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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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At least 1,603 records · Page 89
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Scalable Substitutional Re‐Doping and its Impact on the Optical and Electronic Properties of Tungsten Diselenide

Abstract Reliable, controlled doping of 2D transition metal dichalcogenides will enable the realization of next‐generation electronic, logic‐memory, and magnetic devices based on these materials. However, to date, accurate control over dopant concentration and scalability of the process remains a challenge. Here, a systematic study of scalable in situ doping of fully coalesced 2D WSe 2 films with Re atoms via metal–organic chemical vapor deposition is reported. Dopant concentrations are uniformly distributed over the substrate surface, with precisely controlled concentrations down to <0.001% Re achieved by tuning the precursor partial pressure. Moreover, the impact of doping on morphological, chemical, optical, and electronic properties of WSe 2 is elucidated with detailed experimental and theoretical examinations, confirming that the substitutional doping of Re at the W site leads to n‐type behavior of WSe 2 . Transport characteristics of fabricated back‐gated field‐effect‐transistors are directly correlated to the dopant concentration, with degrading device performances for doping concentrations exceeding 1% of Re. The study demonstrates a viable approach to introducing true dopant‐level impurities with high precision, which can be scaled up to batch production for applications beyond digital electronics.

Kozhakhmetov, Azimkhan↗
DOE OSTI2021

Ionic liquid-water mixtures enhance pretreatment and anaerobic digestion of agave bagasse

Agave bagasse (AB), a byproduct of tequila production, is a waste generated in large quantities and an emerging alternative for biofuels production. Nevertheless, the use of lignocellulosic biomass for this purpose requires a pretreatment that maximizes its degradation and utilization. Although there are several pretreatment types, using ionic liquids (IL) has become attractive due to its ability to dissolve the lignocellulosic biomass under mild conditions of time and temperature. As a drawback are the high cost of IL's and their high viscosity; thus mixing them with water is a way to overcome these hindrances. This work aimed to evaluate the effect of pretreatment with three diluted ILs on the A. tequilana bagasse structure and sugars production, as well as the potential of the enzymatic hydrolysate to produce methane in batch mode. The evaluated ILs were: 1-ethyl-3-methylimidazolium acetate [Emim][OAc], choline lysinate [Ch][Lys] and ethanolamine acetate [EOA][OAc]. The results showed that the IL with the best performance was [Ch][Lys], which not only offered the highest yields of sugar production (0.57 ± 0.03 g total sugars / g bagasse) but also, it is possible to use it at 30 % in a mix with water obtaining similar yields as with pure IL. Enzymatic hydrolysis of IL pretreated AB achieved 50.7 kg sugars and 49.3 kg of sugars for 90 %-[Ch][Lys] and 30 %-[Ch][Lys], respectively per 100 kg of untreated biomass. The enzymatic hydrolysate from the 30 %-[Ch][Lys] pretreated AB was able to achieve 0.28 L CH4/g CODfed, demonstrating that both sugar and methane yields are maintained when pure or 30 %-[Ch][Lys] are used for pretreatment, representing a step forward towards process feasibility.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Core Design Optimization of the Westinghouse Lead Fast Reactor

Westinghouse is pursuing an advanced Nuclear Power Plant design based on Lead Fast Reactor (LFR) technology for global commercialization. To achieve an optimal combination of key attributes, such as safety, sustainability, and economic competitiveness, Westinghouse and ANL partnered in developing and applying a formalized core design optimization strategy. An LFR analysis workflow was developed to automate a suite of reactor physics, fuels performance, safety, and economics simulations on a selected LFR concept. The workflow streamlines analysis of a wide range of LFR designs with different dimensions and fuel types to assess their viability and economic performance, significantly reducing human processing time and risks of processing errors. The LFR optimization exercise was defined, resulting in selection of the design constraints (geometric, neutronics, thermo-mechanical, safety, thermal-hydraulics, and economics) and performance metrics researched (minimization of both the fuels LCOE and the first core inventory cost). A total of 14 varied design parameters were considered, including assembly dimensions, coolant temperature, and enrichment distribution throughout the core. The LFR analysis workflow was connected to DAKOTA for sensitivity and optimization analyses. Due to the extremely large size of the potential LFR optimization solution space relative to the computing time required to characterize one LFR solution, a multi-stage optimization approach was proposed to breakdown the problem into several stages with more reasonable sizes. This optimization approach enabled finding various viable core solutions with different cost tradeoffs that were considered by Westinghouse and justify selection of a smaller core with multi-batch 2-year cycle length.

Stauff, Nicolas E.↗
DOE OSTI2023

Butyric Acid Production from Delignified Corn Stover Using Thermophilic Bacterial Co-Cultures

Butyric acid (BA) is a valuable platform chemical in the food and pharmaceutical industries, and it is also a potential precursor for the production of biobutanol and sustainable aviation fuels (SAFs). BA is mainly synthesized from petroleum; thus, cost-effective, and sustainable alternatives for its production are attracting the interest of several sectors. The present work proposes a solids-to-acids bioprocess to produce BA from corn stover utilizing a co-culture that consists of two thermophilic bacteria, Clostridium thermocellum, a well-known efficient degrader of insoluble and oligomeric cellulosic substrates, and Clostridium thermobutyricum, a highly efficient BA producer from monomeric sugars. After initial proof of concept experiments, a series of optimization studies were carried out to evaluate the process limits of this co-culture. First, the co-cultivation of both microorganisms at different inoculum sizes in deacetylated and mechanically refined corn stover (DMR) was evaluated. No significant differences were found on the solids deconstruction and carbohydrates utilization among all the treatments. In addition, BA production was similar under all conditions, ranging between 2.1 and 2.4 g/L. Next, the deconstruction, and BA production capabilities of the co-culture at increased DMR solids contents (3, 4.5, and 6% (w/v)) were tested. Although no difference was observed in the solids deconstruction and carbohydrates utilization among treatments, BA production increased concomitantly to solids loading; the maximum values observed were 2.8, 3.6, and 6.2 g/L in the 3, 4.5, and 6% treatments, respectively. In fact, BA production did not reach its absolute maximum in the 6% treatment after 160 h of fermentation. Lastly, a fed-batch experiment was performed to investigate the co-culture capabilities and possible system constraints to achieve higher BA titers. Data on substrate modifications and product formation as well as on the growth of each microorganism will be shown. Results from this work demonstrate a promising bioprocess approach for the production of BA from lignocellulosic biomass using a thermophilic bacterial co-culture.

bacteria↗
DOE OSTI2023

Iodine Removal from Carbonate-Containing Alkaline Liquids Using Strong Base Resins, Hybrid Resins, and Silver Precipitation

The ability of several material types to remove aqueous iodine from a mildly alkaline, carbonate-rich nuclear waste stream was evaluated: strong base anion exchange resins (SBAR), hybrid resins, Ag-containing materials and Bi-containing hybrid resins. A combination of batch testing and flow through column testing were used in the evaluation. In batch testing, hybrid resins CHM-20, SIR-110-CE and RTBI were shown to have high efficiency for the removal of both iodide and iodate simultaneously, while Ag-containing materials and SBAR demonstrated high capacity for iodide removal. One example of each material type (CHM-20, A532E and Ionex 400) were further evaluated for their sorption isotherms and column performance. The Langmuir isotherm, or a Langmuir-Freundlich hybrid isotherm, best described the sorption of iodide to the CHM-20 hybrid resin and Purolite A532E. The Freundlich isotherm best described the uptake of iodate to CHM-20 and A532E and for both iodide and iodate to the Ag-containing Ionex-400. In column testing the Purolite A532E had exceptional performance for overall iodide removal. With the capacity demonstrated the A532E resin would exceed Class C waste classification before breakthrough initiated, and column change outs in processing would be dictated by eventual waste classification, not breakthrough. The Ionex 400, a Ag-zeolite, was observed to degrade over time in the column in the mild alkaline conditions whereas the hybrid CHM-20 was limited in the single pass through design and would be best suited for applications where iodide and iodate are present and recirculation of the column effluent is feasible. Here this work highlights the feasibility of commercially available materials to separate radioiodine from liquid environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

DIissolution of low enriched uranium from the experimental breeder reactor-II fuel stored at the Idaho National Laboratory

The Idaho National Laboratory (INL) is actively engaged in the development of electrochemical processing technology for the treatment of fast reactor fuels using irradiated fuel from the Experimental Breeder Reactor-II (EBR-II) as the primary test material. The research and development (R&D) activities generate a low enriched uranium (LEU) metal product from the electrorefining of the EBR-II fuel and the subsequent consolidation and removal of chloride salts by the cathode processor. The LEU metal ingots from past R&D activities are currently stored at INL awaiting disposition. One potential disposition pathway is the shipment of the ingots to the Savannah River Site (SRS) for dissolution in H-Canyon. Carbon steel cans containing the LEU metal would be loaded into reusable charging bundles in the H-Canyon Crane Maintenance Area and charged to the 6.4D or 6.1D dissolver. The LEU dissolution would be accomplished as the final charge in a dissolver batch (following the dissolution of multiple charges of spent nuclear fuel (SNF)). The solution would then be purified and the 235 U enrichment downblended to allow use of the U in commercial reactor fuel. To support this potential disposition path, the Savannah River National Laboratory (SRNL) developed a dissolution flowsheet for the LEU using samples of the material received from INL.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Hydrotreatment of Nylon 66 and Amide Model Compounds Over Sulfided NiMo Catalysts

Molybdenum sulfide-based catalysts, such as nickel–molybdenum on alumina (NiMoS x /Al 2 O 3 ), are widely used in hydrotreating and have potential for catalyzing waste plastic conversion via hydrogenolysis, yet their performance, such as reaction kinetics and network, for amide-rich polymer feeds is poorly defined. Here we combine Nylon 66 with the amide model compound, N,N-dibutylhexanediamide (DBDAD), to quantify hydrodeoxygenation (HDO) and hydrodenitrogenation (HDN) chemistry in a stirred batch reactor (53 bar H 2 , 280–320°C). DBDAD conversion is near-linear with time, indicating strong adsorption of the substrates on the active sites. Time-resolved product identification indicates parallel C─O first-cleavagedeoxygenation (DO) and C─N first-cleavagedenitrogenation (DN) sequences proceeding through amine and diol intermediates, respectively, to C 4 ─C 6 alkanes. Increasing temperature shifts selectivity toward DN, decreasing the initial r(DO)/r(DN) from 1.38 (280°C) to 0.69 (320°C), with an apparent activation energy of 173 kJ mol −1 for DBDAD conversion. At 300°C, nylon 66 converts faster than DBDAD, producing a complex mixture of oxygen- and nitrogen-containing species and an initial rate ratio r(DO)/r(DN) of 1.6. No heteroaromatic nitrogen products are detected by the method used. These results provide reaction pathways and product signatures relevant to hydro-processing catalysts exposed to polyamide-derived streams.

Nylon 66↗
DOE OSTI2021

Micrometer-sized Magnetite Synthesis using Fe(OH)2(s) as a Precursor for Technetium Sequestration from Liquid Nuclear Waste Streams

Systematic batch experiments under variable adjusted physicochemical conditions were conducted to explore optimization of micrometer-sized magnetite synthesis for Tc sequestration from radionuclide waste streams using Fe(OH)2(s) as the precursor. Extensive solid characterization using x-ray diffraction and spectroscopic methods was performed to assess changes in particle morphology and size distribution, as well as Tc speciation and incorporation, in the produced mineral phases. The results show that the solution pH, temperature, and oxidation kinetics play key roles in the final mineral products. Micrometer-sized magnetite crystals (0.62-0.96 µm on average) with well-defined dodecahedral or octahedral structures were synthesized under near neutral (~pH 8) or alkaline (~pH13) conditions at 75 °C, respectively; whereas goethite dominated the end products at room temperature. An increase in pH at 75 °C improved Tc removal from 27% (near neutral pH) to 42% (alkaline pH), but the removal process remained inhibited by redox competitive Cr(VI) present in the waste streams. By adding additional Fe(II) to the system, Tc sequestration was dramatically improved to up to 87% without observable changes in the solid product. The sequestrated Tc existed as TcO2·2H2O and/or Tc(IV) incorporated into magnetite, where extended X-ray absorption fine structure (EXAFS) spectroscopy showed that more Tc was incorporated into magnetite at elevated temperatures and pH conditions, with complete Tc(IV) incorporation into magnetite occurring under 75 °C-pH 13 conditions. Our results indicate that optimal micrometer-sized magnetite can be produced for Tc sequestration by reacting Fe(OH)2(s) with a waste stream simulant under elevated pH (~13) and temperature (75 °C) conditions. The incorporation of reduced Tc(IV) into stable micrometer-sized magnetite provides a viable supplemental immobilizing technology that may be used to improve nuclear waste treatment and disposal needs.

Wang, Guohui↗
DOE OSTI2024

A novel conditional generative model for efficient ensemble forecasts of state variables in large-scale geological carbon storage

Integrating monitoring data to efficiently update reservoir pressure and CO 2 plume distribution forecasts presents a significant challenge in geological carbon storage (GCS) applications. Inverse modeling techniques are commonly used to fuse observational data and refine reservoir model parameters, thereby improving state variable forecasts. However, these techniques often rely on linear or Gaussian assumptions, which can limit their effectiveness in accurately predicting state variables. Moreover, simulating large-scale three-dimensional (3D) GCS problems is computationally expensive, making iterative runs in inverse problems prohibitive. To address these challenges, we propose a conditional generative model utilizing the score-based diffusion method for real-time 3D pressure and saturation field distribution predictions. Our approach involves solving the score function with a mini-batch-based Monte Carlo estimator to generate labeled data. This data is subsequently employed to train a fully connected neural network, enabling it to learn the conditional sample generator within a supervised learning framework. This method enables the rapid generation of a large ensemble of predictions, facilitating comprehensive uncertainty quantification of state variables. Here we applied our method to forecast the dynamic 3D distributions of pressure and saturation fields over a 30-year injection period. The statistical assessment with low root mean square error (RMSE) values demonstrates that our method can accurately predict the spatiotemporal distributions of both pressure and saturation fields. Moreover, the developed conditional generative model shows high computational efficiency by generating 100 ensemble forecasts of 3D state variables in less than 10 min. The consistency between ensemble averages and ground truth values further illustrates the model’s capability to capture state variable dynamics during the CO 2 plume injection process. Notably, the ground truth values fall within the ensemble forecasts, indicating that our uncertainty quantification effectively captures variability and potential noise in the observations. Thus, the developed conditional generative model proves to be a more efficient, accurate, and practical tool for GCS applications, facilitating timely risk analysis and informed decision-making.

58 GEOSCIENCES↗
NASA NTRS2019

Agile Approach to Assuring the Safety-Critical Embedded Software for NASA's Orion Spacecraft

Human-rated missions like those in NASA's Orion Program continue to grow in complexity. The role of software in achieving ambitious mission objectives has expanded dramatically in the last few decades. Assuring the safety and performance of the embedded flight software is quickly growing beyond the reach of traditional methods and resource levels. The methods used to build these software-dominant systems evolve in an on-going attempt to keep pace with the scope of our ambitions. Agile software development is now commonplace. The long timelines and large batches of work associated with traditional methods are being replaced by rapid delivery of small increments _ as system capabilities are realized in waves. Assurance of these critical software capabilities must therefore conquer an ever-expanding frontier of challenges, and do so with an approach matched to the evolving development methods. This paper recounts the journey of the Orion Independent Verification and Validation (IV&V) team as we addressed this dynamic environment. Widening our aperture to encompass a dramatically larger mission scope, while adjusting our cadence to synchronize with the rapid pace of agile software development, a new approach to IV&V is emerging. This approach is characterized by a sharper focus on mission capabilities, matched with a method to dynamically _follow the risk' as the IV&V team delivers more compelling assurance data in waves. Traditional methods prevalent in IV&V tend to scope the work using artifacts of the development process as they evolve from preliminary to final versions, and the pace of delivery was synchronized with the development timelines prevalent in the waterfall lifecycle. That more static approach is out of phase with the demands of the new environment. Scoping work according to the critical capabilities of the system (rather than artifacts of development) and synchronizing with the rapid pace of agile development, we are moving toward more effective parity with the demands of the environment. We explain the concrete steps we took, the principles that motivated our choices, and the results we have achieved to date.

Capability based assurance↗
DOE OSTI2026

Hydrogen production from full-strength corn stover fermentation effluent in single-chamber replaceable-cathode microbial electrolysis cells

Lignocellulosic residual biomass generated by the agricultural sector is an abundant feedstock for biohydrogen production via dark fermentation. However, this process is intrinsically inefficient, converting only ~30% of the reductant energy into H2 and leaving substantial amounts of reduced byproducts. These byproducts, mostly found in the fermentation effluents, can be further valorized in microbial electrolysis cells (MECs) to enhance the overall H2 recovery. However, current MEC configurations are typically dual- or single-chamber systems, yet both suffer from key inefficiencies. Dual-chamber systems rely on proton exchange membranes that are costly and prone to rapid biofouling, whereas single-chamber, membraneless systems are limited by reduced productivity due to H2 recycling and methanogenic consumption In this study, three single-chamber, 50-mL replaceable-cathode microbial electrolysis cells (RC-MECs) were 3D-printed and equipped with a physical separator to isolate anode and cathode compartments and limit H2 migration. Full-strength milled corn stover (MCS) fermentation effluent (COD of ~23.8 g-COD/L) was treated in fed-batch mode over two operational periods spanning 21 (Run 1) and 80 (Run 2) days. The RC-MECs exhibited comparable performance in both runs: after biofilm maturation, current densities exceeded 100 A/m²_cathode, COD removal reached up to 43%. Notably, extended RC-MECs operation led to a substantial methanogenic activity with the CH4 fraction in the cathode gas increasing to as high as 80% of the total biogas. Additions of a methanogenesis inhibitor 2-bromoethanesulfonate (2-BES) produced transient increases in hydrogen yields (11.51 and 5.12 L-H2/L_reactor/day in Runs 1 and 2, respectively); however, sustained 2-BES addition in subsequent cycles reduced total biogas production, decreased COD removal, and led to volatile fatty acid accumulation. Overall, single-chamber MECs can treat high-strength dark fermentation effluents while improving H2 recovery, but methanogenesis remains a key bottleneck, and complete long-term inhibition may be operationally unsustainable.

Hydrogen Production↗
DOE OSTI2020

Selective sulfur removal from semi-dry flue gas desulfurization coal fly ash for concrete and carbon dioxide capture applications

High-sulfur mixed fly ash residues from semi-dry flue gas desulfurization units in coal-fired power plants are unsuitable for use as supplementary cementitious material (SCM) for concrete production or carbon dioxide utilization. In this work, we explore the potential for upcycling a representative spray dry absorber ash (10.44 wt% SO 3 ) into concrete-SCM by selective sulfur removal via weak acid dissolution while simultaneously exploring the possibility for CO 2 capture. Towards this effort, parametric studies varying liquid-to-solid ratio, acidity, and CO 2 pressure were conducted in a batch reactor to establish the sulfur removal characteristics in de-ionized water, nitric acid, and carbonic acid, respectively. The dissolution studies show that the leaching of sulfur from calcium sulfite hemihydrate, which is the predominant S phase, is rapid and achieves a concentration plateau within 5 min, and subsequently, appears to be controlled by the primary mineral solubility. Here, preferential S removal was sufficient to meet SCM standards (e.g., 5.0 wt% as per ASTM C618) using all three washing solutions with 0.62–0.72 selectivity (S^), defined as the molar ratio of S to Ca in the leachate, for a raw fly ash with bulk S^ = 0.3. Acid dissolution with 1.43 meq/g of ash or under 5 atm CO 2 retained > 18 wt% CaO and other Si-, Al-rich phases in the fly ash. Based on the experimental findings, two sulfur removal schemes were suggested for either integration with CO 2 capture and utilization processes using flue gas or to produce fly ash for use as a SCM.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2016

INTEGRATION OF PANDA WORKLOAD MANAGEMENT SYSTEM WITH SUPERCOMPUTERS

Abstract The Large Hadron Collider (LHC), operating at the international CERN Laboratory in Geneva, Switzerland, is leading Big Data driven scientific explorations. Experiments at the LHC explore the funda- mental nature of matter and the basic forces that shape our universe, and were recently credited for the dis- covery of a Higgs boson. ATLAS, one of the largest collaborations ever assembled in the sciences, is at the forefront of research at the LHC. To address an unprecedented multi-petabyte data processing challenge, the ATLAS experiment is relying on a heterogeneous distributed computational infrastructure. The ATLAS experiment uses PanDA (Production and Data Analysis) Workload Management System for managing the workflow for all data processing on over 140 data centers. Through PanDA, ATLAS physicists see a single computing facility that enables rapid scientific breakthroughs for the experiment, even though the data cen- ters are physically scattered all over the world. While PanDA currently uses more than 250000 cores with a peak performance of 0.3+ petaFLOPS, next LHC data taking runs will require more resources than Grid computing can possibly provide. To alleviate these challenges, LHC experiments are engaged in an ambitious program to expand the current computing model to include additional resources such as the opportunistic use of supercomputers. We will describe a project aimed at integration of PanDA WMS with supercomputers in United States, Europe and Russia (in particular with Titan supercomputer at Oak Ridge Leadership Com- puting Facility (OLCF), Supercomputer at the National Research Center Kurchatov Institute , IT4 in Ostrava, and others). The current approach utilizes a modified PanDA pilot framework for job submission to the supercomputers batch queues and local data management, with light-weight MPI wrappers to run single- threaded workloads in parallel on Titan s multi-core worker nodes. This implementation was tested with a variety of Monte-Carlo workloads on several supercomputing platforms. We will present our current accom- plishments in running PanDA WMS at supercomputers and demonstrate our ability to use PanDA as a portal independent of the computing facility s infrastructure for High Energy and Nuclear Physics, as well as other data-intensive science applications, such as bioinformatics and astro-particle physics.

De, K↗
DOE OSTI2018

Explicitly Accounting for Multiple Spatial Scales in Data Informing Kd Distribution Development - 18414

This work provides an example of incorporating information about spatial scale into input parameter distribution development for probabilistic performance assessment (PA) models and highlights the importance of having an interdisciplinary team working together in the distribution development process. The novel approach is demonstrated for contaminant partitioning coefficients for water/rock (Kds), providing a specific context for discussing the approach and challenges, but the strategy is general and applies to many other PA model inputs. In this example, a PA model of a radioactive waste disposal site is assumed to have large cells representing spatial scales of up to thousands of square meters in area and several to tens of meters in depth. Spatial variability in Kds is expected to occur at scales much smaller than the units in the model domain over which values are applied, and therefore values are intended to represent possible averages over the modeled volume (i.e., spatial scale represented by a PA model cell). Information about possible Kd values for each material category comes from a variety of literature sources, and the reported results used to inform the distribution are available at a wide range of scales (e.g., individual batch experiment results from small-scale samples, averages based on samples collected over site-scales, averages based on samples from large regions, etc.). Effectively addressing the mismatch in spatial scale between available information and the PA Model is a challenge within PA distribution development and it takes effort from database managers, subject matter experts, modelers, and statisticians. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2014

New generation NMR bioreactor coupled with high-resolution NMR spectroscopy leads to novel discoveries in Moorella thermoaceticum metabolic profiles

An in-situ nuclear magnetic resonance (NMR) bioreactor was developed and employed to monitor microbial metabolism under batch-growth conditions in real time. We selected Moorella thermoacetica ATCC 49707 as a test case. M. thermoacetica (formerly Clostridium thermoaceticum) is a strictly anaerobic, thermophilic, acetogenic, gram-positive bacterium with potential for industrial production of chemicals. The metabolic profiles of M. thermoacetica were characterized during growth in batch mode on xylose (a component of lignocellulosic biomass) using the new generation NMR bioreactor in combination with high-resolution, high sensitivity NMR (HR-NMR) spectroscopy. In-situ NMR measurements were performed using water-suppressed H-1 NMR spectroscopy at an NMR frequency of 500 MHz, and aliquots of the bioreactor contents were taken for 600 MHz HR-NMR spectroscopy at specific intervals to confirm metabolite identifications and expand metabolite coverage. M. thermoacetica demonstrated the metabolic potential to produce formate, ethanol and methanol from xylose, in addition to its known capability of producing acetic acid. Real-time monitoring of bioreactor conditions showed a temporary pH decrease, with a concomitant increase in formic acid during exponential growth. Fermentation experiments performed outside of the magnet showed that the strong magnetic field employed for NMR detection did not significantly affect cell metabolism. Use of the in-situ NMR bioreactor facilitated monitoring of the fermentation process in real time, enabling identification of intermediate and end-point metabolites and their correlation with pH and biomass produced during culture growth. Real-time monitoring of culture metabolism using the NMR bioreactor in combination with the HR-NMR spectroscopy will allow optimization of the metabolism of microorganisms producing valuable bioproducts.

Bioproducts↗
DOE OSTI2016

Integration Of PanDA Workload Management System With Supercomputers for ATLAS and Data Intensive Science

The Large Hadron Collider (LHC), operating at the international CERN Laboratory in Geneva, Switzerland, is leading Big Data driven scientific explorations. Experiments at the LHC explore the fundamental nature of matter and the basic forces that shape our universe, and were recently credited for the discovery of a Higgs boson. ATLAS, one of the largest collaborations ever assembled in the sciences, is at the forefront of research at the LHC. To address an unprecedented multi-petabyte data processing challenge, the ATLAS experiment is relying on a heterogeneous distributed computational infrastructure. The ATLAS experiment uses PanDA (Production and Data Analysis) Workload Management System for managing the workflow for all data processing on over 150 data centers. Through PanDA, ATLAS physicists see a single computing facility that enables rapid scientific breakthroughs for the experiment, even though the data centers are physically scattered all over the world. While PanDA currently uses more than 250,000 cores with a peak performance of 0.3 petaFLOPS, LHC data taking runs require more resources than Grid computing can possibly provide. To alleviate these challenges, LHC experiments are engaged in an ambitious program to expand the current computing model to include additional resources such as the opportunistic use of supercomputers. We will describe a project aimed at integration of PanDA WMS with supercomputers in United States, Europe and Russia (in particular with Titan supercomputer at Oak Ridge Leadership Computing Facility (OLCF), MIRA supercomputer at Argonne Leadership Computing Facilities (ALCF), Supercomputer at the National Research Center Kurchatov Institute , IT4 in Ostrava and others). Current approach utilizes modified PanDA pilot framework for job submission to the supercomputers batch queues and local data management, with light-weight MPI wrappers to run single threaded workloads in parallel on LCFs multi-core worker nodes. This implementation was tested with a variety of Monte-Carlo workloads on several supercomputing platforms for ALICE and ATLAS experiments and it is in full production for the ATLAS experiment since September 2015. We will present our current accomplishments with running PanDA WMS at supercomputers and demonstrate our ability to use PanDA as a portal independent of the computing facilities infrastructure for High Energy and Nuclear Physics as well as other data-intensive science applications, such as bioinformatics and astro-particle physics.

Data-intensive science↗