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At least 991 records · Page 55

Science-informed Machine Learning to Increase Recovery Efficiency in Unconventional Reservoirs

Production of hydrocarbons from fractured, unconventional reservoirs is inherently inefficient. But machine learning offers a pathway both to increasing recovery efficiency at a site and to improving forecasts of production, thereby improving the economics of operations in unconventional reservoirs. Los Alamos—in partnership with DOE, NETL, and WVU—has been developing a science-informed workflow and platform for optimizing pressure-drawdown at a site, which will allow an operator to make reservoir-management decisions that optimize recovery in consideration of future production. This work relies on a hybridization of physics-based prediction and machine learning, whereby accurate synthetic data (in combination with available site data) can enable the application of machine learning methods for rapid forecasting and optimization. The physics-based prediction is built upon experimental and theoretical work to determine transport characteristics in shale at various scales, with an emphasis on materials from MSEEL-I; this fundamental shale R&D was conducted in partnership with DOE, NETL, and several other national labs. This work has resulted from a coordinated leveraging of developments across several projects within DOE FE30, along with internal investments from Los Alamos via LDRD. The development has utilized data from the MSEEL–I site for calibration and demonstration; however, the workflow and platform are readily extendable to operations at other sites, plays, and basins. This machine-learning method can aid operators to improve both recovery efficiency and competitiveness; to this end, future work would quantify processes for other plays/basins and integrate production details with economics.

04 OIL SHALES AND TAR SANDS↗

An exploration of online-simulation-driven portfolio scheduling in Workflow Management Systems

Workflow Management Systems used to automate the execution of scientific workflow applications on parallel and distributed computing platforms must make scheduling decisions at runtime. A large number of workflow scheduling algorithms have been proposed in the literature, but often these algorithms are evaluated based on simplifying assumptions that may not hold in practice. Furthermore, published algorithm evaluation and/or comparison results are necessarily only for a subset of all possible scenarios, and thus may not include scenarios relevant to particular use-cases. Consequently, it is difficult for Workflow Management Systems (WMSs) developers to decide which scheduling algorithm should be implemented. To obviate this difficulty, one possible approach is to implement a portfolio of scheduling algorithms and select the most effective algorithm at runtime. One method for performing this selection is to run an online simulation for each algorithm in the portfolio. The algorithm that leads to the best performance, in simulation, is selected for future use. The above simulation-driven portfolio scheduling (SDPS) approach has been proposed in a few parallel and distributed computing contexts. The main objective of this work is to evaluate the feasibility and potential merit of SDPS if implemented in WMSs. Here we perform this evaluation using simulated WMS executions, where the simulations are instantiated from real-world platform and workflow configurations. Our main finding is that SDPS is on par with or outperforms an approach in which a single algorithm is used, where this algorithm is the one that performs best on average across all our experimental scenarios. Furthermore, we find that SDPS remains an attractive proposition even in the presence of high levels of simulation error and for simulators with relatively low levels of sophistication. In many of our experimental scenarios we find that mitigating simulation error at runtime can further improve performance. Finally, we show that simulation overhead can be made sufficiently low for SDPS to be feasible in practice.

97 MATHEMATICS AND COMPUTING↗

Comparable Enhancement of TERS Signals from WSe 2 on Chromium and Gold

Plasmonic tip-sample junctions, at which the incident and scattered optical fields are localized and optimally enhanced, are often exploited to achieve ultrasensitive and highly spatially localized tip-enhanced Raman scattering (TERS). Recent work has demonstrated that the sensitivity and spatial resolution that are required to probe single molecules are attainable in such platforms. In this work, we observe and rationalize comparable TERS from few-layer WSe 2 single crystals exfoliated onto Au- and Cr-coated Si substrates, using a plasmonic TERS probe excited with a 638-nm laser. Our experimental observations are supported by finite-difference time-domain simulations that illustrate that the attainable field enhancement factors at the Au-Au and Au-Cr tip-sample nanojunctions are comparable in magnitude. Furthermore, through a combined experimental and theoretical analysis, we propose that besides Au/Ag, several metallic substrates may be used to record bright TERS spectral images.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Sustainable Triacetic Acid Lactone Production from Sugarcane by Fermentation and Crystallization

Triacetic acid lactone (TAL) has the potential to serve as a bioderived platform chemical for commercial products including sorbic acid and recyclable polydiketoenamine plastics. In this study, we leveraged BioSTEAM to design, simulate, and evaluate (via techno-economic analysis, TEA, and life cycle assessment, LCA) TAL production from sugarcane. We experimentally characterized TAL solubility, calibrated solubility models, and designed a process to separate TAL from fermentation broths by crystallization. The biorefinery could produce TAL at a minimum product selling price (MPSP) of $\$3.73$–5.86·kg –1 (5th–95th percentiles; baseline at $\$4.60$·kg –1 ) and a carbon intensity (CI) of 5.31 [2.60–8.71] kg CO 2 -eq·kg –1 , which could enable financially viable, low-CI production of sorbic acid and polydiketoenamines. To drive down costs and CI, we explored the theoretical fermentation space (titer, yield, productivity combinations), operation scheduling and capacity expansion strategies (e.g., integrated sorghum processing), and potential separation improvements (mitigating TAL loss through pH control). Advancements in key design and technological parameters could further reduce MPSP by 51% to $\$2.26$·kg –1 [$\$1.97$–2.80·kg –1 ] and CI by 43% to 3.05 [1.91–4.15] kg CO 2 -eq·kg –1 . This research highlights the ability of agile TEA-LCA to screen promising designs, navigate sustainability trade-offs, prioritize research needs, and chart quantitative roadmaps to advance bioproducts and biofuels.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Twist-angle dependence of moiré excitons in WS 2 /MoSe 2 heterobilayers

Moiré lattices formed in twisted van der Waals bilayers provide a unique, tunable platform to realize coupled electron or exciton lattices unavailable before. While twist angle between the bilayer has been shown to be a critical parameter in engineering the moiré potential and enabling novel phenomena in electronic moiré systems, a systematic experimental study as a function of twist angle is still missing. Here we show that not only are moiré excitons robust in bilayers of even large twist angles, but also properties of the moiré excitons are dependant on, and controllable by, the moiré reciprocal lattice period via twist-angle tuning. From the twist-angle dependence, we furthermore obtain the effective mass of the interlayer excitons and the electron inter-layer tunneling strength, which are difficult to measure experimentally otherwise. These findings pave the way for understanding and engineering rich moiré-lattice induced phenomena in angle-twisted semiconductor van der Waals heterostructures.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Technology for robotic surface inspection in space

This paper presents on-going research in robotic inspection of space platforms. Three main areas of investigation are discussed: machine vision inspection techniques, an integrated sensor end-effector, and an orbital environment laboratory simulation. Machine vision inspection utilizes automatic comparison of new and reference images to detect on-orbit induced damage such as micrometeorite impacts. The cameras and lighting used for this inspection are housed in a multisensor end-effector, which also contains a suite of sensors for detection of temperature, gas leaks, proximity, and forces. To fully test all of these sensors, a realistic space platform mock-up has been created, complete with visual, temperature, and gas anomalies. Further, changing orbital lighting conditions are effectively mimicked by a robotic solar simulator. In the paper, each of these technology components will be discussed, and experimental results are provided.

Volpe, Richard↗

Laser Beam Welding Benchmark Experiments Performed in Reduced Gravity and Vacuum

Laser beam welding (LBW) is affected by the extreme temperatures, reduced pressure, and reduced gravity present in space environments. Gravity and pressure especially influence its melt pool and solidification dynamics. A compact, modular vacuum chamber adaptable to flight platforms from parabolic to orbital currently hosts an experiment to investigate the combined influence of reduced gravity and pressure on LBW. A swappable cartridge contains a rotating platen on which customizable workpieces can be welded under vacuum, greatly increasing experimental throughput. Instrumentation includes weld and thermal cameras observing the process, thermocouples placed on workpieces, accelerometers, and vacuum sensors. Experimental data gathered during the welding process will be combined with post-flight nondestructive evaluation, metallography, and mechanical testing to provide validation datasets for computational modeling. Phase I of this effort involves a parabolic flight campaign in low gravity while an anticipated Phase II would proceed to in-space demonstration to access extended duration microgravity.

in-space welding↗

Method for simultaneous characterization and expansion of reference libraries for small molecule identification

A variational autoencoder (VAE) has been developed to learn a continuous numerical, or latent, representation of molecular structure to expand reference libraries for small molecule identification. The VAE has been extended to include a chemical property decoder, trained as a multitask network, to shape the latent representation such that it assembles according to desired chemical properties. The approach is unique in its application to metabolomics and small molecule identification, focused on properties that are obtained from experimental measurements (m/z, CCS) paired with its training paradigm, which involves a cascade of transfer learning iterations. First, molecular representation is learned from a large dataset of structures with m/z labels. Next, in silico property values are used to continue training. Finally, the network is further refined by being trained with the experimental data. The trained network is used to predict chemical properties directly from structure and generate candidate structures with desired chemical properties. The network is extensible to other training data and molecular representations, and for use with other analytical platforms, for both chemical property and feature prediction as well as molecular structure generation.

Colby, Sean M.↗

A consolidated bioprocess design to produce multiple high-value platform chemicals from lignocellulosic biomass and its technoeconomic feasibility

5-Hydroxymethyl furfural (HMF) and furfurals are DOE-listed platform chemicals that can be derived from the renewable carbon in the lignocellulosic biomasses and have the potential to replace petroleum-derived alter- natives. High substrate cost and use of expensive solvents limit the economic feasibility of bio-based HMF production on an industrially relevant scale. The study presents an experimental optimized condition that maximizes the chemical-free production of HMF and furfurals without lowering the yield of total fermentable sugars from Saccharum bagasse. Hydrothermal pretreatment at 210 °C for 15 min yielded approximately 10%, 12%, and 46% of HMF, furfurals, and fermentable sugars per gram of dry biomass, respectively. Additionally, the study proposes a consolidated bioprocess model to produce and recover four high-value bioproducts i.e., HMF, furfurals, ethanol, and acetic acid based on the experimental results and evaluates its technoeconomic feasibility considering HMF as the main product. The minimum selling price (MSP) of HMF was estimated to be 930.6 USD/ t which is competitive with its petroleum-derived precursor alternative p-xylene (1,113 USD/t). The sensitivity analysis performed for the process parameters suggests that pretreatment cost and revenues from coproducts immensely influence the MSP of HMF. The preliminary technoeconomic analysis performed on the consolidated bioprocess design indicates that additional revenue streams from diversified coproducts in biorefineries aid in lowering the MSP of high-value bioproducts.

09 BIOMASS FUELS↗

Single-Step Conversion of Ethanol to n-Butene over Ag-ZrO2/SiO2 Catalysts

Ethanol is a promising platform molecule for production of a variety of fuels and chemicals. Of particular interest is producing middle distillate fuels (i.e., jet and diesel blendstock) from renewable ethanol feedstock. State-of-the-art alcohol-to-jet technology requires multiple process steps based on catalytic dehydration of ethanol to form ethylene, followed by sometimes a multi-step oligomerization, and then hydrotreatment and distillation. Here we report on a new catalytic route in which ethanol is directly converted to n-butene (1- and 2-butene mixtures) over Ag-ZrO2/SBA-16, thus offering the potential for a reduction in the number of required processing steps versus conventional alcohol-to-jet technology. This catalyst system provides the balanced metal and Lewis acid sites required to selectively facilitate a cascading sequence of reactions that includes dehydrogenation, aldol condensation, Meerwein–Ponndorf–Verley reduction, dehydration, and hydrogenation. High conversion and selectivity toward either n-butene or 1,3-butadiene is achieved by tuning the hydrogen feed partial pressure and other process/catalyst parameters. With sufficient hydrogen partial pressure 1,3-butadiene is completely and selectively hydrogenated to form n-butene. The reaction mechanism was elucidated through operando-nuclear magnetic resonance investigations coupled with reactivity measurements. Combined experimental-computational investigation reveals how changes in silver and zirconium composition and the silver oxidation state affects reactivity under controlled hydrogen partial pressures and after prolonged run times. Finally, catalyst effectiveness also was demonstrated when using wet ethanol feed, thus highlighting process flexibility in terms of feedstock purity requirements. This work was financially supported by the U.S. Department of Energy (DOE), Office of Energy Efficiency and Renewable Energy, Bioenergy Technologies Office, and was performed at the Pacific Northwest National Laboratory (PNNL) under Contract No. DE-AC05-76RL01830 and the National Renewable Energy Laboratory under Contract No. DE-AC36- 08GO28308. Part of the work conducted by S. A. Akhade was performed under the auspices of the U.S. DOE at Lawrence Livermore National Laboratory under Contract No. DE-AC52-07NA27344. This work was partly supported through the PNNL-WSU Distinguished Graduate Research Program for ADW. NMR and XPS experiments were performed using EMSL (grid.436923.9), a DOE Office of Science User Facility sponsored by the Office of Biological and Environmental Research

Dagle, Vanessa↗

Parallel and Distributed Computational Fluid Dynamics: Experimental Results and Challenges

This paper describes several results of parallel and distributed computing using a large scale production flow solver program. A coarse grained parallelization based on clustering of discretization grids combined with partitioning of large grids for load balancing is presented. An assessment is given of its performance on distributed and distributed-shared memory platforms using large scale scientific problems. An experiment with this solver, adapted to a Wide Area Network execution environment is presented. We also give a comparative performance assessment of computation and communication times on both the tightly and loosely-coupled machines.

Djomehri, Mohammad Jahed↗

Bubble Formation and Detachment in Liquid Flow Under Normal and Reduced Gravity

Two-phase flows are present in a wide variety of applications for spacecraft thermal control systems design. Bubble formation and detachment is an integral part of the two-phase flow science. The authors objective is to experimentally investigate the effects of liquid cross velocity, gas velocity, and nozzle diameter on the bubble diameter at detachment under reduced and normal gravity and under relatively low gas flow rates. Results from ground (1 g) and reduced gravity experiments will be presented in this paper. For the 1 g experiment, a flow loop was designed and built to accommodate a range of liquid and gas flow rates. The reduced gravity experiment was conducted on the NASA DC-9 reduced gravity platform using the two-phase flow loop qualified for operation on the low-gravity platform. Flow visualization is accomplished using a high speed 500 frames/s camera. The results suggest that the existence of buoyancy force contributes to the faster detachment of bubbles. Buoyancy helps the detachment process which results in smaller bubbles being formed. In reduced gravity, although drag force is present, the virtual non-existence of buoyant force results in larger bubbles and longer times for detachment. Theoretical predictions are also presented in this paper and seem to agree with the experimental results.

Nahra, Henry K.↗

Nanoscale Mapping and Defect-Assisted Manipulation of Surface Plasmon Resonances in 2D Bi 2 Te 3 /Sb 2 Te 3 In-Plane Heterostructures

Here, the Bi 2 Te 3 /Sb 2 Te 3 in-plane heterostructure is reported as a low-dimensional tunable chalcogenide well suited as plasmonic building block for the visible-UV spectral range. Electron-driven plasmon excitations of low-dimensional Bi 2 Te 3 /Sb 2 Te 3 are investigated by monochromated electron energy loss spectroscopy spectrum imaging. To resolve the nanoscale spatial distribution of various local plasmonic resonances, singular value decomposition is used to disentangle the spectral data and identify the individual spectral contributions of various corner, edge, and face modes. Furthermore, defect-plasmon interactions are investigated both for nanoscale intrinsic and thermally induced extrinsic polygonal defects (in situ sublimation). Signature of defect-induced red shift ranging from a several hundreds of millielectronvolts to a few electronvolts, broadening of various plasmon response, together with selective enhancement and significant variations in their intensity are detected. This study highlights the presence of a heterointerface and identifies defects as physical tuning pathways to modulate the plasmonic response over a broad spectral range. Finally, the experimental observations are compared qualitatively and validated with numerical simulations using the electron-driven discrete dipole approximation. Low-dimensional Bi 2 Te 3 /Sb 2 Te 3 as a less explored plasmonic system holds great promises as emerging platform for integrated plasmonics. Furthermore, introducing controlled structural defects can open the door for nanoengineering of plasmonic properties in such systems.

36 MATERIALS SCIENCE↗

ADAM: A web platform for graph-based modeling and optimization of supply chains

Modeling and optimization are essential tasks that arise in the analysis and design of supply chains (SCs). SC models are essential for understanding emergent behavior such as transactions between participants, inherent value of products exchanged, as well as impact of externalities (e.g., policy and climate) and of constraints. Unfortunately, most users of SC models have limited expertise in mathematical optimization, and this hinders the adoption of advanced decision-making tools. Here, in this work, we present ADAM, a web platform that enables the modeling and optimization of SCs. ADAM facilitates modeling by leveraging intuitive and compact graph-based abstractions that allow the user to express dependencies between locations, products, and participants. ADAM model objects serve as repositories of experimental, technology, and socio-economic data; moreover, the graph abstractions facilitate the organization and exchange of models and provides a natural framework for education and outreach. Here, we discuss the graph abstractions and software design principles behind ADAM, its key functional features and workflows, and application examples.

97 MATHEMATICS AND COMPUTING↗

Development of Ternary Transition Metal Oxide Catalysts for Oxygen Evolution Reaction

Electrochemical water splitting, a promising method for green hydrogen production, is currently hindered by the high cost of precious-group metal (PGM)-based catalysts for the oxygen evolution reaction (OER). This study addresses this challenge by advancing the development of catalysts for OER, focusing on the development of high-performance PGM-free catalysts using nickel-iron-cobalt (NiFeCo)-based aerogels. The catalysts were synthesized via a sol-gel method and critical point drying to achieve a highly porous structure with an exceptionally high surface area. The designed catalyst structure provides an ideal platform for maximizing catalytic active sites and enhancing mass transport kinetics. Co has been systematically incorporated into the current PGM-free state-of-the-art, NiFeOx catalyst, and the metal ratios have been optimized. In addition to the experimental studies, density functional theory calculations were performed to study the material’s properties of this ternary catalyst and the effect of Co addition on enhancing OER catalysis.

Mizrahi, Michal [Bar-Ilan University, Ramat Gan, I↗

Flat band carrier confinement in magic-angle twisted bilayer graphene

Abstract Magic-angle twisted bilayer graphene has emerged as a powerful platform for studying strongly correlated electron physics, owing to its almost dispersionless low-energy bands and the ability to tune the band filling by electrostatic gating. Techniques to control the twist angle between graphene layers have led to rapid experimental progress but improving sample quality is essential for separating the delicate correlated electron physics from disorder effects. Owing to the 2D nature of the system and the relatively low carrier density, the samples are highly susceptible to small doping inhomogeneity which can drastically modify the local potential landscape. This potential disorder is distinct from the twist angle variation which has been studied elsewhere. Here, by using low temperature scanning tunneling spectroscopy and planar tunneling junction measurements, we demonstrate that flat bands in twisted bilayer graphene can amplify small doping inhomogeneity that surprisingly leads to carrier confinement, which in graphene could previously only be realized in the presence of a strong magnetic field.

36 MATERIALS SCIENCE↗

Inverse-designed broadband low-loss grating coupler on thick lithium-niobate-on-insulator platform

A grating coupler on 700-nm-thick Z-cut lithium-niobate-on-insulator platform with high coupling efficiency, large bandwidth, and high fabrication tolerance is designed and optimized by inverse design method. The optimized grating coupler is fabricated with a single set of e-beam lithography and etching process, and it is experimentally characterized to possess peak coupling efficiency of −3.8 dB at 1574.93 nm, 1 dB bandwidth of 71.7 nm, and 3 dB bandwidth of over 120 nm, respectively.

Physics↗

Photoluminescence spectra of point defects in semiconductors: Validation of first-principles calculations

Optically and magnetically active point defects in semiconductors are interesting platforms for the development of solid state quantum technologies. Their optical properties are usually probed by measuring photoluminescence spectra, which provide information on excitation energies and on the interaction of electrons with lattice vibrations. We present a combined computational and experimental study of photoluminescence spectra of defects in diamond and SiC, aimed at assessing the validity of theoretical and numerical approximations used in first-principles calculations, including the use of the Franck-Condon principle and the displaced harmonic oscillator approximation. We focus on prototypical examples of solid state qubits, the divacancy centers in SiC and the nitrogen-vacancy in diamond, and we report computed photoluminescence spectra as a function of temperature that are in very good agreement with the measured ones. As expected we find that the use of hybrid functionals leads to more accurate results than semilocal functionals. Interestingly our calculations show that constrained density functional theory (CDFT) and time-dependent hybrid DFT perform equally well in describing the excited state potential energy surface of triplet states; our findings indicate that CDFT, a relatively cheap computational approach, is sufficiently accurate for the calculations of photoluminescence spectra of the defects studied here. Finally, we find that only by correcting for finite-size effects and extrapolating to the dilute limit can one obtain a good agreement between theory and experiment. Our results provide a detailed validation protocol of first-principles calculations of photoluminescence spectra, necessary both for the interpretation of experiments and for robust predictions of the electronic properties of point defects in semiconductors.

36 MATERIALS SCIENCE↗