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DOE OSTI2019

A deep learning approach to anomaly detection in geological carbon sequestration sites using pressure measurements

Carbon capture and storage (CCS) has been extensively investigated as a potential engineering measure to reduce anthropogenic carbon emission to the atmosphere. Real-time monitoring of the safety and integrity of carbon storage reservoirs is a critical aspect of any commercial-scale CCS deployment. Pressure-based sensing is cost effective, suitable for real-time monitoring, and scalable to large monitoring networks. However, questions remain on how to best harness intelligent information from the high-frequency pressure monitoring sensors to support real-time decisions. Here this work presents a deep-learning-based framework for analyzing and detecting anomalies in pressure data streams by using a convolutional long short-term memory (ConvLSTM) neural network model, which allows for the fusion of both static and dynamic reservoir data. In ConvLSTM, the convolutional neural network (CNN) is used for spatial pattern mining and the LSTM is used for temporal pattern recognition. The performance of the ConvLSTM model for real-time anomaly detection is demonstrated using a set of pressure monitoring data collected from Cranfield, Mississippi, an active enhanced-oil-recovery field. The anomaly detection model is trained using bottom-hole pressure data acquired from the base experiment (without leak event) and then tested on pressure data collected during a series of controlled CO 2 release experiments (with artificially created leak events). Results show that the ConvLSTM neural network model successfully detected anomalies in the pressure time series obtained from the controlled release experiments. Inclusion of static information into the model further improves the robustness of ConvLSTM.

13 HYDRO ENERGY↗

DOE OSTI2020

Deep learning to generate in silico chemical property libraries and candidate molecules for small molecule identification in complex samples

Comprehensive and unambiguous identification of small molecules in complex samples will revolutionize our understanding of the role of metabolites in biological systems. Existing and emerging technologies have enabled measurement of chemical properties of molecules in complex mixtures and, in concert, are sensitive enough to resolve even stereoisomers. Despite these experimental advances, small molecule identification is inhibited by (i) chemical reference libraries (e.g. mass spectra, collision cross section, and other measurable property libraries) representing <1% of known molecules, limiting the number of possible identifications, and (ii) the lack of a method to generate candidate matches directly from experimental features (i.e. without a library). To this end, we developed a variational autoencoder (VAE) to learn a continuous numerical, or latent, representation of molecular structure to expand reference libraries for small molecule identification. We extended the VAE to include a chemical property decoder, trained as a multitask network, in order to shape the latent representation such that it assembles according to desired chemical properties. The approach is unique in its application to metabolomics and small molecule identification, with its focus on properties that can be obtained from experimental measurements (m/z, CCS) paired with its training paradigm, which involved a cascade of transfer learning iterations. First, molecular representation is learned from a large dataset of structures with m/z labels. Next, in silico property values are used to continue training, as experimental property data is limited. Finally, the network is further refined by being trained with the experimental data. This allows the network to learn as much as possible at each stage, enabling success with progressively smaller datasets without overfitting. Once trained, the network can be used to predict chemical properties directly from structure, as well as generate candidate structures with desired chemical properties. Our approach is orders of magnitude faster than first-principles simulation for CCS property prediction. Additionally, the ability to generate novel molecules along manifolds, defined by chemical property analogues, positions DarkChem as highly useful in a number of application areas, including metabolomics and small molecule identification, drug discovery and design, chemical forensics, and beyond.

Colby, Sean M.↗

DOE OSTI2020

Carbon-Negative Biofuel Production

Achievement of the 1.5 °C limit for global temperature increase relies on the large-scale deployment of carbon dioxide removal (CDR) technologies. In this article, we explore two CDR technologies: soil carbon sequestration (SCS), and carbon capture and storage (CCS) integrated with cellulosic biofuel production. These CDR technologies are applied as part of decentralized biorefinery systems processing corn stover and unfertilized switchgrass grown in riparian zones in the Midwestern United States. Cover crops grown on corn-producing lands are chosen from the SCS approach, and biogenic CO 2 in biorefineries is captured, transported by pipeline, and injected into saline aquifers. The decentralized biorefinery system using SCS, CCS, or both can produce carbon-negative cellulosic biofuels (≤-22.2 gCO 2 MJ –1 ). Meanwhile, biofuel selling prices increase by 15–45% due to CDR costs. Economic incentives (e.g., cover crop incentives and/or a CO 2 tax credit) can mitigate price increases caused by CDR technologies. Lastly, a combination of different CDR technologies in decentralized biorefinery systems is the most efficient method for greenhouse gas (GHG) mitigation, and its total GHG mitigation potential in the Midwest is 0.16 GtCO 2 year –1 .

09 BIOMASS FUELS↗

DOE OSTI2019

Techno-Economic Analysis of an Intensified Integrated Gasification Combined Cycle (IGCC) Power Plant Featuring a Combined Membrane Reactor - Adsorptive Reactor (MR-AR) System

In this work, the novel concept of a combined membrane-adsorptive reactor sequence (MRAR) is developed and implemented in an Integrated Gasification Combined Cycle (IGCC) plant. This novel MR-AR IGCC plant is subsequently analyzed from an economic viewpoint through a techno-economic analysis (TEA) of the proposed plant. This novel design can achieve over 90% carbon capture without the use of a Dual-Stage Selexol unit. The resultant intensified design is more efficient from both an economic and power production perspective than the traditional IGCC plants with pre-combustion Carbon-Capture Storage (CCS) technology. The COMSOL software package is utilized to simulate the MR-AR sequence proposed in this work, and the UNISIM software (HoneywellTM) is used to create an intensified process flowsheet of the proposed MR-AR IGCC plant, which is subsequently heat-integrated. The TEA developed for the MR-AR IGCC power plant will be used to identify the extent of process intensification the proposed design has over the traditional IGCC plants with pre-combustion CCS. Furthermore, the results demonstrate a reduction in both the cost-of-electricity (COE) and in the capital cost of the proposed design over the baseline case.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Anion Exchange Membrane Water Electrolysis Using a Catalyst-Coated Membrane Cathode

A catalyst-coated membrane (CCM) approach to electrode fabrication for high pH water electrolysis offers enhanced interfacial contact between the catalyst layer and the membrane surface in comparison to the catalyst-coated substrate (CCS) electrode configuration. The CCM facilitates enhanced ionic and water transport between the cathode and the anion exchange membrane (AEM). This advantage is particularly significant with AEM water electrolysis (compared to proton exchange membrane water electrolysis) because the cathode typically operates under dry conditions and relies solely on diffusive water transport across the AEM from the liquid-fed anode. This study presents a direct performance comparison between CCS and CCM cathode configurations using identical hydrogen evolution reaction (HER) catalysts and other components. The use of a pseudo-reference electrode integrated into the membrane electrode assembly enabled detailed analysis of the CCM cathode polarization behavior. Surface characterization provided insight into the degradation mechanisms associated with the CCM configuration. Optimization of the cathode ionomer cross-link density improved both the cathode polarization performance and the electrolysis device durability. Further optimization of the HER catalyst loading in the CCM cathode resulted in additional gains in the electrolysis efficiency. Collectively, these findings offer valuable guidance for the design and fabrication of high-performance, durable AEM electrolysis CCMs.

Water electrolysis↗

DOE OSTI2019

Using Heat as a Predictor of CO 2 Breakthrough in Highly Heterogeneous Reservoirs

Injecting supercritical CO 2 into the subsurface changes the temperature, pressure, and geochemistry of the storage reservoir. Understanding these perturbations within the reservoir may be used to monitor the CO 2 plume during a carbon capture and sequestration (CCS) project. Here we analyze results from 1-D, 2-D, and 3-D numerical modeling studies to investigate how the thermal signature of the CO 2 -water system evolves during CCS. These models show that the thermodynamic processes of the CO 2 -water system results in a characteristic thermal profile within a homogeneous storage reservoir during a CO 2 injection. This thermal signature is characterized by warming front of up to 4 °C, which is caused by CO 2 dissolution and migrates contemporaneously with free-phase CO 2 migration. When reservoir properties are highly heterogeneous, this thermal front travels well ahead of free-phase CO 2 , thus implying that thermal monitoring may be an effective predictor of CO 2 breakthrough.

58 GEOSCIENCES↗

DOE OSTI2022

Multi‐Layered Systems for Permanent Geologic Storage of CO 2 at the Gigatonne Scale

Abstract The effectiveness of Carbon Capture and Storage (CCS) as an imperative decarbonization technology relies on the sealing capacity of a fine‐grained caprock to permanently store CO 2 deep underground. Uncertainties in assessing the caprock sealing capacity increase with the spatial and temporal scales and may delay CCS deployment at the gigatonne scale. We have developed a computationally efficient transport model to capture the dynamics of basin‐wide upward CO 2 migration in a multi‐layered setting over geological time scales. We find that massive capillary breakthrough and viscous flow of CO 2 , even through pervasively fractured caprocks, are unlikely to occur and compromise the storage security. Potential leakage from the injection reservoir is hampered by repetitive layering of overlying caprocks. This finding agrees with geologic intuition and should be understandable by the public, contributing to the development of climate policies around this technology with increased confidence that CO 2 will be indefinitely contained in the subsurface.

58 GEOSCIENCES↗

DOE OSTI2023

Impacts of Permeability Heterogeneity and Background Flow on Supercritical CO 2 Dissolution in the Deep Subsurface

Motivated by CO 2 capture and sequestration (CCS) design considerations, we consider the coupled effects of permeability heterogeneity and background flow on the dissolution of a supercritical CO 2 lens into an underlying deep, confined aquifer. We present the results of a large-scale Monte Carlo simulation study examining the interaction of background flow rate and three parameters describing multi-Gaussian log-permeability fields: mean, variance, and correlation length. Hundreds of high-resolution simulations were performed using the PFLOTRAN finite volume software to model CO 2 dissolution in a kilometer-scale aquifer over 1,000 years. Predictive dimensionless scaling relationships relating CO 2 dissolution rate to heterogeneity statistics, Rayleigh (Ra) and Péclet (Pe) numbers were developed for both gravitationally dominated free convection to background flow-dominated forced convection regimes. An empirical criterion, Pe = Ra 3/4 , was discovered for regime transition. All simulations converged quickly to a quasi-steady, approximately linear dissolution rate. However, this rate displayed profound variability between permeability field realizations sharing the same heterogeneity statistics, even under mild permeability heterogeneity. In general, increased heterogeneity was associated with a lower mean and higher variance of dissolution rate, undesirable from a CCS design perspective. The relationship between dissolution rate and background flow was found to be complex and nonlinear. Dimensionless scaling relationships were uncovered for a number of special cases. Results call into question the validity of the Boussinesq approximation in the context of modest-to-high background flow rates and the general applicability of numerical simulations without background flow.

42 ENGINEERING↗

DOE OSTI2022

Thermodynamic approach for enhancing superconducting critical current performance

Abstract The addition of artificial pinning centers has led to an impressive increase in the critical current density ( J c ) of superconductors, enabling record-breaking all-superconducting magnets and other applications. The J c of superconductors has reached ~0.2–0.3 J d , where J d is the depairing current density, and the numerical factor depends on the pinning optimization. By modifying λ and/or ξ, the penetration depth and coherence length, respectively, we can increase J d . For (Y 0.77 Gd 0.23 )Ba 2 Cu 3 O y ((Y,Gd)123), we can achieve this by controlling the carrier density, which is related to λ and ξ. We can also tune λ and ξ by controlling the chemical pressure in Fe-based superconductors, i.e., BaFe 2 (As 1− x P x ) 2 films. The variation in λ and ξ leads to an intrinsic improvement in J c via J d , allowing extremely high values of J c of 130 MA/cm 2 and 8.0 MA/cm 2 at 4.2 K, consistent with an enhancement in J d of a factor of 2 for both incoherent nanoparticle-doped (Y,Gd)123 coated conductors (CCs) and BaFe 2 (As 1− x P x ) 2 films, showing that this new material design is useful for achieving high critical current densities in a wide array of superconductors. The remarkably high vortex-pinning force in combination with this thermodynamic and pinning optimization route for the (Y,Gd)123 CCs reached ~3.17 TN/m 3 at 4.2 K and 18 T ( H || c ), the highest values ever reported for any superconductor.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2017

High reactivity of deep biota under anthropogenic CO 2 injection into basalt

Basalts are recognized as one of the major habitats on Earth, harboring diverse and active microbial populations. Inconsistently, this living component is rarely considered in engineering operations carried out in these environments. This includes carbon capture and storage (CCS) technologies that seek to offset anthropogenic CO 2 emissions into the atmosphere by burying this greenhouse gas in the subsurface. Here, we show that deep ecosystems respond quickly to field operations associated with CO 2 injections based on a microbiological survey of a basaltic CCS site. Acidic CO 2 -charged groundwater results in a marked decrease (by ~ 2.5–4) in microbial richness despite observable blooms of lithoautotrophic iron-oxidizing Betaproteobacteria and degraders of aromatic compounds, which hence impact the aquifer redox state and the carbon fate. Host-basalt dissolution releases nutrients and energy sources, which sustain the growth of autotrophic and heterotrophic species whose activities may have consequences on mineral storage.

58 GEOSCIENCES↗

DOE OSTI2023

Field programmable spin arrays for scalable quantum repeaters

The large scale control over thousands of quantum emitters desired by quantum network technology is limited by the power consumption and cross-talk inherent in current microwave techniques. Here we propose a quantum repeater architecture based on densely-packed diamond color centers (CCs) in a programmable electrode array, with quantum gates driven by electric or strain fields. This ‘field programmable spin array’ (FPSA) enables high-speed spin control of individual CCs with low cross-talk and power dissipation. Integrated in a slow-light waveguide for efficient optical coupling, the FPSA serves as a quantum interface for optically-mediated entanglement. We evaluate the performance of the FPSA architecture in comparison to a routing-tree design and show an increased entanglement generation rate scaling into the thousand-qubit regime. Our results enable high fidelity control of dense quantum emitter arrays for scalable networking.

42 ENGINEERING↗

DOE OSTI2025

Conformally coated scaffold design using water-tolerant Pr 1.8 Ba 0.2 NiO 4.1 for protonic ceramic electrochemical cells with 5,000-h electrolysis stability

Protonic ceramic electrochemical cells (PCECs) have potential as long-duration energy storage systems. However, their operational stability is limited under industrially relevant conditions due to the intrinsic chemical instability of doped barium cerate-based electrolytes and oxygen electrodes against H 2 O, as well as the poor electrode–electrolyte interfacial contact. Here, in this study, we present a conformally coated scaffold (CCS) design to comprehensively address these issues. A porous proton-conducting scaffold is constructed and conformally coated with Pr 1.8 Ba 0.2 NiO 4.1 electrocatalyst, which has high chemical stability against H 2 O, triple conductivity and hydration capability, and protects vulnerable electrolytes from H 2 O. The CCS structure consolidates the electrode–electrolyte interfacial bonding to enable fast proton transfer in the percolated network. This design enables PCECs to reach electrolysis stability for 5,000 h at −1.5 A cm−2 and 600 °C in 40% H 2 O. This work provides a general strategy to stabilize PCECs and offers guidance for designing resilient and stable solid-state energy storage systems.

Protonic ceramic electrochemical cell↗

DOE OSTI2021

QM7-X, a comprehensive dataset of quantum-mechanical properties spanning the chemical space of small organic molecules

We introduce QM7-X, a comprehensive dataset of 42 physicochemical properties for ≈4.2 million equilibrium and non-equilibrium structures of small organic molecules with up to seven non-hydrogen (C, N, O, S, Cl) atoms. To span this fundamentally important region of chemical compound space (CCS), QM7-X includes an exhaustive sampling of (meta-)stable equilibrium structures—comprised of constitutional/structural isomers and stereoisomers, e.g., enantiomers and diastereomers (including cis-/trans- and conformational isomers)—as well as 100 non-equilibrium structural variations thereof to reach a total of ≈4.2 million molecular structures. Computed at the tightly converged quantum-mechanical PBE0+MBD level of theory, QM7-X contains global (molecular) and local (atom-in-a-molecule) properties ranging from ground state quantities (such as atomization energies and dipole moments) to response quantities (such as polarizability tensors and dispersion coefficients). By providing a systematic, extensive, and tightly-converged dataset of quantum-mechanically computed physicochemical properties, we expect that QM7-X will play a critical role in the development of next-generation machine-learning based models for exploring greater swaths of CCS and performing in silico design of molecules with targeted properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2017

Impact of naturally leaking carbon dioxide on soil properties and ecosystems in the Qinghai-Tibet plateau

One of the major concerns for CO 2 capture and storage (CCS) is the potential risk of CO 2 leakage from storage reservoirs on the shallow soil property and vegetation. This study utilizes a naturally occurring CO 2 leaking site in the Qinghai-Tibet Plateau to analog a “leaking CCS site”. Our observations from this site indicates that long-term CO 2 invasion in the vadose zone results in variations of soil properties, such as pH fluctuation, slight drop of total organic carbon, reduction of nitrogen and phosphorus, and concentration changes of soluble ions. Simultaneously, XRD patterns of the soil suggest that crystallization of soil is enhanced and mineral contents of calcite and anorthite in soil are increased substantially. Parts of the whole ecosystem such as natural wild plants, soil dwelling animals and microorganisms in shallow soil are affected as well. Under a moderate CO 2 concentration (less than 110000 ppm), wild plant growth and development are improved, while an intensive CO2 flux over 112000 ppm causes adverse effects on the plant growth, physiological and biochemical system of plants, and crop quality of wheat. Results of this study provide valuable insight for understanding the possible environmental impacts associated with potential CO 2 leakage into shallow sediments at carbon sequestration sites.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2013

Prospective life-cycle modeling of a carbon capture and storage system using metal-organic frameworks for CO2 capture

Metal-organic frameworks (MOFs) are promising new material media for carbon dioxide (CO2) capture. Their tunable adsorption patterns may allow relatively efficient separation of gases, e.g. from power plant exhaust. Here we conduct scenario-based prospective life-cycle system modeling to estimate the potentials and implications of large-scale MOF application for post-combustion carbon capture and storage (CCS), and estimate the source and magnitude of uncertainties. The methodological approach includes parametric system modeling to quantify relations between system components; scenario projections of plausible pathways for system scale-up; proxy data on analogous materials and processes; and uncertainty analysis of parameter significance. We estimate the system-wide material and energy flows and economic costs associated with projected large-scale CCS deployment. We compare the performance of a MOF-based system to currently more mature amine-based capture technology. We discuss balancing two critical factors that determine the success of CO2 capture media: thermodynamic efficiency of the capture/regeneration cycle, and life-cycle embodied energy and cost of the material and its ancillary systems.

Sathre, R↗

DOE OSTI2016

Cutting the cost of carbon capture: a case for carbon capture and utilization

A significant part of the cost for carbon capture and storage (CCS) is related to the compression of captured CO 2 to its supercritical state, at 150 bar and typically 99% purity. These stringent conditions may however not always be necessary for specific cases of carbon capture and utilization (CCU). In this manuscript, we investigate how much the parasitic energy of an adsorbent-based carbon capture process may be lowered by utilizing CO 2 at 1 bar and adapting the final purity requirement for CO 2 from 99% to 70% or 50%. We compare different CO 2 sources: the flue gases of coal-fired or natural gas-fired power plants and ambient air. We evaluate the carbon capture performance of over 60 nanoporous materials and determine the influence of the initial and final CO 2 purity on the parasitic energy of the carbon capture process. Moreover, we demonstrate the underlying principles of the parasitic energy minimization in more detail using the commercially available NaX zeolite. Finally, the calculated utilization cost of CO 2 is compared with the reported prices for CO 2 and published costs for CCS.

36 MATERIALS SCIENCE↗

DOE OSTI2011

Assessing the health risks of natural CO2 seeps in Italy

Industrialized societies which continue to use fossil fuel energy sources are considering adoption of Carbon Capture and Storage (CCS) technology to meet carbon emission reduction targets. Deep geological storage of CO2 onshore faces opposition regarding potential health effects of CO2 leakage from storage sites. There is no experience of commercial scale CCS with which to verify predicted risks of engineered storage failure. Studying risk from natural CO2 seeps can guide assessment of potential health risks from leaking onshore CO2 stores. Italy and Sicily are regions of intense natural CO2 degassing from surface seeps. These seeps exhibit a variety of expressions, characteristics (e.g., temperature/ flux), and location environments. Here we quantify historical fatalities from CO2 poisoning using a database of 286 natural CO2 seeps in Italy and Sicily. We find that risk of human death is strongly influenced by seep surface expression, local conditions (e.g., topography and wind speed), CO2 flux, and human behavior. Risk of accidental human death from these CO2 seeps is calculated to be 10-8 year-1 to the exposed population. This value is significantly lower than that of many socially accepted risks. Seepage from future storage sites is modeled to be less than Italian natural flux rates. With appropriate hazard management, health risks from unplanned seepage at onshore storage sites can be adequately minimized.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Establishment of a Nationwide Plasma Science and Fusion Energy Certification and Apprenticeship Programs

Here we propose the establishment of a national Plasma Science and Fusion Energy training program that will combine professional development certification courses with hands-on apprenticeship opportunities. The program should be developed by a collaboration of stakeholders (academia, national laboratories, and industry) and should offer pathways for students from community colleges (CCs), minority-serving institutions (MSIs), high school graduates, and veterans. We argue that certification courses offer fast and flexible discipline-specific education that can be rapidly translated into marketable skills through hands-on apprenticeship opportunities. Furthermore, we first list major findings and recommendations related to the fusion workforce and discuss how to address them through the establishment of the proposed training program. We then highlight the appropriateness of this format for engagement with CCs, MSIs, high schools, and veteran employment services. In the final section, we provide a strategy for the establishment of the program, along with a tentative timeline and projected costs.

Certification↗