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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Treatment of brackish water for fossil power plant cooling

In this study, we evaluated the technical, economic and environmental impacts of retrofitting brackish groundwater treatment systems at existing coal- and gas-fired electric generating units (EGUs) to reduce freshwater consumption in wet cooling towers. Based on fleet averages, retrofitting brackish water treatment systems decreases unit freshwater consumption by 94–100%, while increasing the cost of electricity generation by 8–10%. The unit capacity shortfalls are less than 1.1%. The resulting cost of freshwater consumption savings by brackish water treatment is US$1.7 m -3 and US$2.9 m -3 on average for coal- and gas-fired EGUs, respectively. However, these trade-offs are highly affected by the brine disposal method. The use of thermal zero liquid discharge for brine disposal can roughly double the average cost of freshwater consumption savings. The cost-effectiveness of brackish water treatment compared with dry cooling deployment depends on how concentrated brines are managed. In conclusion, the identified trade-offs and their dependence fill knowledge gaps to better inform water management.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2020

Combining Three-Dimensional Modeling with Artificial Intelligence to Increase Specificity and Precision in Peptide–MHC Binding Predictions

The reliable prediction of the affinity of candidate peptides for the MHC is important for predicting their potential antigenicity and thus influences medical applications, such as decisions on their inclusion in T cell–based vaccines. In this study, we present a rapid, predictive computational approach that combines a popular, sequence-based artificial neural network method, NetMHCpan 4.0, with three-dimensional structural modeling. We find that the ensembles of bound peptide conformations generated by the programs MODELLER and Rosetta FlexPepDock are less variable in geometry for strong binders than for low-affinity peptides. In tests on 1271 peptide sequences for which the experimental dissociation constants of binding to the well-characterized murine MHC allele H-2D b are known, by applying thresholds for geometric fluctuations the structure-based approach in a standalone manner drastically improves the statistical specificity, reducing the number of false positives. Furthermore, filtering candidates generated with NetMHCpan 4.0 with the structure-based predictor led to an increase in the positive predictive value (PPV) of the peptides correctly predicted to bind very strongly (i.e., Kd < 100 nM) from 40 to 52% (p = 0.027). The combined method also significantly improved the PPV when tested on five human alleles, including some with limited data for training. Overall, an average increase of 10% in the PPV was found over the standalone sequence-based method. The combined method should be useful in the rapid design of effective T cell–based vaccines.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

The completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: cosmological implications from multitracer BAO analysis with galaxies and voids

We construct cosmic void catalogues with the dive void finder upon SDSS BOSS DR12 and eBOSS DR16 galaxy samples with BAO reconstruction, and perform a joint BAO analysis using different types of galaxies and the corresponding voids. The BAO peak is evident for the galaxy–galaxy, galaxy–void, and void–void correlation functions of all data sets, including the ones cross-correlating LRG and ELG samples. Two multitracer BAO fitting schemes are tested, one combining the galaxy and void correlation functions with a weight applied to voids, and the other using a single BAO dilation parameter for all clustering measurements. Both methods produce consistent results with mock catalogues, and on average ~10 per cent improvements of the BAO statistical uncertainties are observed for all samples, compared to the results from galaxies alone. By combining the clustering of galaxies and voids, the uncertainties of BAO measurements from the SDSS data are reduced by 5–15 per cent, yielding 0.9 per cent, 0.8 per cent, 1.1 per cent, 2.3 per cent, and 2.9 per cent constraints on the distance $D_{_{\rm V}}(z)$, at effective redshifts 0.38, 0.51, 0.70, 0.77, and 0.85, respectively. When combined with BAO measurements from SDSS MGS, QSO, and Lyα samples, as well as the BBN results, we obtain $H_0 = 67.58 \pm 0.91\, {\rm km}\, {\rm s}^{-1}\, {\rm Mpc}^{-1}$, Ω m = 0.290 ± 0.015, and $\Omega _\Lambda h^2 = 0.3241 \pm 0.0079$ in the flat-ΛCDM framework, where the 1σ uncertainties are around 6 per cent, 6 per cent, and 17 per cent smaller respectively, compared to constraints from the corresponding anisotropic BAO measurements without voids and LRG–ELG cross-correlations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

NGEE Arctic Soil Micro-warming Experiment Temperature Profiles, Council Road Mile Marker 71, Seward Peninsula, Alaska, 2017-2019

The reported soil temperature profile measurements (24 locations - 2 probes with 5 and 6 thermistors, respectively - Fig. 1 and Fig. 2) were initiated as part of a soil micro-warming experiment at the Council Road Mile Marker 71 Site (CN_MM71) in September 2017. From 2017 through August 2019, these were measurements of ambient pre-treatment plot conditions. This tussock tundra site (with underlying permafrost) experiences annual frost heaving that causes a vertical movement of the ground surface, hence causing some of the upper most temperature thermistors to be at surface level or above ground and recorded therefore air temperatures near the surface and not below ground soil temperature (see section on Quality Assurance). After August 2019, these measurements ended in preparation for transitioning to the experimental warming of individual plots. The reported temperature data are nominally 3-hour averages of measurements made at varying frequencies (3-hour maximum) with frequencies that depended upon power (solar) availability to operate the sensors (see section in documentation on Methods). The number of values and the standard deviation for each 3-hour average (where appropriate) are also provided. These measurements are located near the NGEE-Arctic CO2 and CH4 eddy covariance tower at the Council Road Site (US-NGC: NGEE Arctic Council, https://ameriflux.lbl.gov/sites/siteinfo/US-NGC#overview) and auxiliary data at https://doi.org/10.5440/1526749. This dataset contains four *.csv files and one *.pdf file. 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).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Thixotropic spectra and Ashby-style charts for thixotropy

There is no universal model for thixotropy, and comparing thixotropic effects between different fluids is a subtle yet challenging problem. We introduce a generalized (model-insensitive) framework for comparing thixotropic properties based on thixotropic spectra. A superposition of exponential stress modes distributed over thixotropic time scales is used to quantify buildup and breakdown times and mode strengths in response to step-change input. This mathematical framework is tested with several experimental step-shear rate data on colloidal suspensions. Low-dimensional metrics based on moments of the distribution reveal characteristic average thixotropic properties, which are visualized on Ashby-style diagrams. This method outlines a framework for describing thixotropy across a diverse range of microstructures, supporting scientific studies as well as material selection for engineering design applications.

Mechanics↗
DOE OSTI2022

A method to predict texture effect on ion beam channeling analysis of polycrystals and the application to study the mosaic spreading effect in highly oriented pyrolytic graphite

We propose a method to convert the channeling Rutherford backscattering spectrum yield map of a single crystal to a polycrystal through a matrix rotation technique. The rotation matrix is determined by the deviation of the crystal axial direction from the original z axis. The final yield map is created after averaging the rotated yields using the texture function as the weight factor. For highly oriented pyrolytic graphite (HOPG) exhibiting mosaic spread, the method leads to a Gaussian kernel averaging of the map obtained from a single crystal. The yield map of a single crystal is obtained by a simulation of ion trajectories in a potential field described by Moliere screened Coulomb potentials. Yield maps are calculated under various σ values (standard deviations of mosaic spread). The simulated results are compared with experimental results obtained using 1.2 MeV alpha particle. σ is extracted through the best fitting, demonstrating that the method can be used to obtain texture details. The effects of mosaic spread on minimum yield χ min and the half-width at half maximum of angular scans ψ ½ are systematically modeled and compared with previous theoretical equations. The study also shows that previous theoretical equations are valid only at small σ values. The proposed method can be applied to any type of polycrystal and is not limited to HOPG. It provides near-surface mosaic spread and crystallography information with a longitudinal depth resolution of tens of nanometers and is not influenced by grain shapes.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Rapid and Simultaneous Characterization of Drug Conjugation in Heavy and Light Chains of a Monoclonal Antibody Revealed by High-Resolution Ion Mobility Separations in SLIM

Antibody-drug conjugates (ADCs) have recently gained traction in the biomedical community due to their promise for human therapeutics and an alternative to chemotherapy for cancer. Crucial metrics for ADC efficacy, safety, and selectivity are their drug-antibody ratios (DARs). However, DAR characterization (i.e., determining the average number of conjugated drugs on the antibody) through analytical methods remains challenging due to the heterogeneity of drug conjugation as well as the numerous post-translational modifications possible in the monoclonal antibody. In this work, we report on the use of high-resolution ion mobility spectrometry separations in our structures for lossless ion manipulations coupled to mass spectrometry (SLIM IMS-MS) platform for the rapid and simultaneous characterization of the drug load profile (i.e., stoichiometric distribution of the number of conjugated drugs present on the mAb), determination of the weighted average DAR in both the heavy and light chains of a model antibody-drug conjugate, and calculation of the overall DAR of the ADC. After chemical reduction of the ADC and a subsequent 31.5 meter SLIM IMS separation the various drug bound antibody species could be well resolved for both chains. Furthermore, we also show that higher resolution separations were possible with SLIM IMS as compared to ones performed on a commercially available (~1 meter) drift tube IMS-MS platform. Interestingly, additional gas-phase substructures become evident with longer path length SLIM IMS, potentially providing insight related to how drug conjugation may alter the structural properties of a monoclonal antibody and thus affect its overall potency and/or selectivity for a given antigen. We expect high-resolution SLIM IMS separations will augment the existing toolbox for ADC characterization, particularly for structural confirmation to enable the rapid optimization of DAR for a given ADC and thus better understand its potential toxicity and potency.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Impacts of Biofuel Blending on MCCI Ignition Delay with Review of Methods for Defining Cycle-by-Cycle Ignition Points from Noisy Cylinder Pressure Data

Conventional diesel combustion, also known as Mixing-Controlled Compression Ignition (MCCI), is expected to be the primary power source for medium- and heavy-duty vehicles for decades to come. Displacing petroleum-based ultra-low-sulfur diesel (ULSD) as much as possible with low-net-carbon biofuels will become necessary to help mitigate effects on climate change. Neat biofuels may have difficulty meeting current diesel fuel standards but blends of 30% biofuel in ULSD show potential as ‘drop-in’ fuels. These blends must not make significant changes to the combustion phasing of the MCCI process if they are to be used interchangeably with neat ULSD. An important aspect of MCCI phasing is the ignition delay (ID), i.e. the time between the start of fuel injection and the initial premixed autoignition that initiates the MCCI process. Bench experiments can evaluate the expected ignition delay of a fuel via cetane number (CN) or alternative methods such as the indicated cetane number (ICN); however, neither CN nor ICN correlate perfectly with the ignition delay measured in actual engine experiments. Furthermore, there is no standardized methodology on how to quantify MCCI ignition delay from engine cylinder pressure measurements, creating difficulties in cross-study comparison. In this study, several engine ignition delay calculation methods are evaluated for robustness in deriving ignition delay on both a cycle-averaged and cycle-to-cycle basis. Eight biofuel blends with varying ICN, oxygen concentration and other fuel properties were used to study the different methods. This yields a thorough analysis of how certain biofuel blends affect ignition delay and the entire MCCI process, as well as a thorough evaluation of the differences between the ID calculation methods. Many of these methods are equally valid, but the choice of method has a significant impact on the resulting ID, which must be carefully considered when evaluating results across multiple studies.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Impacts of Biofuel Blending on MCCI Ignition Delay with Review of Methods for Defining Cycle-by-Cycle Ignition Points from Noisy Cylinder Pressure Data: Preprint

Conventional diesel combustion, also known as Mixing-Controlled Compression Ignition (MCCI), is expected to be the primary power source for medium- and heavy-duty vehicles for decades to come. Displacing petroleum-based ultra-low-sulfur diesel (ULSD) as much as possible with low-net-carbon biofuels will become necessary to help mitigate effects on climate change. Neat biofuels may have difficulty meeting current diesel fuel standards but blends of 30% biofuel in ULSD show potential as ‘drop-in’ fuels. These blends must not make significant changes to the combustion phasing of the MCCI process if they are to be used interchangeably with neat ULSD. An important aspect of MCCI phasing is the ignition delay (ID), i.e. the time between the start of fuel injection and the initial premixed autoignition that initiates the MCCI process. Bench experiments can evaluate the expected ignition delay of a fuel via cetane number (CN) or alternative methods such as the indicated cetane number (ICN); however, neither CN nor ICN correlate perfectly with the ignition delay measured in actual engine experiments. Furthermore, there is no standardized methodology on how to quantify MCCI ignition delay from engine cylinder pressure measurements, creating difficulties in cross-study comparison. In this study, several engine ignition delay calculation methods are evaluated for robustness in deriving ignition delay on both a cycle-averaged and cycle-to-cycle basis. Eight biofuel blends with varying ICN, oxygen concentration and other fuel properties were used to study the different methods. This yields a thorough analysis of how certain biofuel blends affect ignition delay and the entire MCCI process, as well as a thorough evaluation of the differences between the ID calculation methods. Many of these methods are equally valid, but the choice of method has a significant impact on the resulting ID, which must be carefully considered when evaluating results across multiple studies.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

AERO-MAP: a data compilation and modeling approach to understand spatial variability in fine- and coarse-mode aerosol composition

Abstract. Aerosol particles are an important part of the Earth climate system, and their concentrations are spatially and temporally heterogeneous, as well as being variable in size and composition. Particles can interact with incoming solar radiation and outgoing longwave radiation, change cloud properties, affect photochemistry, impact surface air quality, change the albedo of snow and ice, and modulate carbon dioxide uptake by the land and ocean. High particulate matter concentrations at the surface represent an important public health hazard. There are substantial data sets describing aerosol particles in the literature or in public health databases, but they have not been compiled for easy use by the climate and air quality modeling community. Here, we present a new compilation of PM2.5 and PM10 surface observations, including measurements of aerosol composition, focusing on the spatial variability across different observational stations. Climate modelers are constantly looking for multiple independent lines of evidence to verify their models, and in situ surface concentration measurements, taken at the level of human settlement, present a valuable source of information about aerosols and their human impacts complementarily to the column averages or integrals often retrieved from satellites. We demonstrate a method for comparing the data sets to outputs from global climate models that are the basis for projections of future climate and large-scale aerosol transport patterns that influence local air quality. Annual trends and seasonal cycles are discussed briefly and are included in the compilation. Overall, most of the planet or even the land fraction does not have sufficient observations of surface concentrations – and, especially, particle composition – to characterize and understand the current distribution of particles. Climate models without ammonium nitrate aerosols omit ∼ 10 % of the globally averaged surface concentration of aerosol particles in both PM2.5 and PM10 size fractions, with up to 50 % of the surface concentrations not being included in some regions. In these regions, climate model aerosol forcing projections are likely to be incorrect as they do not include important trends in short-lived climate forcers.

Mahowald, Natalie M. (ORCID:000000022873997X)↗
DOE OSTI2022

An ensemble data assimilation modeling system for operational outdoor microalgae growth forecasting

Microalgae have received increasing attention as a potential feedstock for biofuel or biobased products. Forecasting the microalgae growth is beneficial for managers in planning pond operations and harvesting decisions. This study proposed a biomass forecasting system comprised of the Huesemann Algae Biomass Growth Model (BGM), the Modular Aquatic Simulation System in Two Dimensions (MASS2), ensemble data assimilation (DA), and numerical weather prediction Global Ensemble Forecast System (GEFS) ensemble meteorological forecasts. The novelty of this study is to seek the use of ensemble DA to improve both BGM and MASS2 model initial conditions with the assimilation of biomass and water temperature measurements and consequently improve short-term biomass forecasting skills. This study introduces the theory behind the proposed integrated biomass forecasting system, with an application undertaken in pseudo-real-time in three outdoor ponds cultured with Chlorella sorokiniana in Delhi, California, United States. Results from all three case studies demonstrate that the biomass forecasting system improved the short-term (i.e., 7-day) biomass forecasting skills by about 60% on average, comparing to forecasts without using the ensemble DA method. Given the satisfactory performances achieved in this study, it is probable that the integrated BGM-MASS2-DA forecasting system can be used operationally to inform managers in making pond operation and harvesting planning decisions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Hybrid large-eddy simulation with adaptive downstream anisotropic eddy viscosity model

Turbulence pervades most flows of engineering interest, and its prediction remains a challenge on both accuracy and cost. One promising predictive approach that reduces cost combines large-eddy simulation (LES) with simulation based on Reynolds averaged Navier–Stokes equations (RANS). This study presents a method to overcome stability and accuracy issues associated with these hybrid LES-RANS methods. The method developed involves extracting the Reynolds stresses from the upstream LES solution and then using that information to convert the downstream RANS model from a scalar eddy-viscosity model to an anisotropic nonlinear eddy-viscosity model. The method developed differs from the downstream tensorial eddy-viscosity model by being independent of the coordinate system. The method developed was evaluated by computing film cooling of a flat plate with the coolant injected through one row of circular holes. Results obtained show instabilities at the LES-to-RANS interface to be eliminated. Also, the method developed yielded solutions that compare reasonably well with those from LES, even though a significant portion of the flow is computed by the adapted anisotropic RANS model instead of LES, which significantly reduced the number of grid points and computational time needed. Since modification of the downstream RANS model is based on information extracted from the upstream LES solution, the method developed is adaptive to the problem being studied.

42 ENGINEERING↗
DOE OSTI2021

Understanding Flow Characteristics in Metal Additive Manufacturing

In fluid flow, the frictional effects from interior surfaces of flow components create pressure loss across the surface. Understanding this inherent pressure loss due to friction and other phenomena is important when designing a flow system. For conventional manufacturing, friction loss has been empirically studied and is well known in the engineering community. However, newer manufacturing techniques, such as laser powder bed fusion (LPBF), an additive manufacturing technique, need to be understood. The inherent flow conditions resulting from the additive processes were studied. Test samples were printed with the flow path oriented in the vertical direction with different channel diameters to characterize the inherent fundamental flow properties of the process. Moody diagrams were replicated for a greater understanding of possibilities and shortfalls when implementing LPBF into design applications. Experimental flow testing revealed that greater effective sand grain roughness resulted from this process when compared to conventional machining methods. This roughness did not correlate well to the average roughness measured with a laser scanning microscope but was consistent with the average particle size of the powder metal feedstock.

42 ENGINEERING↗
DOE OSTI2024

On the Impact of Bus Dwelling on Macroscopic Fundamental Diagrams

Network macroscopic fundamental diagrams (MFDs) have recently been shown to exist in real-world urban traffic networks. When present, MFDs can be used to model traffic dynamics within an urban network by dividing the network into a set of spatially compact homogeneous regions and tracking the average level of congestion in each region. Existing analytical methods to estimate MFD mostly focus on the behavior of a single type of vehicle and do not capture the patterns of mixed traffic (e.g., cars and buses). The existence of buses matters since a bus will block the movements of other vehicles when it dwells at the bus stop. This paper proposes an analytical method to estimate the impact of bus dwelling on a network’s MFD based on the network’s geometric features, traffic control strategies, and bus operation parameters, and validates the performance of the proposed method using simulations based on microscopic traffic models. Comparisons of the analytical and simulation results show that the proposed analytical method can generally provide a good estimate of the lower bound and upper bound of the network’s MFD.

Xu, Guanhao↗
DOE OSTI2024

Multiple-carrier-lifetime model for carrier dynamics in InGaN/GaN LEDs with a non-uniform carrier distribution

Here we introduce a multiple-carrier-lifetime model (MCLM) for light-emitting diodes (LEDs) with non-uniform carrier distribution, such as in multiple-quantum-well (MQW) structures. By employing the MCLM, we successfully explain the modulation response of V-pit engineered MQW LEDs, which exhibit an S 21 roll-off slower than –20 dB/decade. Using the proposed model and employing a gradient descent method, we extract effective recombination and escape lifetimes by averaging the carrier behavior across the quantum wells. Our results reveal slower effective carrier recombination and escape in MQW LEDs compared with LEDs emitting from a single QW, indicating the advantages of lower carrier density achieved through V-pit engineering. Notably, the effective carrier recombination time is more than one order of magnitude lower than the effective escape lifetime, suggesting that most carriers in the quantum wells recombine, while the escape process remains weak. To ensure the reliability and robustness of the MCLM, we subject it to a comprehensive threefold validation process. This work confirms the positive impact of spreading carriers into several quantum wells through V-pit engineering. In addition, the MCLM is applicable to other LEDs with a non-uniform carrier distribution, such as micro-LEDs with significant surface recombination and non-uniform lateral carrier profiles.

42 ENGINEERING↗
DOE OSTI2024

Design of experiments to spectroscopically characterize radiation flow in stochastic media

Precise characterization of experimental radiation flow is required to validate the high energy density physics models, numerical methods, and codes that are used to simulate radiation-hydrodynamics phenomena such as thermal radiation transport in stochastic media. The Cassio code is used to simulate thermal radiation flow through inhomogeneous, stochastic-media-foam configurations containing optically thick clumps dispersed within an optically thin background aerogel. Cassio can model small inhomogeneous problems directly, but most problems require approximations to meet computer limitations on run-times and memory usage. Various examples of these approximations are methods that produce, in one calculation, an ensemble-averaged solution and associated standard deviation; reduced spatial dimensionality with approximate geometries; and full material homogenization with no geometric detail. Cassio simulations are used to design experiments at the OMEGA-60 Laser Facility that can measure the radiation flow using the spatially resolved COAX absorption spectroscopy diagnostic. The experimental platforms flow radiation through foam targets ranging from a background-only aerogel, to a single configuration of a specified stochastic medium, to a fully homogenized foam of the background and clump materials. Under constant total clump mass, larger clumps (here, larger than 10 μm diameter) will mix more slowly with the background such that the bulk radiation flow is faster than it would be in a fully homogenized material. The COAX platform can be used to infer temperature and density profiles in both the background material and clumps, simultaneously, and therefore to differentiate radiation flow in a range of stochastic and homogeneous media.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Energetic particle optimization of quasi-axisymmetric stellarator equilibria

Abstract An important goal of stellarator optimization is to achieve good confinement of energetic particles such as, in the case of a reactor, alphas created by deuterium–tritium fusion. In this work, a fixed-boundary stellarator equilibrium was re-optimized for energetic particle confinement via a two-step process: first, by minimizing deviations from quasi-axisymmetry (QA) on a single flux surface near the mid-radius, and secondly by maintaining this improved QA while minimizing the analytical quantity Γ C , which represents the angle between magnetic flux surfaces and contours of J | | , the second adiabatic invariant. This was performed multiple times, resulting in a group of equilibria with significantly reduced energetic particle losses, as evaluated by Monte Carlo simulations of alpha particles in scaled-up versions of the equilibria. This is the first time that energetic particle losses in a QA stellarator have successfully been reduced by optimizing Γ C . The relationship between energetic particle losses and metrics such as QA error ( E q a ) and Γ C in this set of equilibria were examined via statistical methods and a nearly linear relationship between volume-averaged Γ C and prompt particle losses was found.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

PAC in DESI. II. Galaxy-halo connection into the $10^{6}{\rm M}_{\odot}$ frontier

Understanding dwarf galaxy formation is crucial for testing dark matter models and reionization physics. However, constructing stellar-mass complete spectroscopic samples at low masses is increasingly difficult, and the potential existence of a local void complicates studies in an average environment. The Photometric object Around Cosmic webs (PAC) method, which combines deep photometric and spectroscopic data to measure the excess surface density $\bar{n}_2w_{\rm{p}}(r_{\rm{p}})$ of photometric objects around spectroscopic tracers, offers a promising path forward. We model 349 $\bar{n}_2w_{\rm{p}}(r_{\rm{p}})$ measurements from DESI Y1 BGS and DECaLS, reaching $M_*=10^{6.4}\,{\rm M}_{\odot}$, using a stellar mass-halo mass relation (SHMR)-based subhalo abundance matching framework applied to two high-resolution $N$-body simulations from the Jiutian suite. The resulting SHMR is constrained down to $M_{\rm h}\simeq10^{8.0}\,h^{-1}{\rm M}_{\odot}$, revealing a clear upturn at $\sim10^{10.0}\,h^{-1}{\rm M}_{\odot}$ toward lower masses, indicating rising star-formation efficiency (SFE) in small haloes. This feature persists under extensions of the model that allow mass-dependent scatter, reionization-induced suppression of the halo occupation fraction, galaxy assembly bias, and alternative cosmologies. Combining with the results from Paper I, we find that central red galaxies dominate the low-mass regime. Our results motivate a hypothesis in which SFE is significantly higher than previously thought prior to reionization, enabling relatively massive galaxies to form in small haloes. These systems are subsequently quenched by the UV background, producing the central red dwarf galaxies observed. Finally, we obtain $3σ$ and $5σ$ upper mass bounds of $10^{8.80}\,h^{-1}{\rm M}_{\odot}$ and $10^{10.24}\,h^{-1}{\rm M}_{\odot}$ on the smallest haloes required to exist.

Xu, Kun [Pennsylvania U.; Durham U., ICC; Tsung-Da↗