Energy and techno-economic analysis of bio-based carboxylic acid recovery by adsorption
Recent works have established bio-based carboxylic acids as adaptable precursors to renewable biofuels and chemicals.
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Recent works have established bio-based carboxylic acids as adaptable precursors to renewable biofuels and chemicals.
Here we present a tomographic measurement of the cross-correlation between thermal Sunyaev-Zel’dovich (TSZ) maps from Planck and the Atacama Cosmology Telescope and weak galaxy lensing shears measured during the first three years of observations of the Dark Energy Survey. This correlation is sensitive to the thermal energy in baryons over a wide redshift range and is therefore a powerful probe of astrophysical feedback. We detect the correlation at a statistical significance of 21σ, the highest significance to date. We examine the TSZ maps for potential contaminants, including cosmic infrared background and radio sources, finding that cosmic infrared background has a substantial impact on our measurements and must be taken into account in our analysis. We use the cross-correlation measurements to test different feedback models. In particular, we model the TSZ using several different pressure profile models calibrated against hydrodynamical simulations. Our analysis marginalizes over redshift uncertainties, shear calibration biases, and intrinsic alignment effects. We also marginalize over Ω m and σ 8 using Planck or DES priors. We find that the data prefer the model with a low amplitude of the pressure profile at small scales, compatible with a scenario with strong active galactic nuclei feedback and ejection of gas from the inner part of the halos. When using a more flexible model for the shear profile, constraints are weaker, and the data cannot discriminate between different baryonic prescriptions.
Here, we present a simulation-based cosmological analysis using a combination of Gaussian and non-Gaussian statistics of the weak lensing mass (convergence) maps from the first three years of the Dark Energy Survey. We implement the following: (1) second and third moments; (2) wavelet phase harmonics; (3) the scattering transform. Our analysis is fully based on simulations, spans a space of seven 𝑤 Cold Dark Matter (𝑤 CDM) cosmological parameters, and forward models the most relevant sources of systematics inherent in the data: masks, noise variations, clustering of the sources, intrinsic alignments, and shear and redshift calibration. We implement a neural network compression of the summary statistics, and we estimate the parameter posteriors using a simulation-based inference approach. Including and combining different non-Gaussian statistics is a powerful tool that strongly improves constraints over Gaussian statistics (in our case, the second moments); in particular, the figure of merit (𝑆 8 , Ω m ) is improved by 70% (Λ CDM) and 90% (𝑤 CDM). When all the summary statistics are combined, we achieve a 2% constraint on the amplitude of fluctuations parameter 𝑆 8 ≡ 𝜎 8 (Ω m /0.3) 0.5 , obtaining 𝑆 8 = 0.794 ±0.017 (Λ CDM) and 𝑆 8 = 0.817 ±0.021 (𝑤 CDM), and a ∼10% constraint on Ω m , obtaining Ω m =0.259 ±0.025 (Λ CDM) and Ω m = 0.273 ±0.029 (𝑤 CDM). In the context of the 𝑤 CDM scenario, these statistics also strengthen the constraints on the parameter 𝑤, obtaining 𝑤 <−0.72. The constraints from different statistics are shown to be internally consistent (with a 𝑝-value>0.1 for all combinations of statistics examined). We compare our results to other weak lensing results from the first three years of the Dark Energy Survey data, finding good consistency; we also compare with results from external datasets, such as planck constraints from the cosmic microwave background, finding statistical agreement, with discrepancies no greater than <2.2𝜎.
The Dark Energy Spectroscopic Instrument (DESI) is a Stage IV ground-based dark energy experiment that will measure the expansion history of the Universe using the Baryon Acoustic Oscillation technique. The spectra of 35 million galaxies and quasars over 14000 square degrees will be measured during the life of the experiment. We describe the installation of the major elements of the instrument at the Mayall 4m telescope, completed in late 2019. The previous prime focus corrector, spider vanes, and upper rings were removed from the Mayall’s Serrurier truss and replaced with the newlyconstructed DESI ring, vanes, cage, hexapod, and optical corrector. The new corrector was optically aligned with the primary mirror using a laser tracker system. The DESI focal plane system was integrated to the corrector, with each of its ten 500-fiber-positioner petal segments installed using custom installation hardware and the laser tracker. Ten DESI spectrographs with 30 cryostats were installed in a newly assembled clean room in the Large Coude Room. The ten cables carrying 5000 optical fibers from the positioners in the focal plane were routed down the telescope through cable wraps at the declination and hour angle axes, and their integral slitheads were integrated with the ten spectrographs. The fiber view camera assembly was installed to the Mayall’s primary mirror cell. Servers for the instrument control system replaced existing computer equipment. The fully integrated instrument has been commissioned and is ready to start its operations phase.
If goals set under the Paris Agreement are met, the world may hold warming well below 2 degrees C (1); however, parties are not on track to deliver these commitments (2), increasing focus on policy implementation to close the gap between ambition and action. Recently, the US government passed its most prominent piece of climate legislation to date - the Inflation Reduction Act of 2022 (IRA) - designed to invest in a wide range of programs that, among other provisions, incentivize clean energy and carbon management, encourage electrification and efficiency measures, reduce methane emissions, promote domestic supply chains, and address environmental justice concerns (3). IRA's scope and complexity make modeling important to understand impacts on emissions and energy systems. We leverage results from nine independent, state-of-the-art models to examine potential implications of key IRA provisions, showing economy-wide emissions reductions between 43 and 48% below 2005 levels by 2035.
Per U.S. Department of Energy (DOE) Energy to Communities (E2C) Expert Match Program, National Laboratory of the Rockies (NLR) staff provided Technical Assistance (TA) to Moore Street Seniors, Inc., in Fairbanks, Alaska. NLR provided, within the TA scope of work, a list of Recommendations and Best Practices, as well as Data Analysis and Final Deliverable Development. NLR staff have provided the results within this report and several Energy Efficiency Considerations for Moore Street Seniors Inc. Window replacement considerations and best practices are listed in section 3.8. Building ventilation considerations and best practices are listed in section 3.9. A full list of Energy Efficiency Considerations is listed in section 3.10 of this report.
The Energy to Communities (E2C) peer-learning cohort program provides technical assistance to groups of 15 community entities around a common energy topic over the course of 6 months. Every month, participants join a virtual meeting where they hear from experts and exchange strategies and best practices with their peers. This cohort, "Planning for Major Energy Disruptions in the Southeast" focuses on strategies for entities in the Southeast to quickly recover from impacts to energy infrastructure caused by extreme events, such as severe weather and natural disasters. This presentation focuses on the tradeoffs and relative costs of different strategies to improve outcomes from these extreme events. The workshop is on May 21, 2026.
The U.S. Department of Energy Solar Decathlon® Design Challenge is a collegiate competition that challenges student teams to design high performance buildings that push the boundaries of the industry. In the 2020 competition, DOE is piloting Design Partners, a low-risk opportunity for builders and building owners to harness student innovation and explore zero energy design for current or upcoming projects. Design Partners provide a student team of architects and engineers with project requirements. By the end of the Challenge, Design Partners receive a zero energy alternative and cost estimate for their project. The collaboration allows Design Partners to incorporate innovative concepts such as grid-interactivity, resilience, and low embodied carbon in a low-risk environment and provides the future generation of engineers and architects with invaluable experience designing a building for a client under real-world circumstances. Attendees will leave understanding the “perfect storm” of policy, technology, health, and economic trends that make zero energy buildings desirable and feasible and the value of the U.S. DOE Solar Decathlon to industry. They will also get a sneak peek at innovative solutions 2020 Design Partner pilot projects are bringing to the building industry and how becoming a Design Partner in 2021 could benefit their organization.
The challenges associated with energy efficiency of manufacturing and advanced materials often cannot be addressed through experimentation alone, whether because of scale, complexity, or practicality. High-performance computing (HPC) enables fast tackling of these challenges in the manufacturing sector - vital to achieving net-zero carbon emissions by 2050. The National Renewable Energy Laboratory (NREL) and industry partners leverage HPC to apply advanced modeling, simulation, and data analysis to improve manufacturing efficiency, explore new materials for energy applications, and develop technologies to manage carbon across the life cycle. From improving additive manufacturing processes to increasing the energy efficiency of jet-engine components, advanced computing can help manage emissions produced by manufacturing in a wide variety of ways.
The City of Los Angeles has set ambitious goals to transform its electricity supply, aiming to achieve a 100% renewable energy power system by 2045, along with aggressive electrification targets for buildings and vehicles. To reach these goals, and assess the implications for jobs, electricity rates, the environment, and environmental justice, the Los Angeles City Council passed a series of motions directing the Los Angeles Department of Water and Power (LADWP) to determine the technical feasibility and investment pathways of a 100% renewable energy portfolio standard. The Los Angeles 100% Renewable Energy Study (LA100) is a first-of-its-kind objective, rigorous, and science-based power systems analysis to determine what investments could be made to achieve these goals. The LA100 final report is presented as a collection of 12 chapters and an executive summary, each of which is available as an individual download. This chapter explores pathways to 100% renewable electricity, describing the types of generation resources added, their costs, and how the systems maintain sufficient resources to serve customer demand, including resource adequacy and transmission reliability.
The State and Local Planning for Energy (SLOPE) Platform is a free and easy-to-access online platform that helps energy planners at state and local levels make data-driven decisions to achieve their communities' energy goals.
Project summary, objectives, and outcomes for the Energy Resilience Performance tool are provided. The Energy Resilience Performance tool estimates the resilience benefits of solar energy when included in backup power systems. The code is open source and is integrated into NREL's existing REopt web tool.
The presentation highlights: (i) how DEEC-Tec, advanced through the U.S. DOE's InDEEP Prize, holds the potential to redefine ocean wave energy conversion through modular, embedded energy conversion; (ii) a global scan that identified 158 participants and 35 promising concepts, showcasing strong international momentum; (iii) InDEEP's innovation-first approach and how it complements Wave Energy Scotland's structured Direct Generation research; and (iv) the ongoing and possible future collaborative pathways for co-funded trials, joint metric/standards developments, and maturation of these technologies toward and real-world deployment.
Rising data demands from artificial intelligence (AI) and large language models (LLMs) generating images, videos, and text have prompted increased need for larger and more robust data centers in the United States. Major companies interested in these larger data centers face the choice of linking them to existing regional grids, building stand-alone power supplies onsite, or a combination of both. The request, review, and approval process for new transmission lines to grids in the United States, however, has grown in recent years to times spans rivaling those of new construction for nuclear power plants. Building an islanded power supply for each data center is therefore becoming a prominent option. In this case study, several technologies are modeled in techno-economic simulations for long-term system costs subject to fixed electricity demand from a singular data center. A 250 MWe data center is assumed with additional 50 MWe for resiliency. Techno-economic simulations are conducted using the Holistic Energy Resource Optimization Network (HERON) software, which is a part of the Framework for Optimization of Resources and Economics (FORCE) tool suite. Technologies considered include solar, wind, lithium-ion batteries, and several types of nuclear reactors: large-scale reactors, small modular reactors, and microreactors. A low- and high-cost estimate for each technology is assumed to develop a range of expected economic performance. Low-cost estimates included several clean energy production tax credits. Different combinations of renewable energy generators with nuclear reactors are considered, ranging from a fully renewable-powered data center to a fully nuclear-powered data center. Historic time series of wind and solar availability from the Texas grid are used to train a reduced order model; this model then generates unique time series with similar characteristics of the training dataset. Multiple scenarios of weather and subsequent operations are simulated for each renewable-nuclear combination to determine total costs throughout the project lifetime. Fully renewable-powered configurations required large amounts of installed capacity (GW scale) in the simulations to meet the fixed demand of the data center. This is due to some scenarios in the historical dataset which captured low-wind and low-solar days, requiring over-building of these technologies as well as batteries to compensate for the low amounts of electricity generation. Fully nuclear-powered configurations outperformed the fully renewable and mixed renewable-nuclear configurations in terms of cost, with ranges between $1B and $10B in 2023 USDs compared to $40B+ for fully renewable configurations. Of the nuclear technologies, small modular reactors performed better economically than large-scale nuclear models due to lower projected capital costs, and both performed better than the microreactor models. These results demonstrate the applicability of firm, dispatchable electricity resources from baseload generators like nuclear power plants for operating facilities that run at constant power without daily variability.
Vertical-axis wind turbines offer a compelling path to low-cost, reliable distributed energy that can compete with utility prices for businesses, landowners, and municipalities in rural areas. They generate power by using a main rotor shaft perpendicular to the ground to pick up wind from different directions without a yaw mechanism. However, previous commercialization attempts struggled to account for the unsteady aerodynamics of this design, leading to low power production and/or premature structural failure. To address these challenges, Competitiveness Improvement Project recipient XFlow Energy is building on work completed during three previous CIP funding awards to develop a 30-kW vertical-axis wind turbine that achieves both low costs and high energy output.
Event shape observables have been widely used for precision QCD studies at various lepton and hadron colliders. We present the most accurate calculation of the transverse-energy-energy correlation event shape variable in deep-inelastic scattering. In the framework of soft-collinear effective theory the cross section is factorized as the convolution of the hard function, beam function, jet function and soft function in the back-to-back limit. A close connection to TMD factorization is established, as the beam function when combined with part of the soft function is identical to the conventional TMD parton distribution function, and the jet function is the second moment of the TMD fragmentation function matching coefficient. We validate our framework by comparing the obtained LO and NLO leading singular distributions to the full QCD calculations in the back-to-back limit. We report the resummed transverse-energy-energy correlation distributions up to N 3 LL accuracy matched with the NLO cross section for the production of a lepton and two jets. Our work provides a new way to precisely study TMD physics at the future Electron-Ion Collider.