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DOE OSTI2023

Adjoint Waveform Tomography for Crustal and Upper Mantle Structure the Middle East and Southwest Asia for Improved Waveform Simulations Using Openly Available Broadband Data

We present a new model of radially anisotropic seismic wavespeeds for the crust and upper mantle of a broad region of the Middle East and Southwest Asia (MESWA) derived from adjoint waveform tomography. We inverted waveforms from 192 Global Centroid Moment Tensor earthquakes (MW 5.5-7.0) recorded by over 1000 openly available broadband seismic stations from permanent and temporary networks in the region. Spatial coverage of the available data is highly uneven due to earthquakes clustered along plate boundaries and sparse coverage of open seismic networks in the region. We considered three possible starting models: the SPiRaL global model (Simmons et al., 2021); MEC-1 (Kaviani et al., 2020); and CSEM2.0 (Noe et al., 2023). Because the SPiRaL model provides good fits to the observed waveforms measured by the time-bandwidth product of selected windows in several period bands, provides all the necessary parameters and covers the entire domain we used it for the starting model with the period band 50-100 seconds. Inversion iterations proceeded using time-frequency phase misfits in six stages and 54 total iterations reducing the minimum period to 30 seconds. Our final model, MESWA, provides improved waveform fits compared to the starting model for both the data used in the inversion and an independent validation data set of 66 events. Two metrics of waveform fit (the time-frequency phase misfit used in the optimization and normalized L2 misfit) were both reduced by nearly 60% for both data sets and MESWA provides significantly larger misfit reductions relative to the SPiRaL model than the MEC-1 or CSEM models. We also find that MESWA provides a larger time-bandwidth product of selected windows indicating that more information content of the observed waveforms is explained by MESWA than the other models. Our new model reveals tectonic features imaged by other studies and methods but in a new holistic model of shear and compressional wavespeeds (v S and v P , respectively) with anisotropy covering the crust and uppermost mantle of a larger domain. MESWA has smaller scale-length features and tends to sharpen some features relative to the SPiRaL starting model. Examples include: low crustal v S in the TurkishIranian Plateau, Zagros Mountains, Afghan Central Blocks and Sulaiman Fold Belt; low mantle vSfollowing divergent (Gulf of Aden, Red Sea) and transform (Dead Sea Fault) margins of the Arabian Plate; low and high v S in the mantle beneath the Arabian Shield and Platform, respectively. Low vS is imaged below Cenozoic volcanic centers of the Arabian Peninsula, the so-called Mecca-Madina-Nafud (MMN) Line. Positive anisotropy (v SH > v SV ) is inferred for asthenospheric depths across the region except where up/downwelling may influence fabric alignment (e.g. Afar, Red Sea, Arabian Shield). Elevated vS tracks Makran subduction under southeast Iran. MESWA resembles the SPiRaL model in its long-wavelength structure, but enhances shorter wavelengths features on the order of 200 km and smaller. The resulting model could be used for as a starting model for further improvements, say using waveforms from in-country seismic networks that are not openly available or smaller-scale studies targeting shorter period waveforms. The model also could be used for source characterization and moment tensor inversion to improve earthquake hazard studies and nuclear explosion monitoring.

58 GEOSCIENCES↗

DOE OSTI2025

An Open Benchmark of One Million High-Fidelity Cislunar Trajectories

Cislunar space spans from geosynchronous altitudes to beyond the Moon and will underpin future exploration, science, and security operations. We describe and release an open dataset of one million numerically propagated cislunar trajectories generated with the open-source Space Situational Awareness Python package (SSAPy). The model includes high-degree Earth/Moon gravity, solar gravity, and Earth/Sun radiation pressure; other planetary gravities are omitted by design for computational efficiency. Initial conditions uniformly sample commonly used osculating-element ranges, and each trajectory is propagated for up to six years under a single, fixed start epoch. The dataset is intended as a reusable benchmark for method development (e.g., space domain awareness, navigation, and machine-learning pipelines), a reference library for statistical studies of orbit families, and a starting point for community-driven extensions (e.g., alternative epochs). We report empirically observed stability trends (e.g., a band near ~5 GEO and persistence of some co-orbital classes including L4/L5 librators) as dataset descriptors rather than new dynamical results. The chief contribution is the scale, fidelity, organization (CSV/HDF5 with full state time series and metadata), and open availability, which together lower the barrier to comparative and data-driven studies in the cislunar regime.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Energy storage and coherence in closed and open quantum batteries

We study the role of coherence in closed and open quantum batteries. We obtain upper bounds to the work performed or energy exchanged by both closed and open quantum batteries in terms of coherence. Specifically, we show that the energy storage can be bounded by the Hilbert-Schmidt coherence of the density matrix in the spectral basis of the unitary operator that encodes the evolution of the battery. We also show that an analogous bound can be obtained in terms of the battery's Hamiltonian coherence in the basis of the unitary operator by evaluating their commutator. We apply these bounds to a 4-state quantum system and the anisotropic XY Ising model in the closed system case, and the Spin-Boson model in the open case.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Learning thermodynamic master equations for open quantum systems

The characterization of Hamiltonians and other components of open quantum dynamical systems plays a crucial role in quantum computing and other applications. Scientific machine learning techniques have been applied to this problem in a variety of ways, including by modeling with deep neural networks. However, the majority of mathematical models describing open quantum systems are linear, and the natural nonlinearities in learnable models have not been incorporated using physical principles. We present a data-driven model for open quantum systems that includes learnable, thermodynamically consistent terms. The trained model is interpretable, as it directly estimates the system Hamiltonian and linear components of coupling to the environment. We validate the model on synthetic two and three-level data, as well as experimental two-level data collected from a quantum device at Lawrence Livermore National Laboratory.

Mathematics and Computing↗

DOE OSTI2021

Perspectives of Open-Air Processing to Enable Perovskite Solar Cell Manufacturing

We report high throughput open-air processing techniques for the scalable production of all device and barrier layers for perovskite photovoltaics (PV). This work discusses and resolves some of the most formidable barriers to module-level scaling that the perovskite community has been facing. Our advanced technoeconomic manufacturing analysis indicates that vacuum-based processes with high capital expenditures (CapEx) and low throughputs dominate the cost of production. Open-air fabrication methods offer low CapEx routes to manufacturing, but achieving reproducibility in ambient conditions with varying relative humidity has been a persistent challenge. The use of rapid processing methods with plasma curing to convert films from the solution-state enables reproducibility, moisture immunity, and the highest perovskite PV efficiency produced in open-air. These methods are readily translatable to in-line processing where layers are sequentially deposited without the need for lengthy post-annealing steps that reduce throughput and involve additional equipment. Significant progress is demonstrated in reduced manufacturing costs as perovskites contend as a commercially viable next-generation thin film PV technology.

14 SOLAR ENERGY↗

DOE OSTI2024

A novel open-source cultivation system helps establish the first full cycle chemosynthetic symbiosis model system involving the giant ciliate Zoothamnium niveum

Symbiotic interactions drive species evolution, with nutritional symbioses playing vital roles across ecosystems. Chemosynthetic symbioses are globally distributed and ecologically significant, yet the lack of model systems has hindered research progress. The giant ciliate Zoothamnium niveum and its sulfur-oxidizing symbionts represent the only known chemosynthetic symbiosis with a short life span that has been transiently cultivated in the laboratory. While it is experimentally tractable and presents a promising model system, it currently lacks an open-source, simple, and standardized cultivation setup. Following the FABricated Ecosystems (EcoFABs) model, we leveraged 3D printing and polydimethylsiloxane (PDMS) casting to develop simple flow-through cultivation chambers that can be produced and adopted by any laboratory. The streamlined manufacturing process reduces production time by 86% and cuts cost by tenfold compared to the previous system. Benchmarking using previously established optimal growth conditions, the new open-source cultivation system proves stable, efficient, more autonomous, and promotes a more prolific growth of the symbiosis. For the first time, starting from single cells, we successfully cultivated the symbiosis in flow-through chambers for 20 days, spanning multiple generations of colonies that remained symbiotic. They were transferred from chamber to chamber enabling long-term cultivation and eliminating the need for continuous field sampling. The chambers, optimized for live imaging, allowed detailed observation of the synchronized growth between the host and symbiont. Highlighting the benefit of this new system, we here describe a new step in the first hours of development where the host pauses growth, expels a coat, before resuming growth, hinting at a putative symbiont selection mechanism early in the colony life cycle. With this simple, open-source, cultivation setup, Z. niveum holds promises for comparative studies, standardization of research and wide adoption by the symbiosis research community.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

An Investigation of Poorly Studied Open Cluster NGC 4337 Using Multicolor Photometric and Gaia DR2 Astrometric Data

We present a comprehensive analysis (photometric and kinematical) of the poorly studied open cluster NGC 4337 using 2MASS, WISE, APASS, and Gaia DR2 databases. By determining the membership probabilities of stars, we identified the 624 most probable members with membership probability higher than 50% by using proper motion and parallax data taken from Gaia DR2. The mean proper motion of the cluster is obtained as μ{sub x}=−8.83±0.01 and μ {sub y} = 1.49 ± 0.006 mas yr{sup −1}. We find the normal interstellar extinction toward the cluster region. The radial distribution of members provides a cluster radius of 7.′75 (5.63 pc). The estimated age of 1600 ± 180 Myr indicates that NGC 4337 is an old open cluster with a bunch of red giant stars. The overall mass function slope for main-sequence stars is found as 1.46±0.18 within the mass range 0.75−2.0 M{sub ⊙}, which is in fair agreement with Salpeter’s value (x = 1.35) within uncertainty. The present study demonstrates that NGC 4337 is a dynamically relaxed open cluster. Using the Galactic potential model, Galactic orbits are obtained for NGC 4337. We found that this object follows a circular path around the Galactic center. Under the kinematical analysis, we compute the apex coordinates (A, D) by using two methods: (i) the classical convergent point method and (ii) the AD-diagram method. The obtained coordinates are (A {sub conv}, D {sub conv}) = (96.°27 ± 0.°10, 13.°14 ± 0.°27) and (A {sub ◦}, D {sub ◦}) = (100.°282 ± 0.°10, 9.°577 ± 0.°323) respectively. We also computed the Velocity Ellipsoid Parameters, matrix elements (μ {sub ij}), direction cosines (l {sub j}, m {sub j}, n {sub j}), and the Galactic longitude of the vertex (l {sub 2}).

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Stellar Radial Velocities in the Old Open Cluster M67 (NGC 2682). II. The Spectroscopic Binary Population

We present and analyze 120 spectroscopic binary and triple cluster members of the old (4 Gyr) open cluster M67 (NGC 2682). As a cornerstone of stellar astrophysics, M67 is a key cluster in the WIYN Open Cluster Study (WOCS); radial-velocity (RV) observations of M67 are ongoing and extend back over 45 yr, incorporating data from seven different telescopes, and allowing us to detect binaries with orbital periods ≲10{sup 4} days. Our sample contains 1296 stars (604 cluster members) with magnitudes of 10 ≤ V ≤ 16.5 (about 1.3–0.7 M {sub ⊙}), from the giants down to ∼4 mag below the main-sequence turnoff, and extends in radius to 30′ (7.4 pc at a distance of 850 pc, or ∼7 core radii). This paper focuses primarily on the main-sequence binaries, but orbital solutions are also presented for red giants, yellow giants, and sub-subgiants. Out to our period detection limit and within our magnitude and spatial domain, we find a global main-sequence incompleteness-corrected binary fraction of 34% ± 3%, which rises to 70% ± 17% in the cluster center. We derive a tidal circularization period of P{sub circ}=11.0{sub −1.0}{sup +1.1} days. We also analyze the incompleteness-corrected distributions of binary orbital elements and masses. The period distribution rises toward longer periods. The eccentricity distribution, beyond P {sub circ}, is consistent with a uniform distribution. The mass-ratio distribution is also consistent with a uniform distribution. Overall, these M67 binaries are closely consistent with similar binaries in the galactic field, as well as with the old (7 Gyr) open cluster NGC 188. WOCS. 83.

47 OTHER INSTRUMENTATION↗

DOE OSTI2020

Carbon-Carbon Aeroshell Chemical Reaction Model in an Open RPS in Martian Environment

A new RPS is being designed to be open to the vacuum of space to improve its thermal efficiency during deep space missions. This design, however, could lead to some potential complications if it is ever used in the low-pressure gas environment of mission destinations like Mars. This report documents the development of a chemical kinetics reaction model of the FWPF carbon-carbon aeroshell in the Martian gaseous environment. This model uses an “infinite sink” assumption where the RPS is open to the Martian environment with open exchange of flowing gases, so the gas chemistry over the aeroshell does not change with the reaction and represents the worst case scenario of the chemical reaction of the FWPF in the Martian environment. The model combines the kinetics equation of both oxidation reactions that would occur on Mars: the Langmuir-Hinshelwood kinetics of the Boudouard reaction of CO2 with the chemical kinetics of O2 oxidation of the carbon-carbon. The FWPF chemical reaction model was benchmarked using the Opila’s experimental chemical reaction test data (1) in a simulated Martian environment to increase the validity of the model’s predicted mass loss rate. The output of the benchmarked chemical reaction model showed a trade-off between the maximum temperature of the aeroshell to have less than 10% reaction at the mission life. For example, an RPS with a five-year intended mission life on Mars has a maximum aeroshell temperature of 835 K / 562 °C, increasing the mission life to ten years reduces the maximum operating temperature to 810 K / 527 °C. If the aeroshell operating temperature in the new RPS on the surface of Mars is 960 Kelvin, the model calculates that the life is limited to 0.22 years / 81 days. Increasing the aeroshell temperature to 1343 Kelvin, further reduces the life to 0.375 days / 9 hrs. This illustrates the thermally activated nature of the chemical kinetics model in limiting the life of the aeroshell.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

SorpPropLib : An Open-Source Database for Sorption Equilibrium Properties

Hundreds of sorption working pair equilibrium measurements have been reported in the literature, and many experimental results have been fitted to equilibrium equations. However, an open database does not exist for the equilibrium equations. Therefore, this work compiled 438 published equilibrium equations of sorption working pairs into an open-source database called SorpPropLib. SorpPropLib is accessible from six programming environments commonly used in sorption cycle simulation (C++, Excel®, Python®, Matlab®, Modelica® and Lab-VIEW™). Plotting capabilities allow fast cycle visualization in each programming environment. Thereby, the open-source database SorpPropLib aims to enable and encourage easy data sharing to advance sorption research.

Engelpracht, Mirko↗

DOE OSTI2023

Developing Synthetic Distribution Models Using Open-Source Data Sets

The deployment of distributed generation resources at scale with the distribution side of the power system network over the last two decades has spurred a lot of research interest in distribution networks. Given, the sensitive nature of power system data sets, utilities are still reluctant to open-source distribution networks. Although some open-source data sets are available, they may not cover the region of interest. In this paper, we introduce the Synthetic dIstribution Network Generator (SING), new software that allows users to develop synthetic distribution models, using open-source data sets, in any region of interest within the continental US.

data set↗

DOE OSTI2023

Additively manufactured structure with reinforced access opening

A method and system of additively-manufacturing a structure having a reinforced access opening includes printing, via an additive printing device having at least one printer head, a portion of the structure adjacent to a support surface. The portion of the structure is printed of a cementitious material, and the printed portion of the structure defines an access opening for the structure. Moreover, the method includes providing a void of the cementitious material at a top boundary of the access opening, placing one or more reinforcement members in the void such that the one or more reinforcement members extend across the void, and continuing to print the printed portion of the structure around the void to build up the structure. Thus, the method also includes backfilling the void with a backfill material to incorporate the one or more reinforcement members within the void into the printed portion of the structure.

Li, Xiaopeng↗

DOE OSTI2024

Life-Cycle Assessment Integration into Scalable Open-Source Numerical Models (LiAISON) for Prospective Impact Analysis of Novel Technologies

Decarbonizing the industrial sector is a significant challenge in achieving a net-zero greenhouse gas (GHG) emissions economy by 2050 and the Paris Agreement, i.e., a global climate change mitigation target of achieving a maximum average temperature change potential of 1.5 Degrees Celsius or less by 2100 with respect to pre-industrial levels. In the United States (US), the industrial sector accounts for 23% of total GHG emissions and is home to a number of hard-to-electrify activities. The chemicals subsector has the single largest subsector emissions profile after direct emissions from fossil fuel combustion and leakage from fossil fuel distribution systems. Within the chemicals subsector, many processes depend on hydrogen or ammonia precursors. Decarbonizing these two commodities would contribute significantly to decarbonizing the industrial sector as hydrogen could also be used for low carbon steel production (e.g., hydrogen-based direct reduction of iron) and other industrial applications. Emerging technologies require the application of prospective life cycle assessment (LCA), which can account for technology (foreground) scaling and process improvements via learning-by-doing, among others. In many cases, the future system context (background) in which the technologies are assumed to operate in is equally relevant. Background scenarios generated by integrated assessment models (IAM) can coherently incorporate potential future dynamics of the energy-climate-human-land system. Further, IAM scenarios are harmonized across socioeconomic and climate change mitigation pathways, which facilitates the comparability of prospective LCAs using different IAMs. We introduce an open source prospective LCA framework, the Life-cycle Assessment Integration into Scalable Open-source Numerical models (LiAISON), to analyze the non-linear relationships between technology foreground and the future energy system background across a series of midpoint and resource use metrics. The integration of LCA and IAM data is achieved using prospective environmental Impact assessment (PREMISE). We showcase it by assessing two Power-to-Hydrogen (PtH2) processes, namely Solid Oxide Electrolysis (SOE) and Polymer Electrolyte Membrane Electrolysis (PEME). We compare the technologies to a baseline of hydrogen production via natural gas-based Steam Methane Reforming (SMR) in a US context of multiple energy system and climate change mitigation futures. Besides providing an analysis that specifies the LCA results ranges with temporal and geospatial explicitness across the two technologies, metrics, and impact assessment methods, this research also aims to establish a base framework that can be expanded to use other IAM generated scenarios and US open-source life cycle inventory (LCI) databases. We find that the temporal environmental performance of either technology or their difference to SMR is directly influenced by the underlying background dynamics. Additionally we compare our results by linking two other prospective models with LiAISON - GCAM (Global Change Assessment Model) and ReEDS (Regional Energy Deployment System) to analyze the effect of changing background scenarios using varying predictions in life cycle analysis.

decarbonizing↗

DOE OSTI2024

Life-Cycle Assessment Integration into Scalable Open-Source Numerical Models (LiAISON) for Analyzing Emerging Low-Carbon Technologies

Decarbonizing the industrial sector is a significant challenge in achieving a net-zero greenhouse gas (GHG) emissions economy by 2050 and the Paris Agreement, i.e., a global climate change mitigation target of achieving a maximum average temperature change potential of 1.5 degrees Celsius or less by 2100 with respect to pre-industrial levels. In the United States (US), the industrial sector accounts for 23% of total GHG emissions and is home to a number of hard-to-electrify activities. The chemicals subsector has the single largest subsector emissions profile after direct emissions from fossil fuel combustion and leakage from fossil fuel distribution systems. Within the chemicals subsector, many processes depend on hydrogen or ammonia precursors. Decarbonizing these two commodities would contribute significantly to decarbonizing the industrial sector as hydrogen could also be used for low carbon steel production (e.g., hydrogen-based direct reduction of iron) and other industrial applications. Emerging technologies require the application of prospective life cycle assessment (LCA), which can account for technology (foreground) scaling and process improvements via learning-by-doing, among others. In many cases, the future system context (background) in which the technologies are assumed to operate in is equally relevant. Background scenarios generated by integrated assessment models (IAM) can coherently incorporate potential future dynamics of the energy-climate-human-land system. Further, IAM scenarios are harmonized across socioeconomic and climate change mitigation pathways, which facilitates the comparability of prospective LCAs using different IAMs. We introduce an open source prospective LCA framework, the Life-cycle Assessment Integration into Scalable Open-source Numerical models (LiAISON), to analyze the non-linear relationships between technology foreground and the future energy system background across a series of midpoint and resource use metrics. The integration of LCA and IAM data is achieved using prospective environmental Impact assessment (PREMISE). We showcase it by assessing two Power-to-Hydrogen (PtH2) processes, namely Solid Oxide Electrolysis (SOE) and Polymer Electrolyte Membrane Electrolysis (PEME). We compare the technologies to a baseline of hydrogen production via natural gas-based Steam Methane Reforming (SMR) in a US context of multiple energy system and climate change mitigation futures. Besides providing an analysis that specifies the LCA results ranges with temporal and geospatial explicitness across the two technologies, metrics, and impact assessment methods, this research also aims to establish a base framework that can be expanded to use other IAM generated scenarios and US open-source life cycle inventory (LCI) databases. We find that the temporal environmental performance of either technology or their difference to SMR is directly influenced by the underlying background dynamics. Under baseline projections (i.e., no decarbonization goals), neither process reaches parity with the incumbent technology across several environmental metrics. Under the decarbonization scenarios, the underlying sectoral shifts result in declining impacts over time, compared to 2020 levels, except for metal depletion levels, which increase. The background shifts postulate a heavily decarbonized economy and energy system, which help technologies reach parity with SMR between 2040-2050 (RCP2.6) and 2030-2040 (RCP1.9) for global warming. Despite declines across several other metrics over time, neither PtH2 technology break even with SMR by 2100 besides for global warming.

decarbonizing↗

DOE OSTI2024

Life-Cycle Assessment Integration into Scalable Open-Source Numerical Models (LiAISON) for Analyzing Emerging Low-Carbon Technologies

Decarbonizing the industrial sector is a significant challenge in achieving a net-zero greenhouse gas (GHG) emissions economy by 2050 and the Paris Agreement, i.e., a global climate change mitigation target of achieving a maximum average temperature change potential of 1.5 degrees C or less by 2100 with respect to pre-industrial levels. In the United States (US), the industrial sector accounts for 23% of total GHG emissions and is home to a number of hard-to-electrify activities. The chemicals subsector has the single largest subsector emissions profile after direct emissions from fossil fuel combustion and leakage from fossil fuel distribution systems. Within the chemicals subsector, many processes depend on hydrogen or ammonia precursors. Decarbonizing these two commodities would contribute significantly to decarbonizing the industrial sector as hydrogen could also be used for low carbon steel production (e.g., hydrogen-based direct reduction of iron) and other industrial applications. Emerging technologies require the application of prospective life cycle assessment (LCA), which can account for technology (foreground) scaling and process improvements via learning-by-doing, among others. In many cases, the future system context (background) in which the technologies are assumed to operate in is equally relevant. Background scenarios generated by integrated assessment models (IAM) can coherently incorporate potential future dynamics of the energy-climate-human-land system. Further, IAM scenarios are harmonized across socioeconomic and climate change mitigation pathways, which facilitates the comparability of prospective LCAs using different IAMs. We introduce an open source prospective LCA framework, the Life-cycle Assessment Integration into Scalable Open-source Numerical models (LiAISON), to analyze the non-linear relationships between technology foreground and the future energy system background across a series of midpoint and resource use metrics The integration of LCA and IAM data is achieved using prospective environmental Impact assessment (PREMISE). We showcase it by assessing two Power-to-Hydrogen (PtH2) processes, namely Solid Oxide Electrolysis (SOE) and Polymer Electrolyte Membrane Electrolysis (PEME). We compare the technologies to a baseline of hydrogen production via natural gas-based Steam Methane Reforming (SMR) in a US context of multiple energy system and climate change mitigation futures. Besides providing an analysis that specifies the LCA results ranges with temporal and geospatial explicitness across the two technologies, metrics, and impact assessment methods, this research also aims to establish a base framework that can be expanded to use other IAM generated scenarios and US open-source life cycle inventory (LCI) databases. We find that the temporal environmental performance of either technology or their difference to SMR is directly influenced by the underlying background dynamics. Under baseline projections (i.e., no decarbonization goals), neither process reaches parity with the incumbent technology across several environmental metrics. Under the decarbonization scenarios, the underlying sectoral shifts result in declining impacts over time, compared to 2020 levels, except for metal depletion levels, which increase. The background shifts postulate a heavily decarbonized economy and energy system, which help technologies reach parity with SMR between 2040-2050 (RCP2.6) and 2030-2040 (RCP1.9) for global warming. Despite declines across several other metrics over time, neither PtH2 technology break even with SMR by 2100 besides for global warming.

decarbonizing↗

DOE OSTI2024

Towards Prospective LCA Using Life-Cycle Assessment Integration into Scalable Open-Source Numerical Models (LiAISON) Framework for Analyzing Emerging Low-Carbon Technologies

Decarbonizing the industrial sector is a significant challenge in achieving a net-zero greenhouse gas (GHG) emissions economy by 2050 and the Paris Agreement, i.e., a global climate change mitigation target of achieving a maximum average temperature change potential of 1.5 Degrees Celsius or less by 2100 with respect to pre-industrial levels. In the United States (US), the industrial sector accounts for 23% of total GHG emissions and is home to a number of hard-to-electrify activities. The chemicals subsector has the single largest subsector emissions profile after direct emissions from fossil fuel combustion and leakage from fossil fuel distribution systems. Within the chemicals subsector, many processes depend on hydrogen or ammonia precursors. Decarbonizing these two commodities would contribute significantly to decarbonizing the industrial sector as hydrogen could also be used for low carbon steel production (e.g., hydrogen-based direct reduction of iron) and other industrial applications. Emerging technologies require the application of prospective life cycle assessment (LCA), which can account for technology (foreground) scaling and process improvements via learning-by-doing, among others. In many cases, the future system context (background) in which the technologies are assumed to operate in is equally relevant. Background scenarios generated by integrated assessment models (IAM) can coherently incorporate potential future dynamics of the energy-climate-human-land system. Further, IAM scenarios are harmonized across socioeconomic and climate change mitigation pathways, which facilitates the comparability of prospective LCAs using different IAMs. We introduce an open source prospective LCA framework, the Life-cycle Assessment Integration into Scalable Open-source Numerical models (LiAISON), to analyze the non-linear relationships between technology foreground and the future energy system background across a series of midpoint and resource use metrics The integration of LCA and IAM data is achieved using prospective environmental Impact assessment (PREMISE). We showcase it by assessing two Power-to-Hydrogen (PtH2) processes, namely Solid Oxide Electrolysis (SOE) and Polymer Electrolyte Membrane Electrolysis (PEME). We compare the technologies to a baseline of hydrogen production via natural gas-based Steam Methane Reforming (SMR) in a US context of multiple energy system and climate change mitigation futures. Besides providing an analysis that specifies the LCA results ranges with temporal and geospatial explicitness across the two technologies, metrics, and impact assessment methods, this research also aims to establish a base framework that can be expanded to use other IAM generated scenarios and US open-source life cycle inventory (LCI) databases. We find that the temporal environmental performance of either technology or their difference to SMR is directly influenced by the underlying background dynamics. Additionally we compare our results by linking two other prospective models with LiAISON - GCAM(Global Change Assessment Model) and ReEDS (Regional Energy Deployment System) to analyze the effect of changing background scenarios using varying predictions in life cycle analysis.

emissions↗

DOE OSTI2026

DC Cryogenic Modeling of Open-Source SkyWater 130 nm MOSFETs at 77 K Using BSIM4

Cryogenic applications in high-energy physics (HEP) demand reliable, low-power CMOS electronics capable of operating at liquid nitrogen temperatures (77 K). The open-source SkyWater 130nm (SKY130) CMOS process has previously been shown to operate at temperatures as low as 4 K making it a promising candidate for HEP applications. In this work, we characterize and model SKY130 low-threshold voltage transistors at 77 K, which is a temperature commonly used in modeling applications for liquid argon detectors. DC characteristic measurements were performed at both room temperature and liquid nitrogen temperature. We created a cryogenic modeling approach to produce a SPICE-compatible, isothermal BSIM4-based model for select transistor sizes at 77 K. The resulting model agrees with data at 77 K with an average error on the order of 20% (relative RMS) and shows no dependence on drain voltage. Due to the open-source nature of SKY130, we have made our models publicly available on Github. We hope this work will continue the trend for democratizing circuit design at cryogenic temperatures in high-energy physics by enabling open access to accurate cryogenic CMOS device models at 77 K.

Beall, F. [Texas U., Arlington]↗

DOE OSTI2024

Shifting institutional culture to develop climate solutions with Open Science

To address our climate emergency, “we must rapidly, radically reshape society”—Johnson & Wilkinson, All We Can Save. In science, reshaping requires formidable technical (cloud, coding, reproducibility) and cultural shifts (mindsets, hybrid collaboration, inclusion). We are a group of cross-government and academic scientists that are exploring better ways of working and not being too entrenched in our bureaucracies to do better science, support colleagues, and change the culture at our organizations. We share much-needed success stories and action for what we can all do to reshape science as part of the Open Science movement and 2023 Year of Open Science.

54 ENVIRONMENTAL SCIENCES↗