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Firestone Walker Brewing Company (FWBC), Paso Robles, California, owns a 1-million-barrel (BBL) brewery that requires up to 5 MW of process heat in form of saturated steam. Firestone Walker Brewery has set a goal of reducing carbon emissions by 50% for our 1 million BBL brewery.
Leaf mass per area (LMA), leaf carbon and nitrogen content of vegetation (Arctagrostis latifolia, Petasites frigidus) within warming chambers and paired control plots. Samples include gas exchange measurement leaves and an end of season bulk harvest. The files included in this data package are in .csv format, and include 2 data files and 4 metadata files. See related datasets for plant physiology, phenology and environmental conditions of these samples. These data were collected in 2018 as part of a series of single-season warming experiments on tundra vegetation on the Barrow Environmental Observatory (BEO), Utqiagvik, Alaska. A different plant species was targeted each year, over four experimental years from 2017–2021. Each year, five warming chambers and paired ambient control plots were deployed from around the time of snowmelt in mid-June through to mid-September. Average seasonal warming of 3–4°C was achieved using Zero Power Warming (ZPW) chambers (Lewin et al, 2017).The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).
The study of defect centers in silicon has been recently reinvigorated by their potential applications in optical quantum information processing. A number of silicon defect centers emit single photons in the telecommunication O-band, making them promising building blocks for quantum networks between computing nodes. The two-carbon G-center, self-interstitial W-center, and spin-1/2 T-center are the most intensively studied silicon defect centers, yet despite this, there is no consensus on the precise configurations of defect atoms in these centers, and their electronic structures remain ambiguous. Here, in this work, we employ ab initio density functional theory to characterize these defect centers, providing insight into the relaxed structures, band structures, and photoluminescence spectra, which are compared to experimental results. Motivation is provided for how these properties are intimately related to the localization of electronic states in the defect centers. In particular, we present the calculation of the zero-field splitting for the excited triplet state of the G-center defect as the structure is linearly interpolated from the A-configuration to the B-configuration, showing a sudden increase in the magnitude of the D zz component of the zero-field-splitting tensor. By performing projections onto the local orbital states of the defect, we analyze this transition in terms of the symmetry and bonding character of the G-center defect, which sheds light on its potential application as a spin-photon interface.
A strongly interacting plasma of linearly dispersing electron and hole excitations in two spatial dimensions (2D), also known as a Dirac fluid, can be captured by relativistic hydrodynamics and shares many universal features with other quantum critical systems. Here, we propose a one-dimensional (1D) model to capture key aspects of the 2D Dirac fluid while including lattice effects and being amenable to nonperturbative computation. When interactions are added to the Dirac-like 1D dispersion without opening a gap, we show that this kind of irrelevant interaction is able to preserve Fermi-liquid-like quasiparticle features while relaxing a zero-momentum charge current via collisions between particle-hole excitations, leading to resistivity that is linear in temperature via a mechanism previously discussed for large-diameter metallic carbon nanotubes. We further provide a microscopic lattice model and obtain numerical results via density-matrix renormalization group simulations, which support the above physical picture. The limits on such fast relaxation at strong coupling are of considerable interest because of the ubiquity of bad metals in experiments.
Over the past decade, the drive to reduce greenhouse gas emissions and to increase thermal efficiency for turbomachinery has invigorated the application of supercritical carbon dioxide (sCO2) power cycles for energy generation. Compared to the industry standard air cycles, sCO2 applications hold the potential for several advantages, including higher efficiencies, smaller footprints, and zero greenhouse gas emissions. However, like any turbomachinery application, the turbine inlet temperature must increase to increase thermal efficiency. This introduces the need for internal cooling features to avoid material failure as operating conditions rise. Two standard features include pin fin turbulators in the trailing edge and jet impingement in the airfoil's leading edge. Over the past several decades, these features have been the subject of extensive research. However, the move to the sCO2 operating environment creates the need to re-visit these features to quantify the heat transfer capabilities within this supercritical cooling environment. The first objective of this paper is to discuss the development of the experimental demonstration for internal heat transfer testing at 200 bar and 400 Celsius, which sits well within the CO2 supercritical region. Next, the heat transfer for pin fin turbulators and single-jet impingement in the sCO2 environment is compared to existing air data-derived correlations to quantify any deviations from literature correlations. Finally, the experimental process aims to validate internal cooling conjugate heat transfer numerical simulations for sCO2 turbines.
This paper explores the role of electricity in achieving economy-wide net-zero CO2 emissions by 2050 in the United States based on results from 17 models as part of the 37th Stanford Energy Modeling Forum (EMF-37). In the study's Net-Zero scenario, the models use diverse pathways to achieve net-zero emissions by 2050, with gross energy-related residual emissions ranging from 17.2 to 66.6 % of 2020 levels. Electricity consistently emerges as central to achieving net-zero, with models projecting rapid electrification of end-uses and rapidly declining CO2 intensity of electricity. However, the extent of electrification and the technology mix to decarbonize the power sector vary considerably across models. In the Net-Zero scenario, electricity is projected to evolve from ~20 % of final energy in 2020 to 17-63 % in 2050 across the models driven by electrification in all sectors-buildings, industry, and transportation-and, to a lesser extent by direct air capture. By 2050, total electricity consumption increases by 24-176 % (relative to 2020), accompanied by significant expansion in renewable electricity production. Together, solar and wind generation grows by 175-834 %, supplying 45-90 % of total electricity in 2050, with wind achieving slightly higher shares than solar. Electricity storage technologies are deployed at scale to support wind and solar generation. The electricity generation mix varies across models: some project almost complete reliance on renewables, while others see a substantial role for natural gas, often with carbon capture and storage. This paper synthesizes the rich diversity of modeling approaches and results, highlighting differing views on how key drivers of electricity demand and supply might evolve.
China’s pledge to reach carbon neutrality before 2060 is an ambitious goal and could provide the world with much-needed leadership on how to limit warming to +1.5°C warming above preindustrial levels by the end of the century. But the pathways that would achieve net zero by 2060 are still unclear, including the role of negative emissions technologies. We use the Global Change Analysis Model to simulate how negative emissions technologies, in general, and direct air capture (DAC) in particular, could contribute to China’s meeting this target. Our results show that negative emissions could play a large role, offsetting on the order of 3 GtCO 2 per year from difficult-to-mitigate sectors, such as freight transportation and heavy industry. This includes up to a 1.6 GtCO 2 per year contribution from DAC, constituting up to 60% of total projected negative emissions in China. But DAC, like bioenergy with carbon capture and storage and afforestation, has not yet been demonstrated anywhere approaching the scales required to meaningfully contribute to climate mitigation. Deploying NETs at these scales will have widespread impacts on financial systems and natural resources, such as water, land and energy in China.
Zero-gap microbial electrolysis cells (MECs) have demonstrated large current and hydrogen production rates from defined substrates in synthetic media, but operation with real waste streams has yet to be proved. This study evaluated the performance and 30-days stability of zero-gap MECs operated with effluent from a single-stage anaerobic digester. The system achieved a maximum current density of 8.8 ± 0.3 A/m 2 with a hydrogen production rate of 32 ± 6 L/L-d, and during 30 days of continuous operation, sustained an average current density of 7 ± 2 A/m 2 and a hydrogen production rate of 20.8 ± 0.2 L/L-d. Carbonate precipitation was identified as a major challenge to long-term stability, and mild acid washing effectively mitigated its adverse effects. The low buffer capacity of the effluent was primarily limiting performance. Furthermore, these findings underscore the significant impact of wastewater chemistry on MEC operation and validate the feasibility of utilizing real waste streams as viable feedstocks for biohydrogen production in zero-gap configurations.
Here, bacterial cellulose (BC) exhibits beneficial properties for use in biomedical applications but is limited by its lack of tunable transparency capabilities. To overcome this deficiency, a novel method to synthesize transparent BC materials using an alternative carbon source, namely arabitol, was developed. Characterization of the BC pellicles was performed for yield, transparency, surface morphology, and molecular assembly. Transparent BC was produced using mixtures of glucose and arabitol. Zero percent arabitol pellicles exhibited 25% light transmittance, which increased with increasing arabitol concentration through to 75% light transmittance. While transparency increased, overall BC yield was maintained indicating that the altered transparency may be induced on a micro-scale rather than a macro-scale. Significant differences in fiber diameter and the presence of aromatic signatures were observed. Overall, this research outlines methods for producing BC with tunable optical transparency, while also bringing new insight to insoluble components of exopolymers produced by Komagataeibacter hansenii.
The detailed design of a 300 MWe, utility scale oxy-fuel turbine has been completed for purposed operation in the sCO2 direct fired Allam-Fetvedt cycle, targeting near-zero emissions and a 50% LHV system efficiency. The turbine and its supporting plant aim to offer a lower levelized cost of energy than a natural gas combined cycle plant employing carbon capture. The oxy-fuel turbine conditions include an inlet temperature of 1150°C and inlet pressure of 305 bar, representing temperatures near that of a gas turbine simultaneously with pressures near an ultra-supercritical steam turbine. The combustor housing and turbine designs were completed according to the ASME BPVC; the turbine case specifically incorporates a multi-body design with inner high-pressure barrel case and low-pressure (30 bar) horizontally split outer case of low-chromium steel material. Lateral rotordynamic evaluation demonstrated acceptable vibration response for a range of imbalance conditions per API standards. The cooling flow required in the six-stage turbine flowpath for 30,000 hr. blade and stator lifetime is predicted through thermal and structural modeling of the first stage. The provided cost estimate of the turbine is formed through a combination of scaled up-costs from procured 10 MWe scale sCO2 turbomachinery hardware, and vendor provided budgetary quotes of larger components including the turbine case requiring casting, welding, and final machining processes. The performance and cost estimation of the oxy-fuel turbine predicted for the completed detailed design provides important information towards future development needs for market penetration of utility scale direct fired sCO2 power cycles.
Abstract Existing studies indicate that future global carbon dioxide (CO 2 ) removal (CDR) efforts could largely be concentrated in Asia. However, there is limited understanding of how individual Asian countries and regions will respond to varying and uncertain scales of future CDR concerning their energy-land-water system. We address this gap by modeling various levels of CDR-reliant pathways under climate change ambitions in Asia. We find that high CDR reliance leads to residual fossil fuel and industry emissions of about 8 Gigatonnes CO 2 yr −1 (GtCO 2 yr −1 ) by 2050, compared to less than 1 GtCO 2 yr −1 under moderate-to-low CDR reliance. Moreover, expectations of multi-gigatonne CDR could delay the achievement of domestic net zero CO 2 emissions for several Asian countries and regions, and lead to higher land allocation and fertilizer demand for bioenergy crop cultivation. Here, we show that Asian countries and regions should prioritize emission reduction strategies while capitalizing on the advantages of carbon removal when it is most viable.
Hydrogen has the potential to be a key contributor toward a low-carbon economy. Generating hydrogen by electrolysis using renewable energy is one way to support a decarbonized economy; however, its cost is not typically competitive with the carbon-emitting incumbent technology, steam methane reforming. The ability of electrolysis to integrate with electricity markets presents a unique cost reduction opportunity due to the perceived future availability of low and zero-marginal cost renewable energy sources. Additionally, as renewables, and particularly, photovoltaics are installed on the grid, they have a value deflation effect. This work evaluates solar-electrolysis configurations using a mathematical programming framework to maximize system net present value. The framework has been tested with specific weather conditions and financial mechanisms in California. Our findings indicate that a spectrum of potential cost competitive solutions is available for systems that (i) have market configurations resembling hybrid retail/wholesale, resulting in a hydrogen production cost range of US$6.2 kg-1–US$6.6 kg-1, or full wholesale market participation, reducing production cost to US$2.6 kg-1–US$3.1 kg-1, and (ii) achieve projected future cost reductions.
The accumulation of amyloid plaques and increased brain redox burdens are neuropathological hallmarks of Alzheimer’s disease. Altered metabolism of essential biometals is another feature of Alzheimer’s, with amyloid plaques representing sites of disturbed metal homeostasis. Despite these observations, metal-targeting disease treatments have not been therapeutically effective to date. A better understanding of amyloid plaque composition and the role of the metals associated with them is critical. To establish this knowledge, the ability to resolve chemical variations at nanometer length scales relevant to biology is essential. Here, we present a methodology for the label-free, nanoscale chemical characterization of amyloid plaques within human Alzheimer’s disease tissue using synchrotron X-ray spectromicroscopy. Our approach exploits a C–H carbon absorption feature, consistent with the presence of lipids, to visualize amyloid plaques selectively against the tissue background, allowing chemical analysis to be performed without the addition of amyloid dyes that alter the native sample chemistry. Using this approach, we show that amyloid plaques contain elevated levels of calcium, carbonates, and iron compared to the surrounding brain tissue. Chemical analysis of iron within plaques revealed the presence of chemically reduced, low-oxidation-state phases, including ferromagnetic metallic iron. The zero-oxidation state of ferromagnetic iron determines its high chemical reactivity and so may contribute to the redox burden in the Alzheimer’s brain and thus drive neurodegeneration. Ferromagnetic metallic iron has no established physiological function in the brain and may represent a target for therapies designed to lower redox burdens in Alzheimer’s disease. Additionally, ferromagnetic metallic iron has magnetic properties that are distinct from the iron oxide forms predominant in tissue, which might be exploitable for the in vivo detection of amyloid pathologies using magnetically sensitive imaging. We anticipate that this label-free X-ray imaging approach will provide further insights into the chemical composition of amyloid plaques, facilitating better understanding of how plaques influence the course of Alzheimer’s disease.
Presentation made at the 2024 Annual International Pittsburgh Energy and Carbon Management Conference (PECMC) OCTOBER 7 - 9, 2024 (virtual). The presentation summarized the methodology and results from energy market scenario analyses of the deployment of Direct Air Capture technologies under net-zero CO2 requirements by 2050. The results showed strong deployment of DAC under all scenarios, with increased value of the technology when other CO2 reduction pathways were unavailable or minimized.
Organic–inorganic metal halides (OIMHs) with high-efficiency solar spectrum-like emission are attracting broad and current interest. Here, in this work, five 0D Zn-based hybrid halides are synthesized based on aromatic organic cations with different carbon-chain lengths: C 6 H 5 CH 2 NH 3 + (PMA + ) and C 6 H 5 (CH 2 ) 4 NH 3 + (PBA + ). (PMA) 2 ZnCl 4 exhibits the highest photoluminescence quantum yield of 37.2% of reported Zn-based white-emission OIMHs. The emission spectrum of (PBA) 2 ZnI 4 indicates a color rendering index of 98, which is the highest among single-component white-light-emitting phosphors. Spectral characterizations and density functional theory calculations demonstrate that the extremely broad emission of (PBA) 2 ZnI 4 originates from the synergistic emission of organic cations and self-trapped excitons. The optical properties of the obtained (PMA) 2 ZnBr 4 , (PMA) 2 ZnI 4 ·H 2 O, and (PBA) 2 ZnCl 4 are also characterized for comparison, and with the same organic cations, the PLQY decreases from chloride to bromide to iodide. This work demonstrates that the selection of appropriate organics and halogens can enable fine tuning of single-component white-light emission, satisfying varying needs for solid-state lighting.
Energy effiecient electrochemical conversion of CO 2 to high-demand chemicals and transportation fuels using renewable solar and wind energy is a key technology needed for a high-productivity, low-carbon future. However, the development of scalable, low-cost, active, selective, and stable electrocatalysts remains a key challenge that needs to be overcome to enable high-volume conversion of CO 2 to feedstock chemicals for the chemical industry. In previous work, Lawrence Livermore National Laboratory (LLNL) has developed a rational design platform for dilute alloy transition metal electrocatalysts that promise to make electrochemical CO 2 conversion more energy efficient and selective. In this project, we worked with our industrial partners, Twelve and TotalEnergies, to improve scale up, integration, and stability of LLNL’s dilute alloy catalyst technology into an industry-relevant zero gap electrolyzer platform. Through virtual experiments and data analysis, we designed efficient and cost-effective copper-based catalysts. The catalyst was specifically designed to streamline the slowest and most energy-intensive step of the electrochemical chemical transformation of CO 2 to multi-carbon products – that is making the carbon-carbon bond by dimerization of the reaction intermediate carbon monoxide - resulting in up to 10% improvement in energy efficiency for C 2 products while simultaneously increasing the selectivity towards C 2 products. We tested two different scalable catalyst coating technologies and down-selected magnetron sputtering as the technique that provided the best control over catalyst loading, composition, and morphology. Using this technology, we successfully demonstrated integration of our dilute alloy catalysts into a 100 cm 2 electrolyzer platform with Faradaic efficiencies for ethylene production reaching 40% at a current density of 200 mA/cm 2 . We also developed the technology to integrate a well-defined nanoscale porosity by depositing alloy compositions that were compatible with dealloying, that is, selective leaching of an alloy component to generate nanoscale porosity. We observed that integration of the dealloying-derived nanoporosity improved catalyst performance and stability by leading to a more hydrophobic catalyst/anion exchange membrane interface. Unsolved problems that still need to be addressed are corrosion of the Cu catalyst -specifically if the used catalyst is exposed to air - as well as long term stability do to salt formation/deposition and flooding of the catalyst/electrolyzer flow channels, especially at higher current densities. As we only worked on optimization of catalyst composition, coating thickness, and morphology, further performance optimization will require a system level approach that includes optimization of electrolyzer design and membrane technology.
Wetlands are globally significant carbon storage hotspots. Recent research has suggested that microbially derived metabolites may contribute to soil organic matter formation. Identifying pathways driving the formation of such metabolites is critical to understand the global impact of wetland carbon cycling. Here, we evaluate the presence of chain-elongating organisms converting two to three carbon compounds (i.e., lactic and acetic acid) to medium-chain carboxylic acids (MCCA; i.e., six-carbon caproic acid) in wetland soils. We demonstrate the enrichment of a lactic acid-driven chain-elongating community from wetland soils producing a mixture of butyric and caproic acid. The enriched community was dominated by Clostridiaceae, Ruminococcaceae, and Lachnospiraceae, three families with known chain elongators. Amplicon sequencing identified three Ruminococcaceae and one Clostridiaceae zero-radius OTU (zOTU) that were (i) present in the soil, (ii) enriched over 1% relative abundance in the bioreactor, and (iii) were closely related to known chain elongators. Moreover, close relatives of the three Ruminococcaceae zOTU were also observed in several other wetland microbiomes. From this observation, we conclude that close relatives of known chain elongators, potentially capable of lactic acid-driven MCCA production themselves, are present in wetland soils. This observation may have implications for our understanding of carbon cycling and storage in wetland ecosystems.
Achieving the United States' target of net-zero greenhouse gas emissions by 2050 will require technological transformations and energy sector mitigation. To understand the role of dynamically evolving technologies, identify synergies and dissonance and the effect of allocating limited low-carbon biomass resources in decarbonizing the U.S. economy, we developed the Decarbonization Scenario Analysis Model. A Life Cycle Assessment based approach is implemented considering the U.S. economy as the functional unit, to estimate greenhouse gas mitigation potential for projected energy demand based on several sector-level and cross-sectoral decarbonization pathways. Direct and supply-chain emissions are accounted, resulting from changes in patterns of energy generation and consumption, technology breakthroughs, and reductions in fugitive emissions over time at the granularity of economic sectors, sub-sectors, and end-use. Decarbonization strategies are implemented over a reference case developed using Energy Information Administration (EIA AEO) projection of economic activities for 2020–2050. Based on the considered scenarios, 80–90% economy-wide decarbonization relative to the 2020 reference case is projected. Electrification, low-carbon fuels, and reduction of fugitive emissions play the most significant role to decarbonization. The majority of the remaining emissions are accounted to the supply-chain and end-use emissions from natural gas and diesel fossil-based fuels in heavy duty transportation and heavy industries, highlighting the need for developing low-carbon and carbon-negative alternatives to mitigate those fossil-based carbon emissions.