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At least 1,423 records · Page 79

Evaluation of non-invasive biomonitoring of 2,4-Dichlorophenoxyacetic acid (2,4-D) in saliva

The objective of this study was to evaluate the potential for noninvasive biomonitoring of 2,4-dichlorophenoxyacetic acid (2,4-D) in saliva. Using an in vitro rat salivary gland epithelial cell (SGEC) system, a collection of experiments investigating chemical protein binding, temporal and directional transport, as well as competitive transport with para-aminohippuric acid (PAH), a substrate for renal organic anion transporters, was conducted to identify cellular transport parameters required to computationally model salivary transport of 2,4-D. Additionally, a physiological protein gradient was implemented to mimic physiologically relevant concentrations of protein in rat plasma and saliva, and under these conditions the transfer of 2,4-D was markedly slower, driven by increased protein binding (i.e. reduced free 2,4-D species available to cross salivary barrier). The rate of transfer was directly proportional to the amount of unbound 2,4-D and demonstrated no indication of active transport. An in vivo assessment of 2,4-D exposure in rats revealed a non-linear protein binding response in plasma, indicating saturated protein binding and increased levels of free 2,4-D species at higher doses. A strong correlation between concentrations in saliva and free unbound species in plasma was observed (Pearson correlation coefficient = 0.95). Saliva:plasma 2,4-D ratios measured in vivo (0.0079) were comparable over dose, but significantly different than ratios measured in vitro (physiological conditions) (0.034), possibly due to 2,4-D concentrations in saliva not being at equilibrium with 2,4-D concentrations in blood, as well as physiological features absent in in vitro settings (e.g. blood flow). We demonstrated that 2,4-D is consistently transported into saliva using both in vitro and in vivo models, making 2,4-D a potential candidate for human non-invasive salivary biomonitoring. Further work is needed to understand whether current sensor limits of detection are sufficient to measure occupationally relevant exposures.

Carver, Zana A.↗

Overview of Nuclear Integration Activities for Mitigation of Radiation Loads to ITER Superconducting Magnets

The Nuclear Integration Unit (NIU) is a trans-departmental team from the ITER Organization and Domestic Agencies, responsible for all nuclear integration aspects of the facility and for ensuring that systems and components are suitable for their radiation environment and satisfy all related performance requirements. This is a very challenging task namely due to the large number of systems, their still evolving designs, the intricate and far-reaching impacts of these in nuclear responses everywhere, and the complex world-wide distribution of procurement responsibilities. A sound systems engineering approach that involves all relevant experts and stakeholders, and trades-off between different performance requirements in an optimum way, needs to be taken and sustained during design evolution and construction, always with the objective of final overall project success. One of the most important current occupations of the NIU is the evaluation of, and protection from, radiation conditions to superconducting magnets during plasma operations, and particularly nuclear heating. This requires neutronic analyses in massive computer resources, with state-of-the-art methods and complex, extensive computer models. The main ITER superconducting magnet systems subject to significant nuclear loads are the toroidal field coils (TFCs) and the poloidal field coils (PFCs). These are illustrated in Fig. 1. Nuclear responses in these depend mostly on the design of all in-vessel (blankets, manifolds, divertor, in-vessel coils, port plugs), vessel and thermal shield components. Sources to consider are the 500 MW DT burning plasma (14.1 MeV neutrons) and the activated water in the in-vessel cooling system (photons up to 7 MeV from N-16 and neutrons up to 3.5 MeV from N-17). This paper discusses a snapshot of the present understanding of nuclear heat conditions in both the TFC and PFC magnets. This includes integral values and distributions, as well as best estimates from computations and conservative upper estimates by consideration of systematic effects and random uncertainties. The computer models, methods and assumptions used for evaluation of these responses are described. Nuclear integration aspects and ongoing efforts to study and implement additional shielding and other mitigating measures are also discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

An integrated approach for the knowledge discovery in computer simulation models with a multi-dimensional parameter space

In production industries, parameter identification, sensitivity analysis and multi-dimensional visualization are vital steps in the planning process for achieving optimal designs and gaining valuable information. Sensitivity analysis and visualization can help in identifying the most-influential parameters and quantify their contribution to the model output, reduce the model complexity, and enhance the understanding of the model behavior. Typically, this requires a large number of simulations, which can be both very expensive and time consuming when the simulation models are numerically complex and the number of parameter inputs increases. There are three main constituent parts in this work. The first part is to substitute the numerical, physical model by an accurate surrogate model, the so-called metamodel. The second part includes a multi-dimensional visualization approach for the visual exploration of metamodels. In the third part, the metamodel is used to provide the two global sensitivity measures: i) the Elementary Effect for screening the parameters, and ii) the variance decomposition method for calculating the Sobol indices that quantify both the main and interaction effects. The application of the proposed approach is illustrated with an industrial application with the goal of optimizing a drilling process using a Gaussian laser beam.

97 MATHEMATICS AND COMPUTING↗

Biomanufacturing and Scale-Up: Pathways to Biochemicals, Biofuels, and Biomaterials

Advancing the bioeconomy requires the development of large-scale microbial bioprocesses capable of converting waste carbon streams into biofuels, biochemicals, and biomaterials at industrially relevant scales. While biomanufacturing has been successfully demonstrated at the laboratory scale for a wide range of chemicals, only a few have reached industrial-scale production. This is partly due to the inherent complexity of microbial systems, which rely on living cells with intricate metabolic pathways that are highly sensitive to environmental changes, making large-scale production difficult to optimize and predict. As a result, scaling-up bioprocesses remains a high-stakes challenge that requires deeper exploration. This involves integrating feedstock and microbial selection, upstream and downstream processes, and computational modelling, among other research efforts. Bulk and specialty chemicals derived from biological processes also face competition from fossil-based production routes, which have been refined through decades of technological advancements. While biologically derived molecules may offer more environmentally friendly production pathways than traditional chemical manufacturing, their widespread adoption depends on achieving cost parity-or superiority-relative to fossil-based methods. This emphasizes the importance of holistic research, including techno-economic analyses and life cycle assessments, to ensure both economic viability and environmental sustainability. This editorial and special issue explores state-of-the-art strategies for converting waste carbon sources into valuable products. It discusses how enzymes, single microbes (e.g., extremophiles), and microbiomes (e.g., through division of labor) can be integrated with upstream and downstream process innovations-such as consolidated bioprocessing and in situ product recovery-to improve the efficiency and scalability of biomanufacturing. The editorial further highlights the role of computational modelling in understanding, predicting, and controlling bioprocess performance across scales, and concludes by emphasizing the importance of techno-economic modelling to identify technologies that can move to market.

09 BIOMASS FUELS↗

Atomic Layer Deposition with TiO2 for Enhanced Reactivity and Stability of Aromatic Hydrogenation Catalysts

Hydrogenation of aromatic molecules in fossil- and bio-derived fuels is essential for decreasing emissions of harmful combustion products and addressing growing concerns around urban air pollution. In this work, we used atomic layer deposition to significantly enhance the hydrogenation performance of a conventional supported Pd catalyst by applying an ultrathin coating of TiO2 in a scalable powder coating process. The TiO2-coated catalyst showed substantial gains in the conversion of multiple aromatic molecules, including a 5-fold improvement in turnover frequency versus the uncoated catalyst in the hydrogenation of naphthalene. This activity enhancement was maintained upon scaling the coating synthesis process from 3 to 100 g. Based on the results from Xray photoelectron spectroscopy, X-ray absorption spectroscopy, and computational modeling, the activity enhancement was attributed to ensemble effects resulting from partial TiO2 coverage of the Pd surface rather than fundamental changes to the Pd electronic structure. Additional durability testing confirmed that the TiO2 coating improved the thermal and hydrothermal stability of the catalyst as well as tolerance toward sulfur impurities in the reactant stream. Using an economic model of an industrial deep hydrogenation process, we found that an increase in catalyst activity or lifetime of 2× would justify even a relatively high estimate for the cost of TiO2 atomic layer deposition coatings at scale

atomic layer↗

Toward High-Throughput Deposition of III-V Materials and Devices Using Halide Vapor Phase Epitaxy: Preprint

III-V devices are used in countless applications due to their excellent physical properties. They could become more prevalent, especially in area-intensive applications such as solar power, if they can achieve significant cost decreases through increasing scale. The development of high-throughput growth systems can help to achieve this scale, leading to the use of III-V devices in areas where they are not currently economically feasible. Here, we describe a pilot production, pseudo inline HVPE reactor with the potential to greatly increase the throughput of III-V devices. We show computational modeling results that both informed system design and the understanding of the impact of different process parameters on the deposition. We show the throughput possibilities of this reactor with an example solar cell device design but note that this system is agnostic to the device structure and can be used to increase the throughput of lasers, LEDs, transistors, and more III-V devices.

high throughput↗

Impurity-induced divertor plasma oscillations

Two different oscillatory plasma regimes induced by seeding the plasma with high- and low-Z impurities are found for ITER-like divertor plasmas, using computer modeling with the DUSTT/UEDGE and SOLPS4.3 plasma-impurity transport codes. The oscillations are characterized by significant variations of the impurity-radiated power and of the peak heat load on the divertor targets. Qualitative analysis of the divertor plasma oscillations reveals different mechanisms driving the oscillations in the cases of high- and low-Z impurity seeding. The oscillations caused by the high-Z impurities are excited near the X-point by an impurity-related instability of the radiation-condensation type, accompanied by parallel impurity ion transport affected by the thermal and plasma friction forces. The driving mechanism of the oscillations induced by the low-Z impurities is related to the cross-field transport of the impurity atoms, causing alteration between the high and low plasma temperature regimes in the plasma recycling region near the divertor targets. The implications of the impurity-induced plasma oscillations for divertor operation in the next generation tokamaks are also discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Tungsten dust impact on ITER-like plasma edge

The impact of tungsten dust originating from divertor plates on the performance of edge plasma in ITER-like discharge is evaluated using computer modeling with the coupled dust-plasma transport code DUSTT-UEDGE. Different dust injection parameters, including dust size and mass injection rates, are surveyed. It is found that tungsten dust injection with rates as low as a few mg/s can lead to dangerously high tungsten impurity concentrations in the plasma core. Dust injections with rates of a few tens of mg/s are shown to have a significant effect on edge plasma parameters and dynamics in ITER scale tokamaks. The large impact of certain phenomena, such as dust shielding by an ablation cloud and the thermal force on tungsten ions, on dust/impurity transport in edge plasma and consequently on core tungsten contamination level is demonstrated. It is also found that high-Z impurities provided by dust can induce macroscopic self-sustained plasma oscillations in plasma edge leading to large temporal variations of edge plasma parameters and heat load to divertor target plates.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Frameworks, Algorithms, and Scalable Technologies for Mathematics (FASTMath) SciDAC Institute

As computational models scale to larger computers, the rate at which they produce data has far outstripped the same computers ability to write that data and further the file systems ability to store that data. Almost all of the SciDAC applications, but especially those related to fusion solve very large scale PDEs whose scientific output his impacted by this problem. To gain access to dynamics in an exascale simulation that are not identifiable a priori and to make that dynamical data available to machine learning requires fundamental research in the area of in situ data data analytics. Here data analytics includes compression, visualization, uncertainty quantification, and machine learning. This in situ data analytics will enable on-the-fly spatial and temporal compression of solution dynamics, expose that space-time compressed field to machine learning algorithms that have been specialized to work with dynamically evolving data (existing machine learning algorithms treat data sets as static), greatly improving the opportunity for machine learning to provide feedback to the compression, all within an ongoing simulation, without the need to write data to files. The same concepts are also being applied to uncertainty quantification and multi-fidelity modeling which have similar needs for spatial and temporal compression of the ongoing exascale simulation to perform either without the typical, unacceptable writing of data to files.

97 MATHEMATICS AND COMPUTING↗

Evolution of Tantalum Content During Vacuum Induction Melting and Electroslag Remelting of a Novel Martensitic Steel

The need for materials with superior thermal and mechanical properties while mitigating cost increases interest in new complex alloy compositions which brings challenges to manufacturing processes. In this investigation, vacuum induction melting (VIM) and electroslag remelting (ESR) of a novel tantalum (Ta)-containing martensitic steel was performed using standard industry practices at a laboratory scale. A 25 pct loss of Ta was measured from the VIM electrode to the ESR ingot using X-ray fluorescence. Several tools were used for broad characterization of the ingots, including LECO for chemistry analysis, scanning electron microscopy, and electron probe microanalysis for observation of the precipitate and inclusion phases post-VIM and post-ESR as well as computational modeling of the ESR process for the calculation of macrosegregation and inclusion travel. It was found that a significant amount of Ta{sub 2}O{sub 5} inclusions formed during VIM and were transferred to the slag during ESR. While ESR was particularly successful at decreasing the number density of inclusions by 95 pct, additional efforts are needed with regard to vacuum leak rate and purity of stock material when melting novel advanced steels.

36 MATERIALS SCIENCE↗

Credible practice of modeling and simulation in healthcare: ten rules from a multidisciplinary perspective

The complexities of modern biomedicine are rapidly increasing. Thus, modeling and simulation have become increasingly important as a strategy to understand and predict the trajectory of pathophysiology, disease genesis, and disease spread in support of clinical and policy decisions. In such cases, inappropriate or ill-placed trust in the model and simulation outcomes may result in negative outcomes, and hence illustrate the need to formalize the execution and communication of modeling and simulation practices. Although verification and validation have been generally accepted as significant components of a model’s credibility, they cannot be assumed to equate to a holistic credible practice, which includes activities that can impact comprehension and in-depth examination inherent in the devel-opment and reuse of the models. For the past several years, the Committee on Credible Practice of Modeling and Simulation in Healthcare, an interdisciplinary group seeded from a U.S. interagency initiative, has worked to codify best practices. Here, we provide Ten Rules for credible practice of modeling and simulation in healthcare developed from a comparative analysis by the Committee’s multidisciplinary membership, followed by a large stakeholder com-munity survey. These rules establish a unified conceptual framework for modeling and simulation design, implementation, evaluation, dissemination and usage across the modeling and simulation life-cycle. While biomedical science and clinical care domains have somewhat different requirements and expectations for credible practice, our study converged on rules that would be useful across a broad swath of model types. In brief, the rules are: (1) Define context clearly. (2) Use contextually appropriate data. (3) Evaluate within context. (4) List limitations explicitly. (5) Use version control. (6) Document appropriately. (7) Disseminate broadly. (8) Get independent reviews. (9) Test competing imple-mentations. (10) Conform to standards. Although some of these are common sense guidelines, we have found that many are often missed or misconstrued, even by seasoned practitioners. Computational models are already widely used in basic science to generate new biomedical knowledge. As they penetrate clinical care and healthcare policy, contributing to personalized and precision medicine, clinical safety will require established guidelines for the credible practice of modeling and simulation in healthcare.

Credibility↗

In Situ Chemical Imaging of Solid-Electrolyte Interphase Layer Evolution in Li–S Batteries

Parasitic reactions of electrolyte and polysulfide with the Li-anode in lithium sulfur (Li-S) batteries lead to the for-mation of solid electrolyte interphase (SEI) layers, which are the major reason behind severe capacity fading in these systems. Despite numerous studies, the evolution mechanism of the SEI layer and specific roles of polysulfides and oth-er electrolyte components are still unclear. We report an in-situ X-ray photoelectron spectroscopy (XPS) and chemical imaging analysis combined with ab initio molecular dynamics (AIMD) computational modeling to gain fundamental understanding regarding the evolution of SEI layers on Li-anodes within Li-S batteries. A multi-modal approach in-volving AIMD modeling and in-situ XPS characterization uniquely reveals the chemical identity and distribution of active participants in parasitic reactions as well as the SEI layer evolution mechanism. The SEI layer evolution has three major stages: the formation of a primary composite mixture phase involving stable lithium compounds (Li2S, LiF, Li2O etc); and formation of a secondary matrix type phase due to cross interaction between reaction products and elec-trolyte components, which is followed by a highly dynamic mono-anionic polysulfide (i.e. LiS5) fouling process. These new molecular-level insights into the SEI layer evolution on Li- anodes are crucial for delineating effective strategies for the development of Li–S batteries.

25 ENERGY STORAGE↗

Sintering-resistant Single-Site Nickel Catalyst Supported by Metal-Organic Framework

Developing supported single-site catalysts is an important goal in heterogeneous catalysis, since the well-defined active sites afford opportunities for detailed mechanistic studies, thereby facilitating the design of improved catalysts. We present herein a method for installing Ni ions uniformly and precisely on the node of a Zr-based MOF, NU-1000, in high density and large quantity (denoted as Ni-AIM) using atomic layer deposition (ALD) in a metal–organic framework (MOF) (AIM). Ni-AIM is demonstrated to be an efficient gas-phase hydrogenation catalyst upon activation. The structure of the active sites in Ni-AIM is proposed, revealing its single-site nature. More importantly, due to the organic linker used to construct the MOF support, the Ni ions stay isolated throughout the hydrogenation catalysis, in accord with its long-term stability. A quantum chemical characterization of the catalyst and the catalytic process complements the experimental results. With validation of computational modeling protocols, we further targeted ethylene oligomerization catalysis by Ni-AIM guided by theoretical prediction. Given the generality of the AIM methodology, this emerging class of materials should prove ripe for the discovery of new catalysts for the transformation of volatile substrates.

Li, Zhanyong↗

Climate Control Load Reduction Strategies for Electric Drive Vehicles in Cold Weather

When operated, the climate control system is the largest auxiliary load on a vehicle. This load has significant impact on fuel economy for conventional and hybrid vehicles, and it drastically reduces the driving range of all electric vehicles (EVs). Heating is even more detrimental to EV range than cooling because no engine waste heat is available. Reducing the thermal loads on the heating, ventilating, and air conditioning system will extend driving range and increase the market penetration of EVs. Researchers at the National Renewable Energy Laboratory have evaluated strategies for vehicle climate control load reduction with special attention toward grid connected electric vehicles. Outdoor vehicle thermal testing and computational modeling were used to assess potential strategies for improved thermal management and to evaluate the effectiveness of thermal load reduction technologies. A human physiology model was also used to evaluate the impact on occupant thermal comfort. Experimental evaluations of zonal heating strategies demonstrated a 5.5% to 28.5% reduction in cabin heating energy over a 20-minute warm-up. Vehicle simulations over various drive cycles show a 6.9% to 18.7% improvement in EV range over baseline heating using the most promising zonal heating strategy investigated. A national-level analysis was conducted to determine the overall national impact. If all vehicles used the best zonal strategy, the range would be improved by 7.1% over the baseline heating range. This is a 33% reduction in the range penalty for heating.

30 DIRECT ENERGY CONVERSION↗

Large Scale Experiments on Spacecraft Fire Safety

Full scale fire testing complemented by computer modelling has provided significant knowhow about the risk, prevention and suppression of fire in terrestrial systems (cars, ships, planes, buildings, mines, and tunnels). In comparison, no such testing has been carried out for manned spacecraft due to the complexity, cost and risk associated with operating a long duration fire safety experiment of a relevant size in microgravity. Therefore, there is currently a gap in knowledge of fire behaviour in spacecraft. The entire body of low-gravity fire research has either been conducted in short duration ground-based microgravity facilities or has been limited to very small fuel samples. Still, the work conducted to date has shown that fire behaviour in low-gravity is very different from that in normal gravity, with differences observed for flammability limits, ignition delay, flame spread behaviour, flame colour and flame structure. As a result, the prediction of the behaviour of fires in reduced gravity is at present not validated. To address this gap in knowledge, a collaborative international project, Spacecraft Fire Safety, has been established with its cornerstone being the development of an experiment (Fire Safety 1) to be conducted on an ISS resupply vehicle, such as the Automated Transfer Vehicle (ATV) or Orbital Cygnus after it leaves the ISS and before it enters the atmosphere. A computer modelling effort will complement the experimental effort. Although the experiment will need to meet rigorous safety requirements to ensure the carrier vehicle does not sustain damage, the absence of a crew removes the need for strict containment of combustion products. This will facilitate the possibility of examining fire behaviour on a scale that is relevant to spacecraft fire safety and will provide unique data for fire model validation. This unprecedented opportunity will expand the understanding of the fundamentals of fire behaviour in spacecraft. The experiment is being developed by an international topical team that is collaboratively defining the experiment requirements and performing supporting analysis, experimentation and technology development. This paper presents the objectives, status and concept of this project.

Urban, David↗

Large Scale Experiments on Spacecraft Fire Safety

Full scale fire testing complemented by computer modelling has provided significant know how about the risk, prevention and suppression of fire in terrestrial systems (cars, ships, planes, buildings, mines, and tunnels). In comparison, no such testing has been carried out for manned spacecraft due to the complexity, cost and risk associated with operating a long duration fire safety experiment of a relevant size in microgravity. Therefore, there is currently a gap in knowledge of fire behaviour in spacecraft. The entire body of low-gravity fire research has either been conducted in short duration ground-based microgravity facilities or has been limited to very small fuel samples. Still, the work conducted to date has shown that fire behaviour in low-gravity is very different from that in normal-gravity, with differences observed for flammability limits, ignition delay, flame spread behaviour, flame colour and flame structure. As a result, the prediction of the behaviour of fires in reduced gravity is at present not validated. To address this gap in knowledge, a collaborative international project, Spacecraft Fire Safety, has been established with its cornerstone being the development of an experiment (Fire Safety 1) to be conducted on an ISS resupply vehicle, such as the Automated Transfer Vehicle (ATV) or Orbital Cygnus after it leaves the ISS and before it enters the atmosphere. A computer modelling effort will complement the experimental effort. Although the experiment will need to meet rigorous safety requirements to ensure the carrier vehicle does not sustain damage, the absence of a crew removes the need for strict containment of combustion products. This will facilitate the possibility of examining fire behaviour on a scale that is relevant to spacecraft fire safety and will provide unique data for fire model validation. This unprecedented opportunity will expand the understanding of the fundamentals of fire behaviour in spacecraft. The experiment is being developed by an international topical team that is collaboratively defining the experiment requirements and performing supporting analysis, experimentation and technology development. This paper presents the objectives, status and concept of this project.

Urban, David L.↗

Atomistic simulation study of short pulse laser interactions with a metal target under conditions of spatial confinement by a transparent overlayer

The distinct characteristics of short pulse laser interactions with a metal target under conditions of spatial confinement by a solid transparent overlayer are investigated in a series of atomistic simulations. The simulations are performed with a computational model combining classical molecular dynamics (MD) technique with a continuum description of the laser excitation, electron-phonon equilibration, and electronic heat transfer based on two-temperature model (TTM). Two methods for incorporation of the description of a transparent overlayer into the TTM-MD model are designed and parameterized for Ag-silica system. The material response to the laser energy deposition is studied for a range of laser fluences that, in the absence of the transparent overlayer, covers the regimes of melting and resolidification, photomechanical spallation, and phase explosion of the overheated surface region. In contrast to the irradiation in vacuum, the spatial confinement by the overlayer facilitates generation of sustained high-temperature and high-pressure conditions near the metal-overlayer interface, suppresses the generation of unloading tensile wave, decreases the maximum depth of melting, and prevents the spallation and explosive disintegration of the surface region of the metal target. At high laser fluences, when the laser excitation brings the surface region of the metal target to supercritical conditions, the confinement prevents the expansion and phase decomposition characteristic for the vacuum conditions leading to a gradual cooling of the hot compressed supercritical fluid down to the liquid phase and eventual solidification. The target modification in this case is limited to the generation of crystal defects and the detachment of the metal target from the overlayer.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗