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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Unified Wind-Wave Growth and Spectrum Functions for All Water Depths: Field Observations and Model Results

Abstract Wind-wave development is governed by the fetch- or duration-limited growth principle that is expressed as a pair of similarity functions relating the dimensionless elevation variance (wave energy) and spectral peak frequency to fetch or duration. Combining the pair of similarity functions, the fetch or duration variable can be removed to form a dimensionless function of elevation variance and spectral peak frequency, which is interpreted as the wave energy evolution with wave age. The relationship is initially developed for quasi-neural stability and quasi-steady wind forcing conditions. Further analyses show that the same fetch, duration, and wave-age similarity functions are applicable to unsteady wind forcing conditions, including rapidly accelerating and decelerating mountain gap wind episodes and tropical cyclone (TC) wind fields. Here it is shown that with the dimensionless frequency converted to dimensionless wavenumber using the surface wave dispersion relationship, the same similarity function is applicable in all water depths. Field data collected in shallow to deep waters and mild to TC wind conditions and synthetic data generated by spectrum model computations are assembled to illustrate the applicability. For the simulation work, the finite-depth wind-wave spectrum model and its shoaling function are formulated for variable spectral slopes. Given wind speed, wave age, and water depth, the measured and spectrum-computed significant wave heights and the associated growth parameters are in good agreement in forcing conditions from mild to TC winds and in all depths from deep ocean to shallow lake. Significance Statement This paper presents a growth function and spectrum model to describe wind-wave development in all water depths. Their applicability covers a wide range of wind forcing conditions including steady, accelerating, decelerating, and tropical cyclone events. Support for the unified spectrum model and growth function is presented with field observations and numerical computations.

Hwang, Paul A.↗
DOE OSTI2023

Projecting Future Energy Production from Operating Wind Farms in North America. Part II: Statistical Downscaling

Abstract Capacity factors (CFs) derived from daily expected power at 22 operating wind farms in different regions of North America are used as predictands to train statistical downscaling algorithms using output from ERA5. The statistical downscaling models are then used to make CF projections for a suite of CMIP6 Earth System Models (ESMs). Downscaling is performed using a hybrid statistical approach that employs synoptic types derived using k -means clustering applied to sea level pressure fields with variance corrections applied as a function of the pressure gradient intensity. ESMs exhibit marked variability in terms of the skill with which the frequency of synoptic types and pressure gradients are reproduced relative to ERA5, and that differential skill is used to infer differential credibility in the associated CF projections. Projections of median annual mean CF [P50(CF)] in each 20-yr period from 1980 to 2099 show evidence of declines at most wind farms except in parts of the southern Great Plains, although the magnitude of the changes is strongly dependent on the ESM. For example, P50(CF) in 2080–99 deviate from those in 1980–99 by from −3.1 to +0.2 percentage points in the Northeast. The largest-magnitude declines in P50(CF) ranging from −3.9 to −2 percentage points are projected for the southern West Coast. CF trends exhibit marked seasonality and are strongly linked to changes in the relative intensity of future synoptic patterns, with much less impact from shifts in the occurrence of synoptic types over time. Internal climate modes continue to play a significant role in inducing interannual variability in wind power production, even under high radiative forcing scenarios. Significance Statement We describe how future climate changes may affect wind resources and wind power generation. Near-term changes in projected wind power electricity generation potential at operating wind farms over North America are small, but by the end of the current century electricity production is projected to decrease in many areas but may increase in parts of the southern Great Plains. The amount of change in projected wind power production is a strong function of the Earth system model that is downscaled and also depends on the continued presence of internally forced climate variability. An additional dependence on the amount of greenhouse gas–induced global warming indicates the transition of the energy sector to low-carbon sources may assist in maintaining the abundant U.S. wind resource.

Meteorology & Atmospheric Sciences↗
DOE OSTI2026

Linking DSC/TGA to Cell Levels: Energetics, Evolved Gases, and Thermal Safety of NMC811‐Graphite Micro‐Cell

Thermochemical characterization of battery materials links intrinsic material properties to decomposition pathways, heat generation, and gas evolution that govern performance and safety. Despite extensive work on NMC811-Graphite, variability across partial configurations and the limited adoption of micro-cell architectures (cathode+anode+electrolyte+separator) hinder robust cell-scale interpretation. Accordingly, this work establishes a bottom-up, component-resolved methodology integrating DSC/TGA, evolved gas analysis (EGA), and in situ XRD to link decomposition pathways and energy release across partial and micro-cell configurations, providing a transferable assessment of safety and stability in emerging chemistries. In separator-free configurations, the gas–solid reaction between cathode-evolved O 2 and anode-leached Li dominates the net heat release (1139 J g −1 ). In contrast, in the micro-cell configuration, the separator hinders O 2 transport and alters the timing and pathways of other reactions, and reduces the net energy release to 618 J g −1 . Energy release was organized into defined temperature windows that provide a framework for a thermodynamic model combining quantified gas evolution with selected decomposition pathways and effective reaction enthalpies to estimate net specific energy release, with agreement between DSC and cell-level tests. Ex situ XPS of heat-treated samples extends post-mortem analysis to thermal-abuse regimes, supporting key pathway elements.

25 ENERGY STORAGE↗
DOE OSTI2022

Numerical algorithms for water waves with background flow over obstacles and topography

Abstract We present two accurate and efficient algorithms for solving the incompressible, irrotational Euler equations with a free surface in two dimensions with background flow over a periodic, multiply connected fluid domain that includes stationary obstacles and variable bottom topography. One approach is formulated in terms of the surface velocity potential while the other evolves the vortex sheet strength. Both methods employ layer potentials in the form of periodized Cauchy integrals to compute the normal velocity of the free surface, are compatible with arbitrary parameterizations of the free surface and boundaries, and allow for circulation around each obstacle, which leads to multiple-valued velocity potentials but single-valued stream functions. We prove that the resulting second-kind Fredholm integral equations are invertible, possibly after a physically motivated finite-rank correction. In an angle-arclength setting, we show how to avoid curve reconstruction errors that are incompatible with spatial periodicity. We use the proposed methods to study gravity-capillary waves generated by flow around several elliptical obstacles above a flat or variable bottom boundary. In each case, the free surface eventually self-intersects in a splash singularity or collides with a boundary. We also show how to evaluate the velocity and pressure with spectral accuracy throughout the fluid, including near the free surface and solid boundaries. To assess the accuracy of the time evolution, we monitor energy conservation and the decay of Fourier modes and compare the numerical results of the two methods to each other. We implement several solvers for the discretized linear systems and compare their performance. The fastest approach employs a graphics processing unit (GPU) to construct the matrices and carry out iterations of the generalized minimal residual method (GMRES).

Ambrose, David M.↗
DOE OSTI2026

Inductance meets memory in a quantum magnet

Orbital degrees of freedom offer a largely untapped route to emergent dynamical phenomena in correlated quantum materials. However, it remains unclear whether collective orbital states can intrinsically generate both reactive and memory functionalities in a bulk system. Here we show that in the ferrimagnet Mn₃Si₂Te₆, nonequilibrium reconfiguration of chiral orbital currents produces both emergent inductance and nonvolatile memristance as intrinsic properties of a single crystal. At low frequency and under a magnetic field along the c axis, coherent orbital-current domains generate robust clockwise inductive I-V loops. At higher frequency and low field, current-driven first-order reconfiguration leads to incomplete reversal and metastable trapping, producing an intrinsic electromotive force and a finite remanent voltage at zero current. These results establish orbital currents as a class of quantum state variables that encode both reactive and memory functionalities, opening routes toward intrinsically reconfigurable and energy-efficient electronic systems.

Cao, Tristan [University of Colorado, Boulder]↗
DOE OSTI2024

First-Principles Insights into the Thermodynamics of Variable-Temperature Ammonia Synthesis on Transition-Metal-Doped Cu (100) and (111)

Ammonia (NH 3 ) is one of the most produced chemicals worldwide. NH 3 synthesis predominantly utilizes the Haber–Bosch (HB) process, requiring high temperatures and pressures. Despite significant process advances, ample opportunity remains for improving the rate, selectivity, catalyst stability, and energy efficiency. Inspired by a recently developed programmable heating and quenching (PHQ) technique, we present in this paper a first-principles screening of candidate single-atom alloy catalysts generated from doping (111) and (100) surfaces of copper (Cu), an ineffective HB catalyst in its pure form. We predict the thermodynamics of two rate-limiting reactions, N 2 dissociative adsorption and the final hydrogenation step leading up to NH 3 release, at 400 and 900 K. Thermodynamically, the former reaction is favored at low temperatures, while the latter is favored at high temperatures. Vanadium-, chromium-, and molybdenum-doped Cu surfaces, due to intermediate M–N covalent bonding character, emerge as appealing candidate catalysts for PHQ NH 3 synthesis, as they balance the thermodynamics of the above-mentioned reaction steps at their respective optimal temperatures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Situational awareness-enhancing community-level load mapping with opportunistic machine learning

Motivated by present and forthcoming challenges in the adoption and integration of distributed renewable energy, we develop a machine learning (ML) approach that builds short-fuse mappings connecting the occasionally-unobservable true load in one target community with information-rich signals collected from relatively more instrumented reference communities. Our setting is inspired by and tailored to target communities with significant unobservable behind-the-meter solar generation, where true load (a relatively well-behaved quantity of interest to grid operators) is hard to discern during daytime due to insufficient instrumentation and/or privacy reasons, but that can be related to reference communities with low unobservable distributed variable generation or with sufficient instrumentation. The developed mapping, herein realized with Support Vector Machine regression, is built using nighttime data from all communities, when their distributed generation is low or zero. Our ML algorithm opportunistically learns to correlate signals of interest and then is operationally used the next day to shed light into target community load evolution. The mapping is subsequently rebuilt, rolling its short-fuse scope perpetually forward in time. Here, we demonstrate the efficacy of our approach on nine synthetically generated topologies and associated timeseries stemming from real-world data, on which we observe cumulative error performance that yields lower than 10% and 15% daily-averaged mean absolute percentage errors in target community load estimation on more than about 75% and 90% of days, respectively, in multiple yearly evaluations that shed light on long-term performance also under seasonal and one-off effects. The proposed ML-powered methodology can offer grid operators much-improved visibility into a previously obscure space and can also serve as an additional source of information in broader, multi-modal solar disaggregation solutions.

14 SOLAR ENERGY↗
DOE OSTI2022

The encasulation effect on thermal performance of micro-encapsulated phase change materials during energy absorption

Understanding the performance of the thermal storage materials is required to successfully meet the needs of next generation concentrating solar power projects. This study focuses on the thermal characteristics of the micro-encapsulated phase change material (MEPCM) with metallic core under high temperature. A numerical model was developed and verified to study the transient heat absorption process of MEPCMs made of tin, aluminum and copper core. Convective heat transfer rate, total energy absorption and volumetric energy density were presented. The effect of encapsulation on theses variables was analyzed under various boundary and initial conditions. Its impact on characteristic time variables was discussed. The method presented can be adopted to analyzing both manufacturing and application processes for MEPCMs of various compositions, during which melting and solidification happen. Given certain operating conditions, the results from the model can be referenced to obtain optimal thermal performance of these materials.

Benner, Jingru↗
DOE OSTI2024

Dynamically Learning Incentives for Load Control

As electrical generation becomes more distributed and volatile, and loads become more uncertain, controllability of distributed energy resources (DERs), regardless of their ownership status, will be necessary for grid reliability. Grid operators lack direct control over end-users' grid interactions, such as energy usage, but incentives can influence behavior -- for example, an end-user that receives a grid-driven incentive may adjust their consumption or expose relevant control variables in response. A key challenge in studying such incentives is the lack of data about human behavior, which usually motivates strong assumptions, such as distributional assumptions on compliance or rational utility-maximization. In this paper, we propose a general incentive mechanism in the form of a constrained optimization problem -- our approach is distinguished from prior work by modeling human behavior (e.g., reactions to an incentive) as an arbitrary unknown function. We propose feedback-based optimization algorithms to solve this problem that each leverage different amounts of information and/or measurements. We show that each converges to an asymptotically stable incentive with (near)-optimality guarantees given mild assumptions on the problem. Finally, we evaluate our proposed techniques in voltage regulation simulations on standard test beds. We test a variety of settings, including those that break assumptions required for theoretical convergence (e.g., convexity, smoothness) to capture realistic settings. In this evaluation, our proposed algorithms are able to find near-optimal incentives even when the reaction to an incentive is modeled by a theoretically difficult (yet realistic) function.

demand response↗
DOE OSTI2021

Evaluating the Interactions Between Variable Renewable Energy and Diurnal Storage

Cost declines and growing deployment of photovoltaic (PV), wind, and storage have led to increasing interest in the potential interactions of these three technologies as their role in the power system grows. In this work we enhance a national-scale capacity expansion model to evaluate how PV, wind, and storage interact in the evolution of the power system. Importantly, the modeling framework captures interactions in both investments and operations. Through this work we identify significant synergies between PV and storage. Scenarios with more PV always have more storage, and scenarios with more storage always have more PV. This synergy is due to the diurnal alignment of PV generation with 4-8 hour storage, and to the ability of PV to narrow system peaks to allow shorter-duration storage to serve as a peaking resource. Interactions between wind and storage are less pronounced, though we do observe that longer-duration storage resources appear to provide greater value for wind.

14 SOLAR ENERGY↗
DOE OSTI2020

Advanced Newton methods for geodynamical models of Stokes flow with viscoplastic rheologies

Strain localization and resulting plasticity and failure play an important role in the evolution of the lithosphere. These phenomena are commonly modeled by Stokes flows with viscoplastic rheologies. The nonlinearities of these rheologies make the numerical solution of the resulting systems challenging, and iterative methods often converge slowly or not at all. Yet accurate solutions are critical for representing the physics. Moreover, for some rheology laws, aspects of solvability are still unknown. We study a basic but representative viscoplastic rheology law. The law involves a yield stress that is independent of the dynamic pressure, referred to as von Mises yield criterion. Two commonly used variants, perfect/ideal and composite viscoplasticity, are compared. We derive both variants from energy minimization principles, and we use this perspective to argue when solutions are unique. We propose a new stress-velocity Newton solution algorithm that treats the stress as an independent variable during the Newton linearization but requires solution only of Stokes systems that are of the usual velocity-pressure form. To study different solution algorithms, we implement 2-D and 3-D finite element discretizations, and we generate Stokes problems with up to 7 orders of magnitude viscosity contrasts, in which compression or tension results in significant nonlinear localization effects. Comparing the performance of the proposed Newton method with the standard Newton method and the Picard fixed-point method, we observe a significant reduction in the number of iterations and improved stability with respect to problem nonlinearity, mesh refinement, and the polynomial order of the discretization.

Rudi, Johann↗
DOE OSTI2023

Photoelectron spectroscopy with entangled photons; enhanced spectrotemporal resolution

In this theoretical study, we show how photoelectron signals generated by time-energy entangled photon pairs can monitor ultrafast excited state dynamics of molecules with high joint spectral and temporal resolutions, not limited by the Fourier uncertainty of classical light. This technique scales linearly, rather than quadratically, with the pump intensity, allowing the study of fragile biological samples with low photon fluxes. Since the spectral resolution is achieved by electron detection and the temporal resolution by a variable phase delay, this technique does not require scanning the pump frequency and the entanglement times, which significantly simplifies the experimental setup, making it feasible with current instrumentation. Application is made to the photodissociation dynamics of pyrrole calculated by exact nonadiabatic wave packet simulations in a reduced two nuclear coordinate space. This study demonstrates the unique advantages of ultrafast quantum light spectroscopy.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

A shift between mineral and nonmineral sources of iron and sulfur causes proteome-wide changes in Methanosarcina barkeri

ABSTRACT Iron (Fe) and sulfur (S) are required elements for life, and changes in their availability can limit the ecological distribution and function of microorganisms. In anoxic environments, soluble Fe typically exists as ferrous iron [Fe(II)] and S as sulfide (HS − ). These species exhibit a strong affinity that ultimately drives the formation of sedimentary pyrite (FeS 2 ). Recently, paradigm-shifting studies indicate that Fe and S in FeS 2 can be made bioavailable by methanogens through a reductive dissolution process. However, the impact of the utilization of FeS 2 , as opposed to canonical Fe and S sources, on the phenotype of cells is not fully understood. Here, shotgun proteomics was utilized to measure changes in the phenotype of Methanosarcina barkeri MS grown with FeS 2 , Fe(II)/HS − , or Fe(II)/cysteine. Shotgun proteomics tracked 1,019 proteins overall, with 307 observed to change between growth conditions. Functional characterization and pathway analyses revealed these changes to be systemic and largely tangential to Fe/S metabolism. As a final step, the proteomics data were viewed with respect to previously collected transcriptomics data to deepen the analysis. Presented here is evidence that M. barkeri adopts distinct phenotypes to exploit specific sources of Fe and S in its environment. This is supported by observed protein abundance changes across broad categories of cellular biology. DNA adjacent metabolism, central carbon metabolism methanogenesis, metal trafficking, quorum sensing, and porphyrin biosynthesis pathways are all features in the phenotypic differentiation. Differences in trace metal availability attributed to complexation with HS − , either as a component of the growth medium [Fe(II)/HS − ] or generated through reduction of FeS 2 , were likely a major factor underpinning these phenotypic differences. IMPORTANCE The methanogenic archaeon Methanosarcina barkeri holds great potential for industrial bio-mining and energy generation technologies. Much of the biochemistry of this microbe is poorly understood, and its characterization will provide a glimpse into biological processes that evolved close to life’s origin. The discovery of its ability to extract iron and sulfur from bulk, solid-phase minerals shifted a longstanding paradigm that these elements were inaccessible to biological systems. The full elucidation of this process has the potential to help scientists and engineers extract valuable metals from low-grade ore and mine waste generating energy in the form of methane while doing so.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Monthly Mean In Situ Surface Flux Observations Paired with Satellite-Derived and Reanalysis-Based Flux Data for the Great Lakes Region, 2001–2020

Surface radiative and turbulent heat fluxes over the Great Lakes strongly influence regional hydrological and meteorological processes, and their accurate representation is critical for numerical weather prediction and coupled atmosphere–lake modeling. However, direct flux observations are spatially sparse across the region, so gridded reanalysis and satellite-derived products are often used for climatological analyses and model evaluation despite differences in their flux representations. This dataset provides processed, quality-controlled, monthly mean surface flux observations from the Great Lakes Evaporation Network (GLEN), AmeriFlux, and the National Data Buoy Center, paired with spatiotemporally matched flux estimates from two reanalysis products, the fifth generation European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis dataset (ERA5) and the Modern Era Reanalysis for Research and Applications, version 2 (MERRA-2), and two satellite-derived products, the Clouds and Earth's Radiant Energy Systems Energy Balanced and Filled (CERES-EBAF) and the Cloud, Albedo and Surface Radiation dataset from AVHRR data - Edition 3 (CLARA-A3). The dataset includes sixteen observational stations with variable temporal coverage within 2001–2020. For each station, a CSV file contains monthly time series of available flux variables, including surface downwelling shortwave radiation (SW), surface downwelling longwave radiation (LW), sensible heat (SH) flux, and latent heat flux (LH), alongside matched gridded product values where available. Columns in the CSV file correspond to different variables sourced from each dataset, with column titles structured as "{dataset}_{variable}". Columns with relevant metadata are also provided in each CSV file, including station latitude and longitude, monthly timestamps, and the name of the sourced observational data. These files are structured for direct use in common analysis tools, including Microsoft Excel, Python pandas, and Python matplotlib. This dataset supports climatological analysis of the Great Lakes regional surface energy budget, evaluation of satellite-derived and reanalysis-based flux products, and development or validation of flux representations in numerical weather prediction and coupled atmosphere–lake models.

Great Lakes↗
DOE OSTI2025

The QPO in RE J1034+396 Originates in the Hot Corona

RE J1034+396 is one of the few active galactic nuclei (AGNs) with a significant quasiperiodic oscillation (QPO). The QPO has been observed in over 1 Ms of XMM-Newton observations spanning over a decade. We investigate the power spectral density function (PSD) of seven long (∼90 ks) XMM-Newton observations of the AGN RE J1034+396 in two energy bands. The soft (0.3–0.5 keV) band targets emission from the disk, while the hard (2–7 keV) band isolates the primary X-ray continuum emission from the corona. The QPO is significantly detected in the hard band of five of the seven observations. The best-fitting models indicate that the QPO detection in both bands is entirely attributable to the coronal emission with no additional contribution from the disk. This explains the strong coherence between the hard and soft bands at the QPO frequency. The covariance spectrum is consistent with this picture as the variability at QPO frequencies is attributed solely to fluctuations in the hot corona. The time lag as a function of energy is well described by a ∼2000 s intrinsic soft lag, resulting from the disk responding to emission from the corona, that undergoes phase wrapping at approximately the QPO frequency. By demonstrating that in this system the QPO arises in the corona, we provide new insights into the mechanisms generating QPOs.

Active galactic nuclei↗
DOE OSTI2023

Data and Tools for Exploring New Pumped Storage Hydropower Deployment Opportunities

Pumped storage hydropower (PSH) is a flexible energy storage technology with the potential to facilitate variable renewable energy integration into the decarbonized electric grid of the future. NREL is developing new data and tools to help understand opportunities for new PSH deployment, including nationwide resource assessment data, a bottom-up component-level cost model, and a lifecycle greenhouse gas emissions calculator. These datasets lay the foundation for better-informed grid planning decisions about how PSH fits into a future portfolio of generation, transmission, and storage assets.

CEM↗
DOE OSTI2022

Front-End Engineering Design for Piperazine with the Advanced Stripper

This Department of Energy (DOE) funded project was executed with the goal of preparing a Front-End Engineering Design (FEED) for the capture and compression of 90% of the CO2 that would normally be emitted from an existing natural gas combined cycle (NGCC) plant. The FEED focused on the application of the piperazine advanced stripper (PZAS) process at Mustang Station of the Golden Spread Electric Cooperative (GSEC), which consists of two gas turbines with common heat recovery steam generator (HRSG). The University of Texas at Austin (UT) served as the prime contractor, and subcontracted AECOM Technical Services and Trimeric Corporation to support FEED development. This project team has worked together to advance PZAS for more than a decade. ExxonMobil, Chevron, and Total provided project co-funding. The objectives of this work included: 1. To advance engineering design such that a comprehensive estimate for the total installed cost of a full-scale PZAS CO2 Capture Plant with CO2 compression can be developed on an existing NGCC power plant. a. These detailed costs can also be used to qualify PZAS and other related second generation (2G) amine scrubbing processes for use on cogeneration facilities in refineries and chemical plants that use gas turbines with HRSGs to produce steam. b. These detailed costs will help qualify 2G amine scrubbing for use on NGCC power plants and establish a more accurate baseline cost to be used as a target by other capture technologies. 2. To provide cost details to be used in the economic optimization of the process features of PZAS and other 2G amine scrubbing processes. 3. To provide DOE with a more detailed understanding of carbon capture costs in a commercial application, enabling DOE to better design its R&D program to improve the economics for carbon capture. 4. To provide the host site and cost share partners with the information necessary to determine whether a commercial project to capture and use CO2 for enhanced oil recovery (EOR) or for sequestration can be justified (when accounting for the 45Q tax credit). A key component of the FEED is the estimated total installed cost, which provides a basis for the likely capital investment necessary to implement the PZAS carbon capture process at this location and scale. In combination with the included economic analysis, which accounts for potential revenue from the produced CO2, potential avenues to profitability are explored. The major findings of the FEED are as follows: The Mustang Station PZAS CO2 Capture Plant estimated total project cost of $698 MM of which $384 MM was direct costs. The annual operating costs were $32.6 MM. The total investment for a PZAS facility at Mustang Station is $725 MM. This estimate includes owner’s cost of $25 million and a contingency of $110 MM. • The study estimated the CO2 capture plant at Mustang Station would generate CO2 at $110/tonne for EOR, assuming a 12% IRR (internal rate of return) and an 85% capacity factor. For CO2 storage, the same case would achieve a 12% IRR at about $114/tonne. At a capacity factor of 52%, the storage and EOR cases would break even when carbon is priced ~$150/tonne. The economic analysis determined that the capacity factor and utility pricing, among other variable factors, had a significant effect on the economics and will need additional studied. • The energy penalty of the PZAS plant would be about 46 MW in connected power and 35 MW in operating load. The natural gas requirement (for the Gas Boiler package) would be about 354 MMBTU/hr. • The FEED revealed no major risks in process maturity. However, some areas were outlined for further engineering during detailed design, which included the Gas Boiler system, general arrangement and site layout, air coolers, schedule development, and optimization of the process for higher CO2 removal. • If PZAS were to be implemented at another host site, additional opportunities for cost reduction for would include cost reduction through use of cooling water and steam extraction.

03 NATURAL GAS↗