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At least 631 records · Page 35

Metall: A persistent memory allocator for data-centric analytics

Data analytics applications transform raw input data into analytics-specific data structures before performing analytics. Unfortunately, such data ingestion steps are often more expensive than analytics. In addition, various types of NVRAM devices are already used in many HPC systems today. Such devices will be useful for storing and reusing data structures beyond a single process life cycle. We developed Metall, a persistent memory allocator built on top of the memory-mapped file mechanism. Metall enables applications to transparently allocate custom C++ data structures into various types of persistent memories. Metall incorporates a concise and high-performance memory management algorithm inspired by Supermalloc and the rich C++ interface developed by Boost.Interprocess library. On a dynamic graph construction workload, Metall achieved up to 11.7x and 48.3x performance improvements over Boost.Interprocess and memkind (PMEM kind), respectively. We also demonstrate Metall’s high adaptability by integrating Metall into a graph processing framework, GraphBLAS Template Library. Here this study’s outcomes indicate that Metall will be a strong tool for accelerating future large-scale data analytics by allowing applications to leverage persistent memory efficiently.

97 MATHEMATICS AND COMPUTING↗

Benzene Ring Knitting Achieved by Ambient-Temperature Dehalogenation via Mechanochemical Ullmann-Type Reductive Coupling

The current approaches capable of affording conjugated porous networks (CPNs) still rely on solution-based coupling reactions promoted by noble metal complexes or Lewis acids, on-surface polymerization conducted in ultrahigh-vacuum environment at very high temperatures (>200 °C), or mechanochemical Scholl-type reactions limited to electron-rich substrates. To develop simple and scalable approaches capable of making CPNs under neat and ambient conditions, herein, a novel and complementary method to the current oxidative Scholl coupling processes is demonstrated to afford CPNs via direct aromatic ring knitting promoted by mechanochemical Ullmann-type reactions. The key to this strategy lies in the dehalogenation of aromatic halides in the presence of Mg involving the formation of Grignard reagent intermediates. Products (Ph-CPN-1) obtained via direct C-C bond formation between 1,2,4,5-tetrabromobenzene (TBB) monomer feature high surface areas together with mesoporous architecture. The versatility of this approach is confirmed by the successful construction of various CPNs via knitting of the corresponding aromatic rings (e.g., pyrene and triphenylene), and even highly crystalline graphite product was obtained. The CPNs exhibit good electrochemical performance as the anode material in lithium-ion batteries (LIBs). Overall, this approach expands the frontiers of CPN synthesis and provides new opportunities to their scalable applications.

36 MATERIALS SCIENCE↗

Experimental and computational design tools for industrial drying processes: Challenges in process‐limit prediction

Abstract The coating and drying of inks and slurries are important steps to manufacture a plethora of products. Drying processes, particularly, comprise energy‐intensive steps that affect product cost and quality. Prior work has highlighted failures of various multicomponent diffusivity models to conserve mass in dryer modeling and challenges in predicting process limits given variability in published values of key thermodynamic parameters. Herein, we develop a computational model and benchtop drying experiments to investigate these concerns for drying polymer‐laden coatings. Model predictions of process limits in a single‐zone drying oven demonstrate that published variability in Flory–Huggins parameter yields large variations in predicted operating temperatures above which blistering occurs. This indicates that caution should be exercised when choosing approaches to obtain or predict the Flory–Huggins parameter, and that both benchtop drying experiments and a set of additional experiments, such as sorption experiments, are needed to fully characterize and optimize a given drying process.

Parrish, Chance↗

Solvent‐Free Self‐Assembly for Scalable Preparation of Highly Crystalline Mesoporous Metal Oxides

Abstract Mesoporous metal oxides (MMOs) have been demonstrated great potential in various applications. Up to now, the direct synthesis of MMOs is still limited to the solvent induced inorganic‐organic self‐assembly process. Here, we develop a facile, general, and high throughput solvent‐free self‐assembly strategy to synthesize a series of MMOs including single‐component MMOs and multi‐component MMOs (e.g., doped MMOs, composite MMOs, and polymetallic oxide) with high crystallinity and remarkable porous properties by grinding and heating raw materials. Compared with the traditional solution self‐assembly process, the avoidance of solvents in this method not only greatly increases the yield of target products and synthesis efficiency, but also reduces the environmental pollution and the consumption of cost and energy. We believe the presented approach will pave a new avenue for scalable production of advanced mesoporous materials for various applications.

Xiong, Hailong↗

Demonstrating Hierarchical System Development With the Common Community Physics Package Single‐Column Model: A Case Study Over the Southern Great Plains

This study demonstrates a specific application of the hierarchical system development (HSD) approach to investigate, analyze, and attribute model issues within the Unified Forecast System (UFS), with a focus on process isolation. By evaluating a non‐precipitating, shallow cumulus case at the Atmospheric Radiation Measurement Southern Great Plains site in the UFS global forecast against the observation, the investigation identifies a warmer and deeper daytime convective planetary boundary layer (PBL) and misrepresented nocturnal PBL transition. Hypothesis testing, which employs the Common Community Physics Package (CCPP) single‐column model (SCM) and uses the same physics as the UFS global model, confirms that these issues are attributed to the model physics and initialization. Specifically, misrepresented PBL processes are linked to problematic surface condition and a lack of cloud formation, which may stem from deficiencies in PBL and cloud microphysics parameterizations and their interactions. The UFS initial condition contributes to an earlier, excessively collapsed daytime convective boundary layer and a lack of decoupling between the stable boundary layer and residual layer late in the afternoon. This work introduces an avenue for the community to engage with the application of HSD, along with the CCPP and CCPP SCM, to understand the interplay of model physics, disentangle the roles of model components, as well as facilitate model and forecast improvement.

54 ENVIRONMENTAL SCIENCES↗

Knowledge-matching based computational framework for genome-scale metabolic model refinement

Genome-scale metabolic models (GEMs) are mathematically structured knowledge base reconstructed from annotated genome of different organisms. With the advancement of next-generation sequencing technology, many organisms have had their genomes sequenced. However, obtaining a high-quality GEM is highly time-consuming, even with the introduction of several genome-scale reconstruction tools that offer automated draft network generation and gap filling. It has been recognized that the iterative process of manual curation and refinement is the limiting step of GEM development, and how to expedite the GEM refinement is still an open question. As cellular metabolism is a complex system with very high degree of freedom and redundancy, the principles and techniques developed in process systems engineering can be adapted to expedite GEM refinement. In this paper we present a knowledge-matching based computation framework for GEM refinement, and demonstrate the effectiveness of the proposed solution using the refinement of a GEM for Clostridium tyrobutyricum.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Fabrication of THz corrugated wakefield structure and its high power test

We present overall process for developing terahertz (THz) corrugated structure and its beam-based measurement results. 0.2-THz corrugated structures were fabricated by die stamping method as the first step demonstration towards GW THz radiation source and GV/m THz wakefield accelerator. 150-μm thick disks were produced from an OFHC (C10100) foil by stamping. Two types of disks were stacked alternately to form 46 mm structure with ~ 170 corrugations. Custom assembly was designed to provide diffusion bonding with a high precision alignment of disks. The compliance of the fabricated structure have been verified through beam-based wakefield measurement at Argonne Wakefield Accelerator Facility. Both measured longitudinal and transverse wakefield showed good agreement with simulated wakefields. Measured peak gradients, 9.4 MV/m/nC for a long single bunch and 35.4 MV/m/nC for a four bunch trains, showed good agreement with the simulation.

43 PARTICLE ACCELERATORS↗

Modification of Wool Fibers via Base/Cationic Detergent Pretreatment and Transglutaminase-mediated Reaction of Keratin

The surface modification of wool fibers is an important part of the textile industry to add functionality and stability to wool products. In this study, we developed a process utilizing a base/cationic surfactant solution pretreatment followed by an enzyme-mediated keratin crosslinking reaction to modify the wool fibers. Changes in water contact angle demonstrated the successful transformation of the hydrophobic wool surface to a more hydrophilic one after soaking in sodium carbonate solution containing hexadecyltrimethylammonium bromide (CTAB). The treated fabrics were further characterized by colorimetry and fluorescent spectrometry. Results showed that the pretreatment increased the yellowness of fabrics and caused some structural changes among certain amino acids, such as tryptophan and cystine. Keratin extracted from coarse wool fibers was further applied on pretreated fabrics through a microbial transglutaminase (mTGase) mediated reaction under mild conditions. Morphological characterization via SEM demonstrated the effective coverage of keratin on the scales of wool. The current method may provide an alternative processing protocol to modify wool fibers and improve the quality and performance of wool products.

36 MATERIALS SCIENCE↗

Methodology for interpretable reinforcement learning model for HVAC energy control

Deep reinforcement learning (DRL) approaches have been used in various application areas to improve efficiency, optimization, or automation. However, very little is known about how the DRL algorithms make decisions and what features affect their performance. Using a case study of a DRL based Heating, Ventilation and Air Conditioning (HVAC) optimization methodology, we demonstrate how we can address these challenges by applying interpretability tools and systematically exploring the model inputs for better understanding the DRL behaviour and decision making process. We developed a methodology for interpretable reinforcement learning and evaluated our approach in real-world house located in Knoxville, TN. Our findings explain the reasoning behind DRL-based optimization decisions under different circumstances which has been discussed and confirmed by the experts in the field.

Kotevska, Olivera↗

Sequential multidimensional heteroepitaxy of chalcogen-sharing 3D ZnSe and 2D MoSe 2 with quasi van der Waals interface engineering

Two-dimensional (2D) materials are emerging as a promising platform for epitaxial growth, largely free from the constraints of lattice constant and thermal expansion coefficient mismatches. Among them, transition metal dichalcogenides (TMDs), known for their superior electrical properties, are ideal for ultrathin semiconductor applications. Their unique epitaxial characteristics enable seamless integration with 3D materials, facilitating the development of gate stacks and heterojunction devices. In this regard, developing a process for growing high-quality 3D epitaxial materials before and after the growth of 2D TMDs and understanding the 2D/3D interface are crucial. This study demonstrates the sequential growth of fully epitaxial ZnSe/MoSe 2 /ZnSe heterostructures using metal-organic chemical vapor deposition. ZnSe and MoSe 2 , sharing chalcogen elements, enable large-area quasi van der Waals epitaxy with sharp interfaces without intermediate phase. Multiscale analysis involving transmission electron microscopy and density functional theory calculation reveals lattice commensurability, van der Waals gaps, termination, and interfacial reconstruction. Understanding these interactions is crucial for advancing multidimensional integration of 2D and 3D materials.

36 MATERIALS SCIENCE↗

A Pilot-Scale Evaluation of Natural Gas-Based Foam at Elevated Pressure and Temperature Conditions

Abstract Nitrogen (N2) and Carbon Dioxide (CO2) foams have been used as hydraulic fracturing fluids for several decades to reduce water usage and minimize damage in water-sensitive reservoirs. These foam treatments require gases to be liquefied and transported to site. An alternative approach would be to use natural gas (NG) that is readily available from nearby wells, pipelines, and processing facilities as the internal, gaseous phase to create a NG-based foam. Hydraulic fracturing with NG foam is a relatively inexpensive option, makes use of an abundant and often wasted resource, and may even provide production benefits in certain reservoirs. As part of an ongoing development project sponsored by the Department of Energy (DOE), the surface process to create NG foam is being developed and the properties of NG foam are being explored. This paper presents recent results from a rigorous pilot-scale demonstration of NG foam over a range of operating scenarios relevant to surface and bottomhole conditions with a variety of base-fluid mixtures. The Pilot-scale Foam Test Facility (PFTF) used in these investigations is first described. The PFTF is capable of generating foamed fluids at pressures up to 7,500 psig and at temperatures in excess of 300°F. Then, results from several investigations aimed at proving NG foam at conditions relevant to the field are presented. NG foam was characterized using rheology measurements and flow visualization techniques. Experiments were performed to investigate the texture and stability of NG foam generated by two different mixing methods: one using a custom designed tee to match mixing velocities in the field where the gas phase is jetted into the aqueous stream, and another to ensure comprehensive mixing for laboratory analysis. Parametric studies were conducted to explore the effects of flow rate, foam quality, and temperature on the stability of NG foam. Moreover, different fluid preparations were used to investigate the effect of base fluid and additive concentrations on the stability of NG foams. Additional laboratory studies that investigated foam stability with produced water and multicomponent NG mixtures are also reported. The NG foams explored in these investigations exhibited typical, shear-thinning behavior observed in rheological studies of N2- and CO2-based foams. The measured viscosity and observed stability indicate that NG foams are well suited for fracturing applications. Like other foams, NG foam exhibits sensitivity to operating temperature characterized by a decrease in apparent viscosity as temperature increases. Rapid foam breakdown was observed at significantly elevated temperatures exceeding 290°F. In addition to fluid characterization, these investigations also yielded several key lessons that should be applied to future field demonstrations of NG foam.

Beck, Griffin↗

Improving the Cost-Effectiveness of Algal CO2 Utilization by Synergistic Integration With Power Plant and Wastewater Treatment Operations

Creating an economic demand for carbon utilization products will require lowering the overall cost of the products to compete within the current market. Photosynthetic uptake of carbon dioxide is an emerging pathway for product development in the animal feed market that globally amounts to over 400 Billion USD and is expected to continue growing. This project aims to continue the development of a process that utilizes carbon dioxide while increasing the cost competitiveness of algae as an animal feed product. The overall goal of the project is to demonstrate an engineering-scale open raceway pond algae cultivation system (180 m2) including integration of technologies that utilize coal-fired power plant CO2 and wastewater nutrient inputs. The system is designed to maximize the cost-effectiveness and environmental benefits of algal biomass production for commodity animal feed.

20 FOSSIL-FUELED POWER PLANTS↗

Tardigrade: Summary (LL20-AM-sensor)

Tardigrade is an effort to create small, passive remote sensor for material detection and identification. The microbolometer based sensor design uses custom bandpass filter bands combined with tuned thermal expansion materials in a ruggedized lens housing to provide passive mechanical correction for optical changes across a wide temperature range. This requires developing computational tools to model and predict thermal performance of meta-materials composed of multiple structured base materials and void-space, along with matching and developing 3D print technology to demonstrate the housing. Current efforts in the project are in 3 areas: material design algorithm development (transitioning into full 3D material design space), multi-material additive manufacturing process exploration, and sensor/optics design and engineering.

42 ENGINEERING↗

Continuous Fiber Bath Treatments at Pilot Scale: A Novel Testbed System

The technical demands on high performance textiles continues to expand, and the research community has answered the call with innovative fiber bath treatments for enhanced properties and sizings for improved composites. However, little translation to greater scale has been demonstrated. To fill this gap, a novel, multifunctional system has been developed to explore polymer fiber treatment methods, the deployment of nanoadditive coatings and other sizings, and smart processing methods at the pilot scale. Continuous tows of fibers can be passed through a temperature-controlled, crossflow bath with an immersion residence time exceeding 2 hours. The modular system is resistant to corrosive solutions, includes additional inline stations for washing and drying after processing, is equipped with a bevy of sensors, pumps, and valves monitored and controlled by a LabView program, and can be fully contained in a standard lab fume hood. This new testbed system, when coupled with high fidelity materials characterization methods, will enable rapid evaluation of new fiber treatment methods at pilot-scale.

36 MATERIALS SCIENCE↗

Rapid Alloy Selection and Additive Manufacturing of Nickel Based Superalloys

In this work the rapid alloy selection and subsequent processability via additive manufacturing of nickelbased superalloys was investigated. Rapid alloy selection protocols developed within the project produced two viable nickel-based superalloys. This phase I CRADA demonstrates a viable route for selecting new nickel-based superalloys for additive manufacturing.

36 MATERIALS SCIENCE↗

Rapid Alloy Selection and Additive Manufacturing of Nickel-Based Superalloys

In this work the rapid alloy selection and subsequent processability via additive manufacturing of nickelbased superalloys was investigated. Rapid alloy selection protocols developed within the project produced two viable nickel-based superalloys. This phase I CRADA demonstrates a viable route for selecting new nickel-based superalloys for additive manufacturing.

36 MATERIALS SCIENCE↗

Rolling Behavior of Surface Tagged Aluminum 6061 using Photoluminescent Oxides

Physical tagging of nuclear fuel is potentially one way of tracking throughout the fuel lifecycle. The process of tagging can take many forms, but one promising method is to embed a small amount of photoluminescent particles in the surface of a material which are not detectable under normal illumination but are readily visible under excitation by ultraviolet light. The goal of this project was to explore the potential to tag simulated nuclear fuel cladding with small ceramic particles, via laser beam welding or gas tungsten arc welding, and measure the photoluminescent response. Surface tagging using this method has demonstrated viability and detectability throughout this project; work in FY24 focused on the survivability of these tags through subsequent deformation processing similar to what taggants in a fuel manufacturing environment would be subjected to. This work demonstrated that particles are readily visible in the as-welded state (i.e., before subsequent rolling treatment to represent mechanical processing of a fuel material), but visibility is reduced as the deformation is induced. Despite the reduction in photoluminescence, the taggants are still visible after rolling processes are performed, making this surface tagging technique a promising candidate for nuclear fuel cladding tagging. This work demonstrated, though, that targeted optimization work would be necessary to develop a robust taggant depending on the fidelity and luminescent properties required.

36 MATERIALS SCIENCE↗

The Art of Automation: Translating Electron Microscopy Workflows Into Automated Processes

Acquiring data using a scanning transmission electron microscope (STEM) is a complex, multi-step process. The intricacy of the process depends on the type of sample, composition of the material, desired results of the experiment, resolution requirement and other experimental factors. Each experiment presents unique complications, such as sample drift and contamination, that the microscopist must consider when acquiring data. All these challenges are handled fluidly and expertly by experienced microscopists, but to reach new levels of innovation in material development, including greater reproducibility, throughput, and precision, the automation of these workflows is essential. The initial phase of this work involved translating intuition-based workflows into discrete, programmable steps. Some common key stages in STEM workflows are the initial tuning, scanning the sample for areas of interest, and then acquiring the data. Each stage can be broken further into specific parameter adjustments, such as aberration correction and dwell time optimization, depending on the experiment. When deconstructing various experiments each step was assessed for automation feasibility based on the amount of real time operator decisions. There are steps that lend themselves to automation more readily than others, such as course focusing and sample screening, but there is potential for full automation of all stages with time. As an initial step, an automated montage routine was developed, allowing for the efficient acquisition of large portions of the sample without requiring continuous intervention from the operator. The automation of this small process of the procedure demonstrates the value of this capability. A major challenge in automation arises from discrepancies between commanded, reported and actual stage movements. Using systematic tests, stage movement was quantified. This error can be corrected algorithmically for more accurate workflows in the future. Expanding automation capabilities would result in larger, more efficient data acquisition which allows for more robust statistical analysis. Additionally, this work lays the groundwork for a closed loop system where machine learning algorithms would intake automatically acquired data and make real time decisions. By progressively automating this instrument, this work establishes the foundation for fully automated experimentation in transmission electron microscopy.

97 MATHEMATICS AND COMPUTING↗