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At least 235 records · Page 13

RB-TnSeq identifies genetic targets for improved tolerance of Pseudomonas putida towards compounds relevant to lignin conversion

We report lignin-derived mixtures intended for bioconversion commonly contain high concentrations of aromatic acids, aliphatic acids, and salts. The inherent toxicity of these chemicals places a significant bottleneck upon the effective use of microbial systems for the valorization of these mixtures. Pseudomonas putida KT2440 can tolerate stressful quantities of several lignin-related compounds, making this bacterium a promising host for converting these chemicals to valuable bioproducts. Nonetheless, further increasing P. putida tolerance to chemicals in lignin-rich substrates has the potential to improve bioprocess performance. Accordingly, we employed random barcoded transposon insertion sequencing (RB-TnSeq) to reveal genetic determinants in P. putida KT2440 that influence stress outcomes during exposure to representative constituents found in lignin-rich process streams. The fitness information obtained from the RB-TnSeq experiments informed engineering of strains via deletion or constitutive expression of several genes. Namely, ΔgacAS, ΔfleQ, ΔlapAB, ΔttgR::P tac :ttgABC, Ptac:PP_1150:PP_1152, ..delta..relA, and ΔPP_1430 mutants showed growth improvement in the presence of single compounds, and some also exhibited greater tolerance when grown using a complex chemical mixture representative of a lignin-rich chemical stream. Overall, this work demonstrates the successful implementation of a genome-scale screening tool for the identification of genes influencing stress tolerance against notable compounds within lignin-enriched chemical streams, and the genetic targets identified herein offer promising engineering targets for improving feedstock tolerance in lignin valorization strains of P. putida KT2440.

09 BIOMASS FUELS↗

Molecular Origin of Wettability Alteration of Subsurface Porous Media upon Gas Pressure Variations

Upon extraction/injection of a large quantity of gas from/into a subsurface system in shale gas production or carbon sequestration, the gas pressure varies remarkably, which may significantly change the wettability of porous media involved. Mechanistic understanding of such changes is critical for designing and optimizing a related subsurface engineering process. Using molecular dynamics simulations, in this work we have calculated the contact angle of a water droplet on various solid surfaces (kerogen, pyrophyllite, calcite, gibbsite, and montmorillonite) as a function of CO 2 or CH 4 gas pressure up to 200 atm at a temperature of 300 K. The calculation reveals a complex behavior of surface wettability alteration by gas pressure variation depending on surface chemistry and structure, and molecular interactions of fluid molecules with surfaces. As the CO 2 gas pressure increases, a partially hydrophilic kerogen surface becomes highly hydrophobic, while a calcite surface becomes more hydrophilic. Considering kerogen and calcite being the major components of a shale formation, we postulate that the wettability alteration of a solid surface induced by a gas pressure change may play an important role in fluid flows in shale gas production and geological carbon sequestration.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Direct Transformation of SiH 4 to a Molecular L(H) 2 Co=Si=Co(H) 2 L Silicide Complex

The synthesis of bimetallic molecular silicide complexes is reported, based on the use of multiple Si–H bond activations in SiH 4 at the metal centers of 14-electron LCo I fragments (L = Tp", HB(3,5-diisopropylpyrazolyl) 3 – ; [BP 2 tBu Pz], PhB(CH 2 P t Bu 2 ) 2 (pyrazolyl)). Upon exposure of (Tp"Co) 2 (μ-N 2 ) (1) to SiH 4 , a mixture of (Tp"Co) 2 (μ-H) (2) and (Tp"Co) 2 (μ-H) 2 (3) was formed and no evidence for Si–H oxidative addition products was observed. In contrast, [BP 2 tBu Pz]-supported Co complexes led to Si–H oxidative additions with the generation of silylene and silicide complexes as products. Notably, the reaction of ([BP 2 tBu Pz]Co) 2 (μ-N 2 ) (5) with SiH 4 gave the dicobalt silicide complex [BP 2 tBu Pz](H) 2 Co=Si=Co(H) 2 [BP 2 tBu Pz] (8) in high yield, representing the first direct route to a symmetrical bimetallic silicide. Here, the effect of the [BP 2 tBu Pz] ligand on Co–Si bonding in 7 and 8 was explored by analysis of solid-state molecular structures and density functional theory (DFT) investigations. Upon exposure to CO or DMAP (DMAP = 4-dimethylaminopyridine), 8 converted to the corresponding [BP 2 tBu Pz]Co(L) x adducts (L = CO, x = 2; L = DMAP, x = 1) with concomitant loss of SiH 4 , despite the lack of significant Si–H interactions in the starting complex. On heating to 60 °C, 8 underwent reaction with MeCl to produce small quantities of Me x SiH 4–x (x = 1–3), demonstrating functionalization of the μ-silicon atom in a molecular silicide to form organosilanes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Probing cosmic velocities with the pairwise kinematic Sunyaev-Zel’dovich signal in DESI Bright Galaxy Sample DR1 and ACT DR6

We present a measurement of the pairwise kinematic Sunyaev-Zel’dovich (kSZ) signal using the Dark Energy Spectroscopic Instrument (DESI) Bright Galaxy Sample (BGS) Data Release 1 (DR1) galaxy sample overlapping with the Atacama Cosmology Telescope (ACT) CMB temperature map. Our analysis makes use of 1.6 million galaxies with stellar masses log⁡ 𝑀 ⋆ /𝑀 ⊙ >10, and we explore measurements across a range of aperture sizes (2.1′ <𝜃 ap <3.5′) and stellar mass selections. This statistic directly probes the velocity field of the large-scale structure, a unique observable of cosmic dynamics and modified gravity. In particular, at low redshifts, this quantity is especially interesting, as deviations from General Relativity are expected to be largest. Notably, our result represents the highest-significance low-redshift (𝑧 ∼ 0.3) detection of the kSZ pairwise effect yet. In our most optimal configuration (𝜃 ap =3.3′, log⁡ 𝑀 ⋆ >11), we achieve a 5⁢𝜎 detection. Assuming that an estimate of the optical depth and galaxy bias of the sample exists via e.g., external observables, this measurement constrains the fundamental cosmological combination 𝐻 0 ⁡𝑓⁡𝜎$^2_8$. A key challenge is the degeneracy with the galaxy optical depth. We address this by combining CMB lensing, which allows us to infer the halo mass and galaxy population properties, with hydrodynamical simulation estimates of the mean optical depth, $\bar{𝜏}$ . We stress that this is a proof-of-concept analysis; with BGS DR2 data we expect to improve the statistical precision by roughly a factor of two, paving the way toward robust tests of modified gravity with kSZ-informed velocity-field measurements at low redshift.

Hadzhiyska, Boryana [Institute of Astronomy; Kavli↗

CB10412: Bulk CWA Destruction

The objective of this project was to eliminate and/or render bulk agent unusable by a threat entity via neutralization and/or polymerization of the bulk agent using minimal quantities of additives. We proposed the in situ neutralization and polymerization of bulk chemical agents (CAs) by performing reactions in the existing CA storage container via wet chemical approaches using minimal quantities of chemical based materials. This approach does not require sophisticated equipment, fuel to power generators, electricity to power equipment, or large quantities of decontaminating materials. By utilizing the CA storage container as the batch reactor, the amount of logistical resources can be significantly reduced. Fewer personnel are required since no sophisticated equipment needs to be set up, configured, or operated. Employing the CA storage container as the batch reactor enables the capability to add materials to multiple containers in a short period of time as opposed to processing one container at a time for typical batch reactor approaches. In scenarios where a quick response is required, the material can be added to all the CA containers and left to react on its own without intervention. Any attempt to filter the CA plus material solution will increase the rate of reaction due to increased agitation of the solution.

36 MATERIALS SCIENCE↗

Preprocessing of municipal solid waste towards thermal insulating material

Municipal solid waste (MSW) is one of the significant challenges in today’s world. A continuous surge in population, increasing living standards, and rapid urbanization are generating an enormous quantity of MSW. For example, the Environmental Protection Agency (EPA) reported that the total generation of MSW in the United States in 2018 was 292.4 million tons. Improper management of this MSW often leads to the release of greenhouse gases, emission of particulate matters, and formation of dioxins, which all ultimately contributes to climate change. Recycling these wastes via landfills with gas recovery and/or energy and material production via thermal and chemical conversions could be viable options to manage these challenges. Depending on the inherent chemical and structural properties of unrecycled wastes, the carbon structures can be tailored for processing and reuse in manufacturing of structural composites, building materials such as insulation, carbon dense reactant materials such as activated carbon, and so on. According to the EPA’s estimation, MSW in the United States is approximately 23% paper and paperboard, 12% plastics, 6% wood and 6% is textiles. Thus, this research focused on the feasibility of using the MSW as insulation material for the construction sector. The goal of this work was to determine the range of particle sizes, consolidation ratios, and component blends that can achieve insulation R-values within at least 70% that of traditional blown cellulose fiber. To achieve this goal, we designed the testing matrix based on five different component blends, three different particle sizes, and three different compaction level. An American Society for Testing and Materials (ASTM) method (C-739) was used to measure the R-value of the insulation material. Results showed that, adding more paper component in addition to smaller particle size and loose compaction made the insulation similar to the traditional blown cellulose fiber insulation as the R-value was within a range of 2.5-3.0 per inch.

42 ENGINEERING↗

Evaluation of DNA Extraction Efficiency in Diverse Algae Strains Using Commercial Kits and Lysis Approaches

Efficient DNA extraction is essential for accurately monitoring microalgae communities in large-scale cultivation systems such as raceway ponds and wastewater ponds. Traditional phenol chloroform extracts are a staple in microbiology but are obsolete for routine sampling due to its high toxicity reagents and time intensive setups. Commercial DNA extraction kits are more favorable for the microbes found in these ponds, but lack specific kits made for these communities. Little is known about which kits perform the best, leading researchers to use a variety of different kits with inconsistent results. This project compared one precipitation based commercial kit (Lucigen Masterpure) and five wash based kits (Monarch, Zymo Quick-DNA, and three Qiagen DNeasy kits) using four brackish algae strains to determine which methods yield the greatest quantity and quality of genomic DNA. Extractions were evaluated using the manufacturers protocol, and additional pretreatment options were administered before a single kit to compare its potential in being added routinely before extractions. Pretreatment options included both cryogenic freeze-thawing and heat incubation using enzymes. DNA was quantified using Qubit fluorometry and NanoDrop purity ratios. Overall, the Qiagen PowerWater kit provided the highest DNA yield and purity, but at a significantly higher cost then the precipitation-based kit (MasterPure). It was also noted that while the precipitation-based kit was significantly cheaper, provided similar results, it took significantly more time to complete a single run. Cryogenic pretreatment (6x cycles) increased average DNA yields by up to 80%, whereas enzymatic pretreatment most improved purity ratios without substantially improving quantity. The results suggest that it may be more cost and time efficient to use Qiagen kits with the addition of lysis pretreatments to procure better results. Future works includes developing a better system to efficiently collect multi variable data, and to upscale to artificial polycultures using similar methodologies alongside sequencing to confirm kit results.

59 BASIC BIOLOGICAL SCIENCES↗

Implicit learning of convective organization explains precipitation stochasticity

Accurate prediction of precipitation intensity is crucial for both human and natural systems, especially in a warming climate more prone to extreme precipitation. Yet, climate models fail to accurately predict precipitation intensity, particularly extremes. One missing piece of information in traditional climate model parameterizations is subgrid-scale cloud structure and organization, which affects precipitation intensity and stochasticity at coarse resolution. Here, using global storm-resolving simulations and machine learning, we show that, by implicitly learning subgrid organization, we can accurately predict precipitation variability and stochasticity with a low-dimensional set of latent variables. Using a neural network to parameterize coarse-grained precipitation, we find that the overall behavior of precipitation is reasonably predictable using large-scale quantities only; however, the neural network cannot predict the variability of precipitation (R 2 ~ 0.45) and underestimates precipitation extremes. The performance is significantly improved when the network is informed by our organization metric, correctly predicting precipitation extremes and spatial variability (R 2 ~ 0.9). The organization metric is implicitly learned by training the algorithm on a high-resolution precipitable water field, encoding the degree of subgrid organization. The organization metric shows large hysteresis, emphasizing the role of memory created by subgrid-scale structures. We demonstrate that this organization metric can be predicted as a simple memory process from information available at the previous time steps. These findings stress the role of organization and memory in accurate prediction of precipitation intensity and extremes and the necessity of parameterizing subgrid-scale convective organization in climate models to better project future changes of water cycle and extremes.

54 ENVIRONMENTAL SCIENCES↗

Energy efficiency and renewable energy utilization in desalination systems

Desalination technologies and industry have advanced significantly in the past two decades to meet the growing freshwater demands stimulated by the compounding issues of both water quality and quantity in many regions of the world. As desalination processes are energy demanding, there have been many efforts dedicated to improve energy-efficiency of the process units, enhance energy conservation and recovery, and increase renewable energy integration in desalination plants. This review article highlights recent key advances and discusses possible venues for further development in desalination energy portfolio to reduce specific energy consumption and, via integration with solar energy, to minimize the environmental footprint associated with freshwater production. First, an overview of current desalination technologies and their energy requirements are presented followed by a discussion on opportunities for improving energy efficiency and energy recovery in both membrane and thermal desalination technologies. Then, various combinations of renewable energy driven desalination plants are discussed with some recent highlights in solar energy driven membrane, thermal and hybrid desalination processes. Technological readiness levels for novel desalination processes, their perceived impact and expected near-future developments in renewable energy integrated desalination technologies are presented. Lastly, the potential for solar driven desalination as a cost-competitive freshwater supply alternative is discussed

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

State of Innovation 2024: Paving the Way for Low-Carbon Cement and Concrete

Concrete production in the U.S. accounted for nearly 393 million cubic yards in 2023, with $38.8 billion in revenue. While cement, the key ingredient in concrete, is only 10%-15% of concrete's mixture by mass, 8% of total global emissions come from the production of cement. A significant challenge lies in the fact that roughly 51% of concrete emissions stem from the material calcination process of cement production. Stakeholders ranging from cement producers to government agencies are beginning to take measures to significantly reduce concrete emissions by 2050 and are seeking novel technologies from the startup community. Strategies to lower carbon emissions include reducing quantities of cement in concrete formulas; optimizing digital and automated production; lower temperature processing; carbon capture, utilization, and durable storage; and other cost-saving approaches to energy and material efficiencies. New materials based on carbon mineralization and novel cement chemistries hold the potential to reach net-zero or even carbon-negative concrete production; however, there is presently no readily available substitute that can replicate concrete's unique properties and versatility at the volume demanded by construction worldwide. The nature of concrete's raw materials, diverse applications, and scale of demand means that complete decarbonization will rely on a combination of innovative production methods and novel cement chemistries. Low-carbon solutions will need to compete economically with traditional concrete to become viable in a high-volume commodity market, although consumer demand and regulation will play important roles. Despite these challenges, this analysis reveals that venture capital (VC) investments in low-carbon concrete reflect a growing awareness of the decarbonized cement market opportunity. Between 2022 and 2023 emerging low-carbon technologies garnered more than $700 million in VC investments, representing a growing share of investment in the built environment. An investment gap appears after Series A for technology solutions, demonstrating the sector's potential, as well as the need for additional performance assurance and technology incubation.

cement↗

Control optimization for parametric Hamiltonians by pulse reconstruction

Optimal control techniques provide a means to tailor the control pulses required to generate customized quantum gates, which helps to improve the resilience of quantum simulations to gate errors and device noise. However, the significant amount of (classical) computation required to generate customized gates can quickly undermine the effectiveness of this approach, especially when pulse optimization needs to be iterated. We propose a method to reduce the computational time required to generate the control pulse for a Hamiltonian that is parametrically dependent on a time-varying quantity. We use simple interpolation schemes to accurately reconstruct the control pulses from a set of pulses obtained in advance for a discrete set of predetermined parameter values. We obtain a reconstruction with very high fidelity and a significant reduction in computational effort. We report the results of the application of the proposed method to device-level quantum simulations of the unitary (real) time evolution of two interacting neutrons based on superconducting qubits.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Advances in physics and applications of 3D magnetic perturbations on the J-TEXT tokamak

In the last two years, three major technical improvements have been made on J-TEXT in supporting of the expanded operation regions and diagnostic capabilities. (1) The successful commission of the 105 GHz/500 kW/1 s electron cyclotron resonance heating (ECRH) system increasing the core electron temperature from 0.9 keV up to around 1.5 keV. (2) The poloidal divertor configuration with an X-point in the high-field side has been achieved. In particular, the 400 kW electron cyclotron wave has also been successfully injected into the diverted plasma. (3) A 256-channel electron cyclotron emission imaging diagnostic system and two sets of four-channel Doppler backscattering diagnostics have been successfully developed on J-TEXT, allowing detailed measurement of the electron temperature and density fluctuations for turbulence and MHD research. The locked mode (LM), especially the 2/1 LM, is one of the biggest threats to the plasma operation. Both the thresholds of 2/1 and 3/1 LM are observed to vary non-monotonically on electron density. The electrode biasing was applied successfully to unlock the LM from either a rotating or static resonant magnetic perturbation (RMP) field. In the presence of 2/1 LM, three kinds of standing wave (SW) structures have been observed to share a similar connection to the island structure, i.e. the nodes of the SWs locate around the O- or X-points of the 2/1 island. The control and mitigation of disruption is essential to the safe operation of ITER, and it has been systematically studied by applying a RMP field, massive gas injection (MGI) and shattered pellet injection on J-TEXT. When the RMP-induced 2/1 LM is larger than a critical width, the MGI shutdown process can be significantly influenced. If the phase difference between the O-point of LM and the MGI valve is +90° (or –90°), the penetration depth and the assimilation of impurities can be enhanced (or suppressed) during the pre-thermal quench (TQ) phase and result in a faster (or slower) TQ. A secondary MGI can also suppress the runaway electron (RE) generation, if the additional high-Z impurity gas arrives at the plasma edge before TQ. When the secondary MGI has been applied after the formation of the RE current plateau, the RE current can be dissipated, and the dissipation rate increases with the injected impurity quantity but saturates with a maximum of 28 MA s –1 . The non-local transport is experimentally observed in the ion transport channel. The electron thermal diffusivity significantly increases with the ECRH power. Theoretical work shows that significant intrinsic current can be driven by electromagnetic turbulence, and the robust formation mechanism of the E × B staircase is identified from the Hasegawa–Wakatani system.

divertor↗

Multilevel and multifidelity uncertainty quantification for cardiovascular hemodynamics

Standard approaches for uncertainty quantification in cardiovascular modeling pose challenges due to the large number of uncertain inputs and the significant computational cost of realistic three-dimensional simulations. Here, we propose an efficient uncertainty quantification framework utilizing a multilevel multifidelity Monte Carlo (MLMF) estimator to improve the accuracy of hemodynamic quantities of interest while maintaining reasonable computational cost. This is achieved by leveraging three cardiovascular model fidelities, each with varying spatial resolution to rigorously quantify the variability in hemodynamic outputs. We employ two low-fidelity models (zero- and one-dimensional) to construct several different estimators. Our goal is to investigate and compare the efficiency of estimators built from combinations of these two low-fidelity model alternatives and our high-fidelity three-dimensional models. We demonstrate this framework on healthy and diseased models of aortic and coronary anatomy, including uncertainties in material property and boundary condition parameters. Our goal is to demonstrate that for this application it is possible to accelerate the convergence of the estimators by utilizing a MLMF paradigm. Therefore, we compare our approach to single fidelity Monte Carlo estimators and to a multilevel Monte Carlo approach based only on three-dimensional simulations, but leveraging multiple spatial resolutions. We demonstrate significant, on the order of 10 to 100 times, reduction in total computational cost with the MLMF estimators. We also examine the differing properties of the MLMF estimators in healthy versus diseased models, as well as global versus local quantities of interest. As expected, global quantities such as outlet pressure and flow show larger reductions than local quantities, such as those relating to wall shear stress, as the latter rely more heavily on the highest fidelity model evaluations. Similarly, healthy models show larger reductions than diseased models. In all cases, our workflow coupling Dakota’s MLMF estimators with the SimVascular cardiovascular modeling framework makes uncertainty quantification feasible for constrained computational budgets.

59 BASIC BIOLOGICAL SCIENCES↗

An investigation of the multi-mode Richtmyer-Meshkov instability at a gas/HE interface using Pagosa

Here, in this work, we present a hydrocode Pagosa and explore the Richtmyer-Meshkov Instability (RMI) at an air/high explosive (HE) interface for the first time that is important but has not received much attention yet in the high explosive safety field. Thus, the presented Pagosa can be expected to predict the whole deflagration-to-detonation transition (DDT) process in future. In Pagosa, spatial discretization is implemented on cubic staggered grids by computing different variables at the vertex and the cell center, respectively, a special operator-splitting technique is employed to reduce the computational cost, and an artificial viscosity is added to handle the discontinuous shock waves in our simulations. To quantitatively evaluate the capability of Pagosa to solve these kinds of instabilities, the single mode Rayleigh-Taylor instability (RTI) and the multimode RMI at an air/SF 6 interface are first performed, respectively. The Pagosa results are compared with the related numerical solutions in the existing references and the experimental result. Moreover, a theoretical derivation of growth of RTI is also provided based on our numerical method. Subsequently, we explore the multi-mode RMI at an air/HE interface as well as the effects of several factors using Pagosa. Numerical results show that Pagosa is a powerful toolset to generate the right structures and the amplitude of RTI and RMI at an air/SF 6 interface. The solid HE can be penetrated by a strong shock wave and forms RMI deformations. The RMI at an air/HE interface behaves very different than at an air/SF 6 interface, periodic, decreased oscillation is observed due to material character, and is very sensitive to the initial simulation settings, that is, a tiny change in physical quantities will lead to a remarkable RMI structure, which is also observed in a shock bubble interaction. The findings in this work are significant, and will present a new insight for the high explosive field.

97 MATHEMATICS AND COMPUTING↗

Towards advanced polarized electron sources

Polarized electrons play an important role in high-energy and nuclear physics, and their properties have also been exploited in ultrafast electron microscopy. Currently, gallium arsenide crystals illuminated by circular polarized infrared laser light are commonly used for generating polarized electrons. However, the achievable accelerating voltage and the gradient of these electrostatic sources limit the beam quality and quantity. A solution could be to combine gallium arsenide photocathodes with radio-frequency electron guns, which are capable of accelerating beams with significantly higher gradients and voltage. Here we report the successful operation of a gallium arsenide photocathode in a superconducting radio-frequency gun. Our findings are relevant for future sources of polarized electrons.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Reconstitution of Sandia's Melt Laboratory: A Strategic Approach to Address Alloy Procurement and Quality Challenges - Part 1

In recent years, the procurement of essential materials such as Stainless Steels, Ni-Alloys, and Kovar has become increasingly challenging. Lead times for these materials have extended to over 24 months, placing significant stress on the reliability of attaining these alloys. This situation is exacerbated by the supplier’s minimum purchase requirement of excessively large quantities to meet unique purchase order (PO) requirements which is usually above the maximum requirements of Sandia National Laboratories (SNL). Additionally, the reluctance of foundries to engage in small lot development for SNL specific needs further complicates the procurement process. This white paper explores the reconstitution of SNL’ Melt Laboratory as a strategic solution to mitigate these challenges.

36 MATERIALS SCIENCE↗

Hybrid HEFA-HDCJ Process for the Production of Jet Fuel Blendstocks

The hydrotreatment of bio-oil derived from the pyrolysis and biocrude from hydrothermal liquefaction of lignocellulosic materials to produce hydrocarbons faces significant technological challenges, mainly due to the high reactivity and poor thermal stability of bio-oil, resulting in the formation of large quantities of coke. This problem has been addressed by existing PNNL patents with a two-step hydrotreatment technology in which the bio-oil is first stabilized with a noble hydrogenation metal (often Pt or Ru). Then, in the second step, the bio-oil is deoxygenated with a Ni-Mo or Co-Mo sulfide catalyst. The main problem with this approach is that the Pt/Ru catalysts deactivate easily in the presence of S or other impurities, which are commonly present in pyrolysis oils. In this project, we explored technological solutions to mitigate coke formation, avoiding the use of Pt/Ru catalysts. Our strategy is based on three actions: (1) Bio-oil stabilization in the presence of alcohols. In this project, we studied the stabilization with butanol. (2) the use of a cosolvent to solubilize the bio-oil. Because coke formation reactions are second-order reactions a reduction in the concentration of reactive bio-oil molecules. In this case, we used yellow greases as a co-solvent. (3) Separation of bio-oil reactive fractions. In this project, we studied the removal of water-soluble fractions. Our batch co-hydrotreatment studies confirmed that the addition of butanol and methanol and the blend with lipids effectively contributed to mitigating coke formation (reducing coke yield to about 1 wt.% %). The removal of sugars did not have a noticeable effect on the overall coke yield, suggesting that coke precursors are present in all bio-oil fractions.

09 BIOMASS FUELS↗

Recovering the Star Formation Histories of Recently Quenched Galaxies: The Impact of Model and Prior Choices

Accurate models of the star formation histories (SFHs) of recently quenched galaxies can provide constraints on when and how galaxies shut down their star formation. The recent development of nonparametric SFH models promises the flexibility required to make these measurements. However, model and prior choices significantly affect derived SFHs, particularly for post-starburst galaxies (PSBs), which have sharp changes in their recent SFH. In this paper, we create mock PSBs, then use the Prospector SED fitting software to test how well four different SFH models recover key properties. We find that a two-component parametric model performs well for our simple mock galaxies, but is sensitive to model mismatches. The fixed- and flexible-bin nonparametric models included in Prospector are able to rapidly quench a major burst of star formation, but systematically underestimate the post-burst age by up to 200 Myr. We develop a custom SFH model that allows for additional flexibility in the recent SFH. Our flexible nonparametric model is able to constrain post-burst ages with no significant offset and just ~90 Myr of scatter. Our results suggest that while standard nonparametric models are able to recover first-order quantities of the SFH (mass, SFR, average age), accurately recovering higher-order quantities (burst fraction, quenching time) requires careful consideration of model flexibility. These mock recovery tests are a critical part of future SFH studies. Finally, we show that our new, public SFH model is able to accurately recover the properties of mock star-forming and quiescent galaxies and is suitable for broader use in the SED fitting community. https://github.com/bd-j/prospector

79 ASTRONOMY AND ASTROPHYSICS↗