication and flexibility by enabling highlevel algorithms to control simulations-based on intermediate results. We review some of the adaptive ensemble algorithms and software infrastructure currently in use and outline where the complexities of implementing adaptive simulation have limited algorithmic innovation to date. In conclusion, we describe an adaptive ensemble API to overcome some of these barriers and more flexibly and simply express adaptive simulation algorithms to help realize the power of this type of simulation.
97 MATHEMATICS AND COMPUTING↗
Optimal design of phase change material storage for steam production using annual simulation
A direct steam generation (DSG) solar collector can be an efficient process-heat application compared to electricity generation, and it can significantly reduce dependence on non-renewable energy sources for steam generation. Due to intermittency of the sun, thermal energy storage is required to increase the capacity factor or the yearly utilization of the system. For this study, phase change material (PCM) is used to store the heat from the steam produced in the solar collector. Sodium formate is selected as the PCM material on a cost basis. A detailed off-design analysis is carried to predict the annual performance of the system. Fins are used to enhance the thermal performance of the PCM, and an simplified method is derived to predict the required fin mass. With an increase in the number of fins, the thermal performance of the system increases significantly at design point. Furthermore the fins are expensive, so an annual simulation and techno-economic analysis is carried to calculate the optimal number of fins and other operating parameters.
14 SOLAR ENERGY↗
Metabolite damage and repair in metabolic engineering design
The necessarily sharp focus of metabolic engineering and metabolic synthetic biology on pathways and their fluxes has tended to divert attention from the damaging enzymatic and chemical side-reactions that pathway metabolites can undergo. Although historically overlooked and underappreciated, such metabolite damage reactions are now known to occur throughout metabolism and to generate (formerly enigmatic) peaks detected in metabolomics datasets. It is also now known that metabolite damage is often countered by dedicated repair enzymes that undo or prevent it. Metabolite damage and repair are highly relevant to engineered pathway design: metabolite damage reactions can reduce flux rates and product yields, and repair enzymes can provide robust, host-independent solutions. Herein, after introducing the core principles of metabolite damage and repair, we use case histories to document how damage and repair processes affect efficient operation of engineered pathways - particularly those that are heterologous, non-natural, or cell-free. We then review how metabolite damage reactions can be predicted, how repair reactions can be prospected, and how metabolite damage and repair can be built into genome-scale metabolic models. Lastly, we propose a versatile 'plug and play' set of well-characterized metabolite repair enzymes to solve metabolite damage problems known or likely to occur in metabolic engineering and synthetic biology projects.
Enzyme promiscuity↗
Examining the Influence of Silver(I) Ion Coordination Environment in Ionic Liquids on Olefin–Paraffin Separations using Inverse Gas Chromatography
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Tryon-Tasson, Nicholas↗
Electrochemical Random-Access Memory: Progress, Perspectives, and Opportunities
Non-von Neumann computing using neuromorphic systems based on analogue synaptic and neuronal elements has emerged as a potential solution to tackle the growing need for more efficient data processing, but progress toward practical systems has been stymied due to a lack of materials and devices with the appropriate attributes. Recently, solid state electrochemical ion-insertion, also known as electrochemical random access memory (ECRAM) has emerged as a promising approach to realize the needed device characteristics. ECRAM is a three terminal device that operates by tuning electronic conductance in functional materials through solid-state electrochemical redox reactions. This mechanism can be considered as a gate-controlled bulk modulation of dopants and/or phases in the channel. Early work demonstrating that ECRAM can achieve nearly ideal analogue synaptic characteristics has sparked tremendous interest in this approach. More recently, the realization that electrochemical ion insertion can be used to tune the electronic properties of many types of materials including transition metal oxides, layered two-dimensional materials, organic and coordination polymers, and that the changes in conductance can span orders of magnitude has further attracted interest in ECRAM as the basis for analogue synaptic elements for inference accelerators as well as for dynamical devices that can emulate a wide range of neuronal characteristics for implementation in analogue spiking neural networks. At its core, ECRAM shares many fundamental aspects with rechargeable batteries, where ion insertion materials are used extensively for their ability to reversibly store charge and energy. Computing applications, however, present drastically different requirements: systems will require many millions of devices, scaled down to tens of nanometers, all while achieving reliable electronic-state tuning at scaled-up rates and endurances, and with minimal energy dissipation and noise. Further, in this review, we discuss the history, basic concepts, recent progress, as well as the challenges and opportunities for different types of ECRAM, broadly grouped by their primary mobile ionic charge carrier, including Li, protons, and oxygen vacancies.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗