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Potential Size of and Value Proposition for H2@Scale Concept

The H2@Scale concept is focused on developing hydrogen as an energy carrier and using hydrogen's properties to improve the national energy system. Specifically hydrogen has the abilities to (1) supply a clean energy source for industry and transportation and (2) increase the profitability of variable renewable electricity generators such as wind turbines and solar photovoltaic (PV) farms by providing value for otherwise potentially-curtailed electricity. Thus the concept also has the potential to reduce oil dependency by providing a low-carbon fuel for fuel cell electric vehicles (FCEVs), reduce emissions of carbon dioxide and pollutants such as NOx, and support domestic energy production, manufacturing, and U.S. economic competitiveness. The analysis reported here focuses on the potential market size and value proposition for the H2@Scale concept. It involves three analysis phases: 1. Initial phase estimating the technical potential for hydrogen markets and the resources required to meet them; 2. National-scale analysis of the economic potential for hydrogen and the interactions between willingness to pay by hydrogen users and the cost to produce hydrogen from various sources; and 3. In-depth analysis of spatial and economic issues impacting hydrogen production and utilization and the markets. Preliminary analysis of the technical potential indicates that the technical potential for hydrogen use is approximately 60 million metric tons (MMT) annually for light duty FCEVs, heavy duty vehicles, ammonia production, oil refining, biofuel hydrotreating, metals refining, and injection into the natural gas system. The technical potential of utility-scale PV and wind generation independently are much greater than that necessary to produce 60 MMT / year hydrogen. Uranium, natural gas, and coal reserves are each sufficient to produce 60 MMT / year hydrogen in addition to their current uses for decades to centuries. National estimates of the economic potential of hydrogen production using steam methane reforming of natural gas, high temperature electrolysis coupled with nuclear power plants, and low temperature electrolysis are reported. To generate the estimates, supply curves for those technologies are used. They are compared to demand curves that describe the market size for hydrogen uses and willingness to pay for that hydrogen. Scenarios are developed at prices where supply meets demand and are used to estimate energy use, emissions, and economic impacts.

13 HYDRO ENERGY↗

Cummins R-SOFC System Development

The overall purpose of this project was to reduce the Reversible-Solid Oxide Fuel Cell (R-SOFC) system cost by developing two technologies, an improved cell design and the incorporation of an ejector in the fuel recycle loop instead of a blower. A Simulink model of the baseline SOFC system was developed and calibrated with experimental test data. The R-SOFC system model was built by integrating GT Suite developed models of the steam generation components into the baseline Simulink SOFC system model. The ability to run the stack in SOEC operating mode was also added to the model. The system model was used to explore the ability of the R-SOFC system to meet operational constraints on Steam/Carbon ratio and H2 concentration on the fuel side electrode. A CFD ejector model was developed and used to explore a range of ejector design parameters, leading to the final ejector design that was prototyped for testing. A prototype steam ejector was first tested in a laboratory environment using room temperature air. The steam ejector was subsequently tested using the full hot recycle loop with all relevant heat exchangers and steam generation components. The test conditions utilized temperatures, pressures, and flow rates expected in an R-SOFC application. Throughout the experimental testing work, ejector performance test data was used to improve and then validate the CFD ejector model. A CFD cell model was developed and used to optimize thermal gradients, voltage, and cost of a new cell substrate design. A CFD comparison of co-flow and cross-flow cell designs informed the decision to use a co-flow design for the new cell substrate. Multiple rounds of CFD simulation were used to improve the cell design to minimize the variation in air and fuel distribution across cell channels and to minimize the variation in air and fuel distribution across different cells in the stack. A few prototypes of the new cell substrate design were produced and validated in a laboratory environment by thermally spraying and verifying that they met established manufacturing specifications. The cell manufacturing process was adjusted in order to bring these metrics within acceptable tolerances. Cummins’ internal calculations show that the new cell design reduces cost ~50% compared to the baseline cell, while the ejector + superheater/boiler concept reduces cost of the recycle loop by ~40%. The impact of these cost reductions on the cost of producing H2 will depend on the specific system where they are applied. Therefore, a Techno-Economic Analysis was completed using system cost as a variable, and showing how the NREL Current and Future system costs translate into H2 production cost.

Henrichsen, Lars↗

Mechanism of Catalytic O2 Reduction by Iron Tetraphenylporphyrin

The catalytic reduction of O2 to H2O is important for energy transduction in both synthetic and natural systems. Herein, we report a kinetic study of O2 reduction catalyzed by iron tetraphenylporphyrin in N,N-dimethylformamide using decamethylferrocene as a soluble reductant and para-toluenesulfonic acid (pTsOH) as the proton source. Reduction of the ferric porphyrin, [FeIII(TPP)]+ , forms the ferrous porphyrin, FeII(TPP), which binds O2 reversibly to form the ferric-superoxide porphyrin complex, FeIII(TPP)(O2 •?). The temperature dependence of both the electron transfer and O2 binding equilibrium constants have been determined. Kinetic studies over a range of concentrations and temperatures show that the catalyst resting state changes during the course of each catalytic run, necessitating the use of global kinetic modeling to extract rate constants and kinetic barriers. The rate-determining step in oxygen reduction is protonation of FeIII(TPP)(O2•?) by pTsOH, which proceeds with a substantial kinetic barrier. Computational studies indicate that this barrier for proton transfer arises from an unfavorable pre-association of the proton donor with the superoxide adduct and a transition state that requires significant desolvation of the proton donor. Together, these results are the first example of oxygen reduction by iron tetraphenylporphyrin where the pre-equilibria between ferric, ferrous, and ferric-superoxide intermediates have been quantified under catalytic conditions. This work gives a generalizable model for the mechanism of iron porphyrin-catalyzed ORR and provides an unusually complete mechanistic study of an ORR reaction. More broadly, this study also highlights the kinetic challenges for proton transfer to catalytic intermediates in organic media.

Pegis, Michael L.↗

High-Pressure Synthesis: A New Frontier in the Search for Next-Generation Intermetallic Compounds

The application of high pressure adds an additional dimension to chemical phase space, opening up an unexplored expanse bearing tremendous potential for discovery. Our continuing mission is to explore this new frontier, to seek out new intermetallic compounds and new solid-state bonding. Simple binary elemental systems, specifically those composed of pairs of elements that do not form compounds under ambient pressures, can yield novel crystalline phases under compression. Thus, high-pressure synthesis can provide access to solid-state compounds that cannot be formed with traditional thermodynamic methods. An emerging approach for the rapid exploration of composition–pressure–temperature phase space is the use of hand-held high-pressure devices known as diamond anvil cells (DACs). These devices were originally developed by geologists as a way to study minerals under conditions relevant to the earth’s interior, but they possess a host of capabilities that make them ideal for high-pressure solid-state synthesis. Of particular importance, they offer the capability for in situ spectroscopic and diffraction measurements, thereby enabling continuous reaction monitoring—a powerful capability for solid-state synthesis. Here, we offer an overview of this approach in the context of research we have performed in the pursuit of new intermetallic compounds. We start with a discussion of pressure as a fundamental experimental variable that enables the formation of intermetallic compounds that cannot be isolated under ambient conditions. We then introduce the DAC apparatus and explain how it can be repurposed for use as a synthetic vessel with which to explore this phase space, going to extremes of pressure where no chemist has gone before. The remainder of the Account is devoted to discussions of recent experiments we have performed with this approach that have led to the discovery of novel intermetallic compounds in the Fe–Bi, Cu–Bi, and Ni–Bi systems, with a focus on the cutting-edge methods that made these experiments possible. We review the use of in situ laser heating at high pressure, which led to the discovery of FeBi2, the first binary intermetallic compound in the Fe–Bi system. Our work in the Cu–Bi system is described in the context of in situ experiments carried out in the DAC to map its high-pressure phase space, which revealed two intermetallic phases (Cu11Bi7 and CuBi). Finally, we review the discovery of β-NiBi, a novel high-pressure phase in the Ni–Bi system. We hope that this Account will inspire the next generation of solid-state chemists to boldly explore high-pressure phase space.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Preliminary Workforce Development and Environmental and Co-use Management Plans for a Floating Offshore Wind Platform - CRADA 609 (Final Report)

Pacific Northwest National Laboratory (PNNL) provided technical assistance to Glosten, Inc. and its affiliate, PelaStar, LLC to advance the development of their floating offshore wind (FOSW) platform. PNNL provided guidance and assessment in two areas that are important to address in the development of FOSW platforms: (1) workforce development and (2) environmental impacts and ocean co-use considerations. This work was funded by the U.S. Department of Energy’s (DOE) Wind Energy Technologies Office (WETO) through Phase 2 of the FLoating Offshore Wind ReadINess (FLOWIN) Prize. It should be noted that the Plans presented in this report are specific to the PelaStar tension-leg platform (TLP) and may not be applicable to all FOSW platforms. Workforce development and environmental/co-use impacts are highly dependent on the geographical region in which activities take place. At the request of PelaStar, PNNL focused on two regions where development may take place: the Gulf of Maine and Northern California. PNNL generated a preliminary Workforce Development Plan for PelaStar, which includes estimated job numbers and skillsets required to establish a workforce to manufacture, install, and operate their platform as part of FOSW projects. The Plan offers methods to increase diversity, equity, and inclusion practices when developing a new workforce and includes colleges and training centers for potential recruitment. Both positive and negative impacts to communities are evaluated, with potential mitigation strategies for reducing negative impacts. The structure of Community Benefit Agreements and Project Labor Agreements are discussed, noting the limitations of the role of a platform manufacturer versus the offshore wind developer. PNNL also drafted a preliminary Environmental and Co-Use Management Plan that serves as a guide to preparing an environmental assessment related to the installation and operation of PelaStar’s unique TLP design, including its potential ecological, socioeconomic, and emissions impacts. The Plan summarizes information on relevant regulatory requirements, potential impact producing factors, monitoring and mitigation measures, and physical and biological resources in the Gulf of Maine and Northern California. One of the primary perceived benefits of the PelaStar TLP is its reduced footprint due to its tensioned tendons versus catenary or taut moorings, but more research must be done as there are no studies on PelaStar’s TLP system to-date. The section also highlights ocean co-use considerations for PelaStar’s TLP system, specifically for fisheries, including existing perspectives, methods, examples, and limitations. The PNNL team established through this preliminary work and review of available literature and resources that there is not yet much research or planning around FOSW. With FOSW being a new industry, many of the findings and planning are adapted from fixed bottom offshore wind, which itself is only just taking off in the United States. More research is needed to establish best practices for workforce development and to assess environmental and ocean co-use impacts and mitigation approaches.

17 WIND ENERGY↗

Evaluating the Effect of Bottom Trawls in Pamlico River, North Carolina

The objective of this study is to evaluate and quantify the amount of sediment resuspension on shallow estuarine systems, with specific comparisons between natural and trawling-induced events. This aids in the assessment of water quality and sediment processes on a specific coastal system of North Carolina, providing a basis for future studies on other shallow estuarine ecosystems. Categorizing these sediment processes into distinct individual units (e.g. natural vs. anthropogenic) is an important component toward fully realizing proper management of our coastal habitats. Heavy trawling activity along North Carolina s coast is one of the major obstacles in management plans. Therefore, it is imperative to quantify the effects of trawling to gain a more specific understanding of the human impact on estuaries.

Corbett, D. Reide↗

Liquid Metals as Plasma-facing Materials for Fusion Energy Systems: From Atoms to Tokamaks

The objective of our studies was to advance our fundamental understanding of liquid metals as plasma-facing materials for fusion energy systems, with a broad scope: from atoms to tokamaks. The flow of liquid metals offers solutions to significant problems of the plasma-facing materials for fusion energy systems. Candidate metals include lithium, tin, gallium, and their eutectic combinations. However, such liquid metal solutions can only be designed efficiently if a range of scientific and engineering issues are resolved that require advances in fundamental fluid dynamics, materials science and surface science. In our research we investigated a range of significant and timely problems relevant to current and proposed engineering designs for fusion reactors, including high-heat flux configurations that are being considered by leading fusion energy groups world-wide. Using experimental and theoretical tools spanning atomistic to continuum descriptions of liquid metals, and bridging surface chemistry, wetting/dewetting and flow, our research has advanced the science and engineering of fusion energy materials and systems. Specifically, we developed a combined experimental and theoretical program to investigate flows of liquid metals in fusion-relevant geometries, including equilibrium and stability of thin-film flows, e.g. wetting and dewetting, effects of electromagnetic and thermocapillary fields on liquid metal thin-film flows, and how chemical interactions and the properties of the surface are influenced by impurities and in turn affect the surface wetting characteristics, the surface tension, and its gradients. Because high-heat flux configurations produce evaporation and sputtering, which forces rearrangement of the liquid, and any dewetting exposes the substrate to damage from the plasma, our studies addressed such evaporatively driven liquid flows and measured and simulated properties of the different bulk phases and material interfaces. The range of our studies included (i) quantum mechanical calculations that allow inclusion of many thousands of atoms for the characterization of the interface of liquid metals exposed to continuous bombardment by deuterium and tritium as expected in fusion, (ii) molecular dynamics studies of the phase behavior of liquid metals, which (a) utilize thermodynamic properties computed using our quantum mechanical calculations and (b) establish material and wetting properties of the liquid metals, including relevant eutectics, (iii) experimental investigations of the surface science of liquid metals, interacting both with the solid substrate as well as gaseous species, and (iv) fluid dynamical studies that incorporate the material and surface science results of (ii) and (iii) in order to characterize flow in capillary porous materials and the thin-film flow along curved boundaries, both of which are potentially major components of plasma-facing materials. The outcome of these integrated studies was new understanding that enables developing design rules useful for future developments of the plasma-facing components critical to the success of fusion energy systems.

36 MATERIALS SCIENCE↗

Polyhydroxyalkanoates in emerging recycling technologies for a circular materials economy

Circular polymer systems, specifically polyesters operating through chemical and biological technologies, are approaching a critical moment of industrial adoption and scale-up feasibility. At the same time, polyhydroxyalkanoate (PHA) production, scale-up, and resulting material development is converging toward commodity applications. The current PHA end-of-life philosophy, however, focalizes leveraging inherent biodegradability to circumvent plastic waste accumulation. If indeed a substantial replacement of incumbent single-use plastics with PHA alternatives is to be met in commercial manufacture, we emphasize the importance of linking PHA development with feasible polymer recycling technologies. In other words, a PHA materials economy is significantly more carbon- and cost-favorable when efficient mechanical (reprocessing), chemical (deconstruction, depolymerization), or biological (enzymatic) recycling is prioritized over biodegradation or composting. In this perspective, we discuss strategies for PHA recyclable-by-design principles, guidable by developing machine learning tools, as well as material compatibility with closed-loop recycling technologies. Additionally, we posit compelling life-cycle assessment incentives for adopting polymer reclamation over competing pathways. Ultimately, we hope this narrative further inspires the alignment between PHA design with growing calls for a circular material economy.

36 MATERIALS SCIENCE↗

Hydrogen Production System Scaling Using a High-Fidelity Simulation-Optimization Framework

Proton exchange membrane (PEM) electrolyzers are widely used for hydrogen production, yet few validated, high-fidelity tools can reliably guide scale-up. Using measured performance from a 50-hour hardware-in-the-loop pilot test, a physics-based, plant-level model of a 1.25 MW PEM electrolyzer and its balance-of-plant (BoP) subsystems is developed and validated. The model couples electrochemistry and thermal/flow submodels and is calibrated against pilot test data via a genetic algorithm (GA) workflow. Validation yields a mean absolute percentage error (APE) of 0.43% for cell voltage and stack power. Two scale-out strategies are then benchmarked under a common 7-day wind-and-photovoltaic (PV) profile: (i) linear duplication of 1.25 MW blocks and (ii) shared-BoP architectures. Sharing BoP between stacks reduces BoP energy by 27% at 10 MW and 34% at 100 MW (vs. linear duplication) and improves system specific energy consumption (SEC) to 52.9 and 52.6 kWh/kg, respectively (from 54.0 kWh/kg with linear duplication). Partial-load studies (25-100% set-point) show that cumulative hydrogen production remains nearly constant down to 50% load because all cases use the same weekly renewable-energy input. Below 50%, the power cap limits how much energy can be used within 168 h, which reduces hydrogen output. The model further indicates that the practical operating optimum lies between 50% and 85% load, where efficiency gains begin to appear without significant loss in hydrogen output. Moreover, the efficiency gains at lower loads are offset by reduced production. The validated framework supports scenario-based engineering trade-off studies for large configurations (10-100 MW) and for operating policies under variable renewables.

08 HYDROGEN↗

Final Technical Report on Quantifying Dependability Attributes of Software Based Safety Critical Instrumentation and Control Systems in Nuclear Power Plants

With the current transition from analog to digital instrumentation and control systems in nuclear power plants, the number and variety of software-based systems have significantly increased. The sophisticated nature and increasing complexity of software raises trust in these systems as a significant challenge. The trust placed in a software system is typically termed software dependability. Software dependability analysis faces uncommon challenges since software systems’ characteristics differ from those of hardware systems. The lack of systematic science-based methods for quantifying the dependability attributes in software-based instrumentation as well as control systems in safety critical applications has proved itself to be a significant inhibitor to the expanded use of modern digital technology in the nuclear industry. Dependability refers to the ability of a system to deliver a service that can be trusted. Dependability is commonly considered as a general concept that encompasses different attributes, e.g., reliability, safety, security, availability and maintainability. Dependability research has progressed significantly over the last few decades. For example, various assessment models and/or design approaches have been proposed for software reliability, software availability and software maintainability. Advances have also been made to integrate multiple dependability attributes, e.g., integrating security with other dependability attributes, measuring availability and maintainability, modeling reliability and availability, quantifying reliability and security, exploring the dependencies between security and safety and developing integrated analysis models. However, there is still a lack of understanding of the dependencies between various dependability attributes as a whole and of how such dependencies are formed. To address the need for quantification and give a more objective basis to the review process -- therefore reducing regulatory uncertainty -- measures and methods are needed to assess dependability attributes early on, as well as throughout the life-cycle process of software development. In this research, extensive expert opinion elicitation is used to identify the measures and methods for assessing software dependability. Semi-structured questionnaires were designed to elicit expert knowledge. A new notation system, Causal Mechanism Graphing, was developed to extract and represent such knowledge. The Causal Mechanism Graphs were merged, thus, obtaining the consensus knowledge shared by the domain experts. In this report, we focus on how software contributes to dependability. However, software dependability is not discussed separately from the context of systems or socio-technical systems. Specifically, this report focuses on software dependability, reliability, safety, security, availability, and maintainability. Our research was conducted in the sequence of stages found below. Each stage is further examined in its corresponding chapter. Stage 1 (Chapter 2): Elicitation of causal maps describing the dependencies between dependability attributes. These causal maps were constructed using expert opinion elicitation. This chapter describes the expert opinion elicitation process, the questionnaire design, the causal map construction method and the causal maps obtained. Stage 2 (Chapter 3): Elicitation of the causal map describing the occurrence of the event of interest for each dependability attribute. The causal mechanisms for the “event of interest” were extracted for each of the software dependability attributes. The “event of interest” for a dependability attribute is generally considered to be the “attribute failure”, e.g. security failure. The extraction was based on the analysis of expert elicitation results obtained in Stage 1. Stage 3 (Chapter 4): Identification of relevant measurements. Measures for the “events of interest” and their causal mechanisms were obtained from expert opinion elicitation for each of the software dependability attributes. The measures extracted are presented in this chapter. Stage 4 (Chapter 5): Assessment of the coverage of the causal maps via measures. Coverage was assessed to determine whether the measures obtained were sufficient to quantify software dependability, and what measures are further required. Stage 5 (Chapter 6): Identification of “missing” measures and measurement approaches for concepts not covered. New measures, for concepts that had not been covered sufficiently as determined in Stage 4, were identified using supplementary expert opinion elicitation as well as literature reviews. Stage 6 (Chapter 7): Building of a detailed quantification model based on the causal maps and measurements obtained. Ability to derive such a quantification model shows that the causal models and measurements derived from the previous stages (Stage 1 to Stage 5) can form the technical basis for developing dependability quantification models. Scope restrictions have led us to prioritize this demonstration effort. The demonstration was focused on a critical system, i.e. the reactor protection system. For this system, a ranking of the software dependability attributes by nuclear stakeholders was developed. As expected for this application, the stakeholder ranking identified safety as the most critical attribute to be quantified. A safety quantification model limited to the requirements phase of development was built. Two case studies were conducted for verification. A preliminary control gate for software safety for the requirements stage was proposed and applied to the first case study. The control gate allows a cost effective selection of the duration of the requirements phase.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

A Multirange Vehicle Speed Prediction With Application to Model Predictive Control-Based Integrated Power and Thermal Management of Connected Hybrid Electric Vehicles

Abstract Connectivity and automated driving technologies have opened up new research directions in the energy management of vehicles which exploit look-ahead preview and enhance the situational awareness. Despite this advancement, the vehicle speed preview that can be obtained from vehicle-to-vehicle/infrastructure (V2V/I) communications is often limited to a relatively short time-horizon. The vehicular energy systems, specifically those of the electrified vehicles, consist of multiple interacting power and thermal subsystems that respond over different time-scales. Consequently, their optimal energy management can greatly benefit from long-term speed prediction beyond that available through V2V/I communications. Accurately extending the look-ahead preview, on the other hand, is fundamentally challenging due to the dynamic nature of the traffic environment. To address this challenge, we propose a data-driven multirange vehicle speed prediction strategy for arterial corridors with signalized intersections, providing the vehicle speed preview for three different ranges, i.e., short-, medium-, and long-range. The short-range preview is obtained by V2V/I communications. The medium-range preview is realized using a neural network (NN), while the long-range preview is predicted based on a Bayesian network (BN). The predictions are updated in real-time based on the current state of traffic and incorporated into a multihorizon model predictive control (MH-MPC) for integrated power and thermal management (iPTM) of connected vehicles. The results of design and evaluation of the performance of the proposed data-informed MH-MPC for iPTM of connected hybrid electric vehicles (HEVs) using traffic data for real-world city driving are reported.

Automation & Control Systems↗

Unveiling the Morphological and Physical Mechanism of Burn–in Loss Alleviation by Ternary Matrix Toward Stable and Efficient All–Polymer Solar Cells

All–polymer solar cells (All–PSCs) are considered the most promising candidate in achieving both efficient and stable organic photovoltaic devices, yet the field has rarely presented an in–depth understanding of corresponding device stability while efficiency is continuously boosted via the innovation of polymer acceptors. Herein, a ternary matrix is built for all–PSCs with optimized morphology, improved film ductility and importantly, boosted efficiency and better operational stability than its parental binary counterparts, as a platform to study the underlying mechanism. The target system PQM–Cl:PTQ10:PY–IT (0.8:0.2:1.2) exhibits an alleviated burn–in loss of morphology and efficiency under light soaking, which supports its promoted device lifetime. The comprehensive characterizations of fresh and light–soaked active layers lead to a clear illustration of opposite morphological and physical degradation direction of PQM–Cl and PTQ10, thus resulting in a delicate balance at the optimal ternary system. Specifically, the enlarging tendency of PQM–Cl and shrinking preference of PTQ10 in terms of phase separation leads to a stable morphology in their mixing phase; the hole transfer kinetics of PQM–Cl:PY–IT host is stabilized by incorporating PTQ10. Finally, this work succeeds in reaching a deep insight into all–PSC's stability promotion by a rational ternary design, which booms the prospect of gaining high–performance all–PSCs.

14 SOLAR ENERGY↗

Engineering Active Sites of Metal/Metal Oxide Catalysts by Oxide Ligand Overlayers

Abstract Engineering sites of supported metal catalysts is essential to enhancing activity and selectivity. Such enhancement is typically achieved by particle size modification, surface alloying, or attaching molecular ligands. Yet, control strategies for complex, multifunctional molecules and catalysts, where selectivity is crucial, are lacking. Here, we demonstrate that submonolayer WO x with tunable coverage preferentially decorates well‐coordinated Pt terrace sites as a stable ligand. By combining experimental kinetics with probe molecules, in situ spectroscopies, and first‐principles modeling, we show that the WO x coverage on Pt modifies the metal‐to‐acid site balance while retaining the acid strength intact and results in optimal reactivity for metal‐acid catalyzed reactions at a specific metal, size, and support‐dependent WO x coverage. The oxide can also alter the reactant adsorption mode, reversing selectivity and pathways from terrace‐ to step‐dominated, as evidenced in furfural decarbonylation and hydrogenation. The insights open avenues for improving metal/metal oxide catalysts beyond the specific system.

Zhou, Jiahua↗

A Co-design Framework for Online Data Analysis and Reduction

Science applications preparing for the exascale era are increasingly exploring in situ computations comprising of simulation-analysis-reduction pipelines coupled in-memory. Efficient composition and execution of such complex pipelines for a target platform is a codesign process that evaluates the impact and tradeoffs of various application- and system-specific parameters. In this article, we describe a toolset for automating performance studies of composed HPC applications that perform online data reduction and analysis. We describe Cheetah, a new framework for composing parametric studies on coupled applications, and Savanna, a runtime engine for orchestrating and executing campaigns of codesign experiments. Furthermore, this toolset facilitates understanding the impact of various factors such as process placement, synchronicity of algorithms, and storage versus compute requirements for online analysis of large data. Ultimately, we aim to create a catalog of performance results that can help scientists understand tradeoffs when designing next-generation simulations that make use of online processing techniques. We illustrate the design of Cheetah and Savanna, and present application examples that use this framework to conduct codesign studies on small clusters as well as leadership class supercomputers.

97 MATHEMATICS AND COMPUTING↗

BCARS Simulated Phantom Dataset for Evaluation of Processing Pipelines

Broadband coherent anti-Stokes Raman scattering (BCARS) microscopy is a powerful label-free biological imaging technique, but the raw signal requires careful processing. The vibrationally resonant (Raman) fingerprint signal is usually small compared with instrumental noise sources and the nonresonant background (NRB) inherent in the BCARS signal. Fortunately, the NRB exhibits a systematic phase relationship with the coherent Raman response, acting as a heterodyne amplifier for the weak fingerprint signal. Due to this heterodyne effect, the Raman response can be recovered quantitatively and invariantly across different instruments, provided the NRB shape is known. Even with heterodyne amplification, the amplitudes of fingerprint signal components are often comparable to system noise. Singular value decomposition (SVD), which utilizes spatial information, is often employed for additional noise filtering. Consequently, finding optimal processing parameters to properly distinguish the NRB and Raman responses and suppress noise in the complex BCARS signal requires a reference system that realistically represents the spectral and spatial properties of BCARS signals obtained from biological samples. We present a digital tissue phantom that meets these criteria as a tool for testing candidate signal processing pipelines. The digital phantom is generated with simulated hyperspectral Raman images having system-specific noise and background characteristics. Here, we analyze phantom datasets with differing background and signal-to-noise conditions to evaluate their impact on the performance of multiple signal processing pipelines. Specifically, we investigate the application of a Butterworth filter-based routine to directly estimate the NRB from the BCARS signal. Additionally, we evaluate a Lorentzian wavelet transform as an alternative to the Hilbert transform for extracting the Raman spectrum from the BCARS signal. While we demonstrate this phantom for BCARS, it can be used for any spectroscopic Raman imaging approach.

Dixon, Jessica Z. [Georgia Institute of Technology↗

Mechanical analysis of heterogeneous materials with higher-order parameters

Abstract Even though heterogeneous porous materials are widely used in a variety of engineering and scientific fields, such as aerospace, energy-storage technology, and bio-engineering, the relationship between effective material properties of porous materials and their underlying morphology is still not fully understood. To contribute to this knowledge gap, this paper adopts a higher-order asymptotic homogenization method to numerically investigate the effect of complex micropore morphology on the effective mechanical properties of a porous system. Specifically, we use the second-order scheme that is an extension of the first-order computational homogenization framework, where a generalized continuum enables us to introduce length scale into the material constitutive law and capture both pore size and pore distribution. Through several numerical case studies with different combinations of porosity, pore shapes, and distributions, we systematically studied the relationship between the underlying morphology and effective mechanical properties. The results highlight the necessity of higher-order homogenization in understanding the mechanical properties and reveal that higher-order parameters are required to capture the role of realistic pore morphologies on effective mechanical properties. Furthermore, for specific pore shapes, higher-order parameters exhibit dominant influence over the first-order continuum.

42 ENGINEERING↗

A comparative study of thermal- and electrocatalytic conversion of furfural: methylfuran as a primary and major product

Controlling reaction selectivity represents a fundamental challenge in heterogeneous catalysis. Here, we compare the selectivity in aqueous-phase thermal catalytic and electrocatalytic conversion of furfural and report the fundamental difference in elementary steps in the two reaction systems. Specifically, we observed that furfural alcohol and 2-methylfuran, which is the hydrogenation and hydrogenolysis product of furfural, respectively, are both primary products in electrocatalysis over a Cu electrode, with 2-methylfuran dominating the product distribution under electrode potentials between -0.55 and -0.75 V versus RHE. By contrast, in an aqueous-phase thermal reaction using a SiO 2 -supported Cu catalyst, furfural alcohol and its derivatives from the ring-rearrangement reaction are the major products, without production of 2-methylfuran, at the reaction temperature between 140 and 200 °C. Here, we propose that the distinct selectivity trends for oxygenate conversion via thermal and electrocatalytic reduction result from the distinct sequence of proton attack to the aldehyde group and may be generally true for reduction reactions of other biomass-derived oxygenates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A cross-platform execution engine for the quantum intermediate representation

Hybrid languages like the quantum intermediate representation (QIR) are essential for programming systems that mix quantum and conventional computing models, while execution of these programs is often deferred to a system-specific implementation. Here, we develop the QIR Execution Engine (QIR-EE) for parsing, interpreting, and executing QIR across multiple hardware platforms. QIR-EE uses LLVM to execute hybrid instructions specifying quantum programs and, by design, presents extension points that support customized runtime and hardware environments. We demonstrate an implementation that uses the XACC quantum hardware-accelerator library to dispatch prototypical quantum programs on different commercial quantum platforms and numerical simulators, and we validate execution of QIR-EE on IonQ, Quantinuum, and IBM hardware. Our results highlight the efficiency of hybrid executable architectures for handling mixed instructions, managing mixed data, and integrating with quantum computing frameworks to realize cross-platform execution.

LLVM↗