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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 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Disinfection byproducts formed during drinking water treatment reveal an export control point for dissolved organic matter in a subalpine headwater stream

Changes in climate, season, and vegetation can alter organic export from watersheds. While an accepted tradeoff to protect public health, disinfection processes during drinking water treatment can adversely react with organic compounds to form disinfection byproducts (DBPs). By extension, DBP monitoring can yield insights into hydrobiogeochemical dynamics within watersheds and their implications for water resource management. In this study, we analyzed temporal trends from a water treatment facility that sources water from Coal Creek in Crested Butte, Colorado. These trends revealed a long-term increase in haloacetic acid and trihalomethane formation over the period of 2005-2020. Additionally, disproportionate export of dissolved organic carbon and formation of DBPs that exceeded regulatory guidelines were consistently recorded in association with late spring freshet. Synoptic sampling of the creek in 2020 and 2021 identified a biogeochemical hotspot for organic carbon export in the upper domain of the watershed that contained a prominent fulvic acid-like fluorescent signature. DBP formation potential analyses from this domain yielded similar ratios of dominant DBP species to those formed at the drinking water facility. Spectrometric qualitative analyses of pre and post-reacted waters with hypochlorite indicated ligninlike and condensed hydrocarbon-like molecules were the major reactive chemical classes during chlorine-based disinfection. This study demonstrates how drinking water quality archives can be coupled with synoptic sampling to identify and understand export control points for dissolved organic matter. Resultant understanding can be applied in water treatment and watershed management plans to improve drinking water quality sourced from analogous watersheds.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Fusion Neutron Generator

The proposed code, named FROG (Fusion neutron Generator) is built upon the open-source particle transport Monte Carlo toolkit Geant4. Geant4 provides C++ classes that can be leveraged to build application-specific codes dealing with the transport of particles through matter. Geant4-based codes are applied in high-energy particle physics experiments, medical applications, shielding, and space applications for example. The FROG code allows the user to define the geometry of a neutron converter device shaped as a hollow cylinder, where a neutron breeding material such as lithium deuteride (LiD) is cladded by two concentric cylinders. Such neutron converter is then placed inside a regular nuclear fission reactor, where thermal neutrons will react with the neutron breeder material (typically, Lithium 6), and through a series of reactions, will generate high-energy neutrons – neutrons whose kinetic energy are around 14 MeV. The hollowed central portion can hold a specimen that will be bombarded by high-energy neutrons created inside the neutron breeding material. Figuratively speaking, this type of device transforms neutrons from thermal (~0.625 eV) to fusion (~14 MeV) energies and is sometimes termed “fusion-to-thermal neutron converters” in the literature. The code consists of C++ source file compiled and linked to generate an executable. The user can select the dimensions of the converter (radius, length, and thickness of the breeder material), the breeder material type, the cladding material, and the specimen material that will be activated or irradiated. As input, the neutron flux for a specific location inside a reactor, for instance, positions in ATR, is required. As output, the code predicts the number of high-energy neutrons produced, the total neutron flux and fluence as well as its detailed spectrum. The physics involved in such device is very complex, as it requires modeling neutron transport, light-ion (tritons) transport, as well as fusion reactions. The Geant4 toolkit provides the required physical models.

Martin, NicholasP. [Idaho National Laboratory (INL↗
DOE OSTI2020

Peatland Microbial Community Composition Is Driven by a Natural Climate Gradient

Peatlands are important players in climate change–biosphere feedbacks via long-term net carbon (C) accumulation in soil organic matter and as potential net C sources including the potent greenhouse gas methane (CH 4 ). Interactions of climate, site-hydrology, plant community, and groundwater chemical factors influence peatland development and functioning, including C dioxide (CO 2 ) and CH 4 fluxes, but the role of microbial community composition is not well understood. To assess microbial functional and taxonomic dissimilarities, we used high throughput sequencing of the small subunit ribosomal DNA (SSU rDNA) to determine bacterial and archaeal community composition in soils from twenty North American peatlands. Targeted DNA metabarcoding showed that although Proteobacteria, Acidobacteria, and Actinobacteria were the dominant phyla on average, intermediate and rich fens hosted greater diversity and taxonomic richness, as well as an array of candidate phyla when compared with acidic and nutrient-poor poor fens and bogs. Moreover, pH was revealed to be the strongest predictor of microbial community structure across sites. Predictive metagenome content (PICRUSt) showed increases in specific genes, such as purine/pyrimidine and amino-acid metabolism in mid-latitude peatlands from 38 to 45° N, suggesting a shift toward utilization of microbial biomass over utilization of initial plant biomass in these microbial communities. Overall, there appears to be noticeable differences in community structure between peatland classes, as well as differences in microbial metabolic activity between latitudes. Finally, these findings are in line with a predicted increase in the decomposition and accelerated C turnover, and suggest that peatlands north of 37° latitude may be particularly vulnerable to climate change.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Spectral Mesh-Free Quadrature for Planar Regions Bounded by Rational Parametric Curves

This article presents spectral, mesh-free, Green’s theorem-based numerical quadrature schemes for integrating functions over planar regions bounded by rational parametric curves. Our algorithm proceeds in two steps: (1) We first find intermediate quadrature rules for line integrals along the region’s boundary curves corresponding to Green’s theorem. (2) We then use a high-order quadrature rule to compute the numerical antiderivative of the integrand along a coordinate axis, which is used to evaluate the Green’s theorem line integral. We present two methods to compute the intermediate quadrature rule. The first is spectrally accurate (it converges faster than any algebraic order with respect to number of quadrature points) and is relatively easy to implement, but has no guarantee of polynomial exactness. The second guarantees exactness for polynomial integrands up to a pre-specified degree with an a priori-known number of quadrature points and retains the convergence properties of the first, but is slightly more complicated. The quadrature schemes have applications to computation of geometric moments, immersogeometric analysis, conservative field transfer between high-order meshes, and initialization of multi-material simulations with rational geometry. We compare the quadrature schemes produced using our method to other methods in the literature and show that they are much more efficient both in terms of number of quadrature points and computational time. We provide an open-source implementation of the algorithm in MATLAB.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Understanding latent timescales in neural ordinary differential equation models of advection-dominated dynamical systems

The neural ordinary differential equation (ODE) framework has shown considerable promise in recent years in developing highly accelerated surrogate models for complex physical systems characterized by partial differential equations (PDEs). For PDE-based systems, state-of-the-art neural ODE strategies leverage a two-step procedure to achieve this acceleration: a nonlinear dimensionality reduction step provided by an autoencoder, and a time integration step provided by a neural-network based model for the resultant latent space dynamics (the neural ODE). This work explores the applicability of such autoencoder-based neural ODE strategies for PDEs in which advection terms play a critical role. More specifically, alongside predictive demonstrations, physical insight into the sources of model acceleration (i.e., how the neural ODE achieves its acceleration) is the scope of the current study. Such investigations are performed by quantifying the effects of both autoencoder and neural ODE components on latent system time-scales using eigenvalue analysis of dynamical system Jacobians. To this end, the sensitivity of various critical training parameters – de-coupled versus end-to-end training, latent space dimensionality, and the role of training trajectory length, for example – to both model accuracy and the discovered latent system timescales is quantified. Furthermore, this work specifically uncovers the key role played by the training trajectory length (the number of rollout steps in the loss function during training) on the latent system timescales: larger trajectory lengths correlate with an increase in limiting neural ODE time-scales, and optimal neural ODEs are found to recover the largest time-scales of the full-order (ground-truth) system. Demonstrations are performed across fundamentally different unsteady fluid dynamics configurations influenced by advection: (1) the Kuramoto–Sivashinsky equations (2) Hydrogen-Air channel detonations (the compressible reacting Navier–Stokes equations with detailed chemistry), and (3) 2D Atmospheric flow.

Advection-dominated dynamical systems↗
DOE OSTI2021

Dairy Methane Emissions in California's San Joaquin Valley Inferred With Ground‐Based Remote Sensing Observations in the Summer and Winter

Abstract The dairy industry in the San Joaquin Valley (SJV) is one of California’s largest methane (CH 4 ) sources. Reducing dairy emissions is a priority for the state’s climate change plans. Observations of current dairy CH 4 emissions are key to monitoring actions taken toward this goal. To help support this, we present new ground‐based measurements of atmospheric column‐averaged CH 4 mixing ratio (XCH 4 ) gradients across a group of 600 dairies in the central SJV using EM27/SUN solar spectrometers. We used measurements from the 2019 summer and 2020 winter seasons for a top‐down emission inversion based on the WRF‐STILT model. Our top‐down estimates of the region’s dairy emissions range from 90% to 183% of the current CALGEM inventory’s emissions of 277 Gg/yr. In contrast to the strong temperature dependence found by earlier dairy CH 4 emission studies, we also find that our top‐down emissions during the winter measurement days are comparable to the summer measurement days, possibly due to seasonal changes in dairy management practices and meteorological conditions. Furthermore, we find significant interday variability in our measurements and find that our emission estimates overlap with earlier top‐down studies and bottom‐up inventories in this region. Our study demonstrates how analysis of ground‐based remotely sensed CH 4 gradient observations can help improve our understanding of CH 4 sources at scales relevant to mitigation policy. It also reflects the need for long‐term monitoring of CH 4 emissions in the region and at individual facilities to better understand their emissions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Synthesis of 2D layered transition metal (Ni, Co) hydroxides via edge-on condensation

Abstract Layered transition metal hydroxides (LTMHs) with transition metal centers sandwiched between layers of coordinating hydroxide anions have attracted considerable interest for their potential in developing clean energy sources and storage technologies. However, two-dimensional (2D) LTMHs remain largely understudied in terms of physical properties and applications in electronic devices. Here, for the first time we report > 20 μm α-Ni(OH) 2 2D crystals, synthesized from hydrothermal reaction. And an edge-on condensation mechanism assisted with the crystal field geometry is proposed to understand the 2D intra-planar growth of the crystals, which is also testified through series of systematic comparative studies. We also report the successful synthesis of 2D Co(OH) 2 crystals (> 40 μm) with more irregular shape due to the slightly distorted octahedral geometry of the crystal field. Moreover, the detailed structural characterization of synthesized α-Ni(OH) 2 are performed. The optical band gap energy is extrapolated as 2.54 eV from optical absorption measurements and the electronic bandgap is measured as 2.52 eV from reflected electrons energy loss spectroscopy (REELS). We further demonstrate its potential as a wide bandgap (WBG) semiconductor for high voltage operation in 2D electronics with a high breakdown strength, 4.77 MV/cm with 4.9 nm thickness. The successful realization of the 2D LTMHs opens the door for future exploration of more fundamental physical properties and device applications.

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

Probabilistic locked mode predictor in the presence of a resistive wall and finite island saturation in tokamaks

We present a framework for estimating the probability of locking to an error field in a rotating tokamak plasma. This leverages machine learning methods trained on data from a mode-locking model, including an error field, resistive magnetohydrodynamics modeling of the plasma, a resistive wall, and an external vacuum region, leading to a fifth-order ordinary differential equation (ODE) system. It is an extension of the model without a resistive wall introduced by Akçay et al. [Phys. Plasmas 28, 082106 (2021)]. Tearing mode saturation by a finite island width is also modeled. We vary three pairs of control parameters in our studies: the momentum source plus either the error field, the tearing stability index, or the island saturation term. The order parameters are the time-asymptotic values of the five ODE variables. Normalization of them reduces the system to 2D and facilitates the classification into locked (L) or unlocked (U) states, as illustrated by Akçay et al., [Phys. Plasmas 28, 082106 (2021)]. This classification splits the control space into three regions: L̂, with only L states; Û, with only U states; and a hysteresis (hysteretic) region Ĥ, with both L and U states. In regions L̂ and Û, the cubic equation of torque balance yields one real root. Region Ĥ has three roots, allowing bifurcations between the L and U states. The classification of the ODE solutions into L/U is used to estimate the locking probability, conditional on the pair of the control parameters, using a neural network. We also explore estimating the locking probability for a sparse dataset, using a transfer learning method based on a dense model dataset.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Rapidly evolving aerosol emissions are a dangerous omission from near-term climate risk assessments

Abstract Anthropogenic aerosol emissions are expected to change rapidly over the coming decades, driving strong, spatially complex trends in temperature, hydroclimate, and extreme events both near and far from emission sources. Under-resourced, highly populated regions often bear the brunt of aerosols’ climate and air quality effects, amplifying risk through heightened exposure and vulnerability. However, many policy-facing evaluations of near-term climate risk, including those in the latest Intergovernmental Panel on Climate Change assessment report, underrepresent aerosols’ complex and regionally diverse climate effects, reducing them to a globally averaged offset to greenhouse gas warming. We argue that this constitutes a major missing element in society’s ability to prepare for future climate change. We outline a pathway towards progress and call for greater interaction between the aerosol research, impact modeling, scenario development, and risk assessment communities.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Perturbation of tonoplast sucrose transport alters carbohydrate utilization for seasonal growth and defense metabolism in coppiced poplar

Abstract Nonstructural carbohydrate reserves of stems and roots underpin overall tree fitness and productivity under short-rotation management practices such as coppicing for bioenergy. While sucrose and starch comprise the predominant stem carbohydrate reserves of Populus, utilization for fitness and agricultural productivity is understood primarily in terms of starch turnover. The tonoplast sucrose transport protein SUT4 modulates sucrose export from source leaves to distant sinks during photoautotrophic growth, but the possibility of its involvement in remobilizing carbohydrates from storage organs during heterotrophic growth has not been explored. Here, we used PtaSUT4-knockout mutants of Populus tremula × P. alba (INRA 717-1B4) in winter (cool) and summer (warm) glasshouse coppicing experiments to assess SUT4 involvement in reserve utilization. Conditions preceding and supporting summer sprouting were considered favorable for growth, while those preceding and supporting cool temperature sprouting were suboptimal akin to conditions associated with coppicing as generally practiced. Epicormic bud emergence was delayed in sut4 mutants following lower temperature ‘winter’ but not summer coppicing. Winter xylem hexose increases were observed in control but not in sut4 stumps after coppicing. The magnitude of starch and sucrose reserve depletion was similar in control and sut4 stumps during the winter and did not explain the sprouting and xylem hexose differences. However, winter maintenance costs appeared higher in sut4 based partly on Krebs cycle intermediate levels. In control plants, bark accrual of abundant defense metabolites, including salicinoids and condensed tannins, was higher in summer than in winter, but this increase of summer defense allocations was attenuated in sut4 mutants. Temperature-sensitive trade-offs between growth and other priorities may therefore depend on SUT4 in Populus.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

BatAnalysis - A Comprehensive Python Pipeline for Swift BAT Survey Analysis

The Swift Burst Alert Telescope (BAT) is a coded-aperture gamma-ray instrument with a large field of view that primarily operates in survey mode when it is not triggering on transient events. The survey data consist of 80- channel detector plane histograms that accumulate photon counts over periods of at least 5 minutes. These histograms are processed on the ground and are used to produce the survey data set between 14 and 195 keV. Survey data comprise >90% of all BAT data by volume and allow for the tracking of long-term light curves and spectral properties of cataloged and uncataloged hard X-ray sources. Until now, the survey data set has not been used to its full potential due to the complexity associated with its analysis and the lack of easily usable pipelines. Here, we introduce the BatAnalysis Python package, a wrapper for HEASoftpy, which provides a modern, opensource pipeline to process and analyze BAT survey data. BatAnalysis allows members of the community to use BAT survey data in more advanced analyses of astrophysical sources, including pulsars, pulsar wind nebula, active galactic nuclei, and other known/unknown transient events that may be detected in the hard X-ray band. We outline the steps taken by the Python code and exemplify its usefulness and accuracy by analyzing survey data of the Crab Nebula, NGC 2992, and a previously uncataloged MAXI transient. The BatAnalysis package allows for ~18 yr of BAT survey data to be used in a systematic way to study a large variety of astrophysical sources.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Long-Term Stability Metrics of Photoelectrochemical Water Splitting

Photoelectrochemical (PEC) water splitting, one of the most promising technologies for clean hydrogen generation, has drawn considerable attention over the past few decades. Achieving simultaneous highly efficient and stable unassisted PEC water splitting has been the “holy grail” in clean and renewable fuel generation. State-of-the-art photoelectrodes have shown relatively high efficiencies (∼10–20%). Still, their stability is limited due to photoelectrode chemical instability, electrolyte resistance, mass transfer issues, and an often unoptimized experimental setup. In this work, we present a framework and a set of protocols for conducting long-term stability experiments and further provide details on several critical factors such as light source calibration, choosing the right counter electrode, the configuration of the PEC cell, and photoelectrode sample preparation.

08 HYDROGEN↗
DOE OSTI2024

The Role of Lignin Molecular Weight on Activated Carbon Pore Structure

Over the past decade, the production of biofuels from lignocellulosic biomass has steadily increased to offset the use of fuels from petroleum. To make biofuels cost-competitive, however, it is necessary to add value to the “ligno-” components (up to 30% by mass) of the biomass. The properties of lignin, in terms of molecular weight (MW), chemical functionality, and mineral impurities often vary from biomass source and biorefinery process, resulting in a challenging precursor for product development. Activated carbon (AC) is a feasible target for the lignin-rich byproduct streams because it can be made from nearly any biomass, and it has a market capacity large enough to use much of the lignin generated from the biorefineries. However, it is not known how the variability in the lignin affects the key properties of AC, because, until now, they could not be well controlled. In this work, various fractions of ultraclean (<0.6% ash) lignin are created with refined MW distributions using Aqueous Lignin Purification using Hot Agents (ALPHA) and used as precursors for AC. AC is synthesized via zinc chloride activation and characterized for pore structure and adsorption capacity. We show that AC surface area and the adsorption capacity increase when using lignin with increasing MW, and, furthermore, that reducing the mineral content of lignin can significantly enhance the AC properties. The surface area of the AC from the highest MW lignin can reach ~1830 m2/g (absorption capacity). Furthermore, single step activation carbonization using zinc chloride allows for minimal carbon burn off (<30%), capturing most of the lignin carbon compared to traditional burn off methods in biorefineries for heat generation.

Biochemistry & Molecular Biology↗
DOE OSTI2023

BatAnalysis - A Comprehensive Python Pipeline for Swift BAT Survey Analysis

The Swift Burst Alert Telescope (BAT) is a coded-aperture gamma-ray instrument with a large field of view that primarily operates in survey mode when it is not triggering on transient events. The survey data consist of 80-channel detector plane histograms that accumulate photon counts over periods of at least 5 minutes. These histograms are processed on the ground and are used to produce the survey data set between 14 and 195 keV. Survey data comprise >90% of all BAT data by volume and allow for the tracking of long-term light curves and spectral properties of cataloged and uncataloged hard X-ray sources. Until now, the survey data set has not been used to its full potential due to the complexity associated with its analysis and the lack of easily usable pipelines. Here, we introduce the BatAnalysis Python package, a wrapper for HEASoftpy, which provides a modern, open-source pipeline to process and analyze BAT survey data. BatAnalysis allows members of the community to use BAT survey data in more advanced analyses of astrophysical sources, including pulsars, pulsar wind nebula, active galactic nuclei, and other known/unknown transient events that may be detected in the hard X-ray band. We outline the steps taken by the Python code and exemplify its usefulness and accuracy by analyzing survey data of the Crab Nebula, NGC 2992, and a previously uncataloged MAXI transient. The BatAnalysis package allows for ~18 yr of BAT survey data to be used in a systematic way to study a large variety of astrophysical sources.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Photosynthesis and rhizome carbohydrate concentrations of switchgrass grown from reserve-depleted rhizomes

A long-standing question in perennial grass breeding and physiology is whether yield improvement strategies could compromise winter survival. Perennial grasses rely on the pool of carbohydrates accumulated in storage organs from the previous growing season for winter maintenance and spring regrowth. Yield improvement strategies could reduce winter survival if they increase biomass and grain yields at the expense of carbon allocation to storage. Therefore, it is crucial to better understand the dependence of regrowth on storage reserves. We experimentally depleted switchgrass ( Panicum virgatum L.) rhizome reserves by storing rhizomes for two weeks at 5 °C (control treatment) and 25 °C (reserve-depleted treatment).

bioenergy↗
DOE OSTI2026

Over 8 hours of continuous operation of a free-electron laser driven by a laser-plasma accelerator

Since the emergence of laser-plasma accelerators (LPAs), substantial work has been dedicated to using LPAs to drive free-electron lasers (FELs) for a broad range of applications. Despite recent breakthroughs, which have proven the fundamental feasibility of operating FELs with an LPA source, stable FEL operation over multiple hours without operator input had yet to be achieved. In this work, we report significant improvements to the stability of a hundred terawatt laser system, resulting in successful demonstration of reliable, long-term operation of an LPA-driven FEL in the self-amplified spontaneous emission (SASE) regime at 420 nm. The LPA source delivered 100 MeV electron beams at 1 Hz with high stability over more than 10 h, enabling over 8 h of continuous FEL operation without operator input. The acquired data were subsequently used to investigate correlations between the measured undulator radiation and parameters of the drive laser, plasma source, and electron beam. The revealed connections between LPA and FEL performance gave important additional insights into ways to further improve and stabilize the system, thus demonstrating the capability of our setup to serve as a powerful platform for future studies of LPA-driven FEL operation. The one-of-a-kind integration of multiple stabilization concepts onto the LPA facility discussed in this manuscript yielded significant accelerator and light source improvements (with residual correlations suggesting even more is possible), which will positively impact LPA applications at large.

Kohrell, Finn [Lawrence Berkeley National Laborato↗
DOE OSTI2022

Velocity dispersion and dynamical masses for 388 galaxy clusters and groups

The second catalogue of Planck Sunyaev-Zeldovich (SZ) sources, hereafter PSZ2, represents the largest galaxy cluster sample selected by means of their SZ signature in a full-sky survey. For this work, using telescopes at the Canary Island observatories, we conducted the long-term observational program 128- MULTIPLE-16/15B (hereafter LP15), a large and complete optical follow-up campaign of all the unidentified PSZ2 sources in the northern sky, with declinations above –15° and no correspondence in the first Planck catalogue PSZ1. This paper is the third and last in the series of LP15 results, after Streblyanska et al. (2019, A&A, 628, A13) and Aguado-Barahona et al. (2019, A&A, 631, A148), and presents all the spectroscopic observations of the full program. We complement these LP15 spectroscopic results with Sloan Digital Sky Survey archival data and other observations from a previous program (ITP13-08), and present a catalogue of 388 clusters and groups of galaxies including estimates of their velocity dispersion. The majority of them (356) are optical counterparts of PSZ2 sources. A subset of 297 of those clusters are used to construct the M SZ – M dyn scaling relation based on the estimated SZ mass from Planck measurements and our dynamical mass estimates. We discuss and correct for different statistical and physical biases in the estimation of the masses, such as the Eddington bias when estimating M SZ and the aperture and the number of galaxies used to calculate M dyn . The SZ-to-dynamical mass ratio for those 297 PSZ2 clusters is (1 – B) = 0.80 ± 0.04 (stat) ± 0.05 (sys), with only marginal evidence for a possible mass dependence for this factor. Our value is consistent with previous results in the literature, but is associated with a significantly smaller uncertainty due to the use of the largest sample size for this type of study.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Combined Techno-Economic Analysis and Life Cycle Assessment of an Integrated Direct Air Capture System with Advanced Algal Biofuel Production

The continuous increase in carbon dioxide (CO2) concentration in the atmosphere since the First Industrial Revolution correlates convincingly with the ongoing rise of the Earth's global average temperature contributing to climate change. As a response, carbon capture and sequestration (CCS) technologies are being implemented to mitigate anthropogenic CO2 emissions by capturing CO2 from high emitting point sources, such as power plants, refineries, and cement factories, and subsequently buried in geological formations underground for long term storage. Recently direct air capture (DAC) has emerged as a promising alternative technology that captures CO2 directly from the atmosphere for use or sequestration. This study investigates the potential synergistic benefits of integrating a solid amine-based DAC system with advanced algal biofuel production in photobioreactors (PBRs). DAC utilization allows the removal of atmospheric CO2 while also decoupling algae production facilities from anthropogenic point CO2 sources and avoiding the cost and logistics challenges of transporting CO2 long distances to remote facilities. Techno-economic analysis and life cycle assessment are performed to assess the economic and environmental benefits of heat and mass integration between the DAC and the PBR for biofuel production. The DAC-PBR system integration also considers on-site flue gas handling options, DAC capital utilization, the tradeoff between centralization or decentralization of key unit operations, and the PBR array. This presentation will discuss how optimizing DAC-PBR process integration can enhance the algal biofuel's economic and environmental sustainability and the prospect of DAC enabling the circular carbon economy.

algal biofuel production↗