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At least 19 records

Role of the junction voltage on the overflow current in light-emitting diodes

Quantum-well (QW)-based light emitters, such as light-emitting diodes (LEDs) and lasers, of various semiconductor materials experience a reduction in their efficiency when operating at higher temperatures, a phenomenon referred to as “thermal droop.” Among the various claims on the origins of thermal droop, an increased overflow current with increasing temperatures is a common contender. Since overflow of carriers can only occur when the junction voltage 𝑉 Junction approaches the built-in voltage 𝑉 BI of any diodes, we develop a simple method relating the difference between 𝑉 Junction and 𝑉 BI to approximate the upper limit of overflow occurring in QW-based light-emitting diodes. The measured difference between 𝑉 Junction and 𝑉 BI of state-of-the-art commercial blue and green In⁢Ga⁢N-based LEDs at temperatures up to ∼450 K suggests negligible overflow. To further experimentally verify the absence of overflow, we perform temperature-dependent electron emission spectroscopy on the same commercial blue and green LEDs and find no evidence of thermally enhanced overflow carriers up to ∼450 K. In agreement with our claims that 𝑉 Junction must approach 𝑉 BI for overflow to occur, two-dimensional temperature-dependent electrical simulations of violet, blue, and green LEDs including alloy disorder and V-defects demonstrate that overflow can be significant in violet LEDs, where the small band offset between the In⁢Ga⁢N QW and Ga⁢N cladding layers due to the larger QW bandgap requires larger 𝑉 Junction to reach standard operating current densities, thereby approaching 𝑉 BI . By contrast, simulations indicate that overflow is negligible in blue and green LEDs, whose smaller QW bandgaps result in smaller quasi-Fermi levels difference to reach significant carrier injection, resulting in a 𝑉 Junction much smaller than 𝑉 BI up to large operating current densities. Considering that overflow is negligible in blue and longer-wavelength LEDs, and our observations of the large thermal droop occurring at low current densities, where Shockley-Read-Hall (SRH) recombination dominates, we conclude that thermally enhanced SRH processes are the most significant contributor to thermal droop. Finally, we also simulate the carrier densities in the different QWs of a multiple-QW LED and observe a reduction in the total carrier density at a given operating current density, which results in a decrease in the total Auger-Meitner current of the LED from just the thermally enhanced carrier redistribution among QWs without taking any possible additional temperature dependence of their recombination coefficients. Taking all this into account, minimizing thermal droop effects in LEDs can be achieved by a reduction in defect density, using wider band gap p-n junction-defining cladding layers, and operating at higher currents.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND

Development of a Data Overflow Protection System for Super-Kamiokande to Maximize Data from Nearby Supernovae

Neutrinos from very nearby supernovae, such as Betelgeuse, are expected to generate more than ten million events over 10 s in Super-Kamokande (SK). At such large event rates, the buffers of the SK analog-to-digital conversion board (QBEE) will overflow, causing random loss of data that are critical for understanding the dynamics of the supernova explosion mechanism. In order to solve this problem, two new data-acquisition (DAQ) modules were developed to aid in the observation of very nearby supernovae. The first of these, the SN module, is designed to save only the number of hit photomultiplier tubes during a supernova burst and the second, the Veto module, prescales the high-rate neutrino events to prevent the QBEE from overflowing based on information from the SN module. In the event of a very nearby supernova, these modules allow SK to reconstruct the time evolution of the neutrino event rate from beginning to end using both QBEE and SN module data. This paper presents the development and testing of these modules together with an analysis of supernova-like data generated with a flashing laser diode. We demonstrate that the Veto module successfully prevents DAQ overflows for Betelgeuse-like supernovae as well as the long-term stability of the new modules. During normal running the Veto module is found to issue DAQ vetos a few times per month resulting in a total dead-time less than 1 ms, and does not influence ordinary operations. Additionally, using simulation data we find that supernovae closer than 800 pc will trigger the Veto module, resulting in a prescaling of the observed neutrino data.

F20 Instrumentation and technique

Investigating overflow metabolism in heterotrophic cultures of the green alga Chromochloris zofingiensis

Chromochloris zofingiensis is of interest for its ability to perform a reversible trophic switch in the presence of glucose that is characterized by a shutdown of photosynthesis and an accumulation of energy storage metabolites. Previous work has shown that this trophic switch is accompanied by overflow metabolism and the production of lactate in aerobic conditions. This trophic switch is not observed in nutrient replete media. We utilized isotopically assisted metabolic flux analysis to characterize intracellular flux distributions that are associated with different metabolic phenotypes observed in this organism in different media formulations in light and dark conditions. The results of this analysis showed that low iron cultures have no flux through carbon fixation reactions, and that the carbon flux entering the TCA cycle in these cultures is approximately 40 % lower than that in iron replete cultures grown heterotrophically. This analysis was complemented with transcriptomics data collected for C. zofingiensis grown in iron limited conditions to provide further evidence towards the negative impact of iron limitation on both photosynthetic and respiratory activity. Overflow metabolism allows this alga to compensate for the lower energy production that results from iron limitation. This work highlights how nutrient availability can lead to changes in the metabolism of C. zofingiensis.

59 BASIC BIOLOGICAL SCIENCES

Expanded genome and proteome reallocation in a novel, robust Bacillus coagulans strain capable of utilizing pentose and hexose sugars

Bacillus coagulans, a Gram-positive thermophilic bacterium, is recognized for its probiotic properties and recent development as a microbial cell factory. Despite its importance for biotechnological applications, the current understanding of B. coagulans’ robustness is limited, especially for undomesticated strains. To fill this knowledge gap, we characterized the metabolic capability and performed functional genomics and systems analysis of a novel, robust strain, B. coagulans B-768. Genome sequencing revealed that B-768 has the largest B. coagulans genome known to date (3.94 Mbp), about 0.63 Mbp larger than the average genome of sequenced B. coagulans strains, with expanded carbohydrate metabolism and mobilome. Functional genomics identified a well-equipped genetic portfolio for utilizing a wide range of C5 (xylose, arabinose), C6 (glucose, mannose, galactose), and C12 (cellobiose) sugars present in biomass hydrolysates, which was validated experimentally. For growth on individual xylose and glucose, the dominant sugars in biomass hydrolysates, B-768 exhibited distinct phenotypes and proteome profiles. Faster growth and glucose uptake rates resulted in lactate overflow metabolism, which makes B. coagulans a lactate overproducer; however, slower growth and xylose uptake diminished overflow metabolism due to the high energy demand for sugar assimilation. Carbohydrate Transport and Metabolism (COG-G), Translation (COG-J), and Energy Conversion and Production (COG-C) made up 60%–65% of the measured proteomes but were allocated differently when growing on xylose and glucose. The trade-off in proteome reallocation, with high investment in COG-C over COG-G, explains the xylose growth phenotype with significant upregulation of xylose metabolism, pyruvate metabolism, and tricarboxylic acid (TCA) cycle. Strain B-768 tolerates and effectively utilizes inhibitory biomass hydrolysates containing mixed sugars and exhibits hierarchical sugar utilization with glucose as the preferential substrate.

carbohydrate metabolism

Oleaginous Yeast Biology Elucidated With Comparative Transcriptomics

ABSTRACT Extremophilic yeasts have favorable metabolic and tolerance traits for biomanufacturing‐ like lipid biosynthesis, flavinogenesis, and halotolerance – yet the connection between these favorable phenotypes and strain genotype is not well understood. To this end, this study compares the phenotypes and gene expression patterns of biotechnologically relevant yeasts Yarrowia lipolytica , Debaryomyces hansenii , and Debaryomyces subglobosus grown under nitrogen starvation, iron starvation, and salt stress. To analyze the large data set across species and conditions, two approaches were used: a “network‐first” approach where a generalized metabolic network serves as a scaffold for mapping genes and a “cluster‐first” approach where unsupervised machine learning co‐expression analysis clusters genes. Both approaches provide insight into strain behavior. The network‐first approach corroborates that Yarrowia upregulates lipid biosynthesis during nitrogen starvation and provides new evidence that riboflavin overproduction in Debaryomyces yeasts is overflow metabolism that is routed to flavin cofactor production under salt stress. The cluster‐first approach does not rely on annotation; therefore, the coexpression analysis can identify known and novel genes involved in stress responses, mainly transcription factors and transporters. Therefore, this work links the genotype to the phenotype of biotechnologically relevant yeasts and demonstrates the utility of complementary computational approaches to gain insight from transcriptomics data across species and conditions.

Weintraub, Sarah J. [Department of Bioinformatics

Hydrocyclone pre-processing of wastewater algae: A strategy for inorganic ash separation

Microalgae cultivation on wastewater can provide remediation and generate valuable feedstocks for biofuel production. Wastewater algae typically have a high percentage of inorganic ash, which can reduce yield and quality of biocrude produced during hydrothermal liquefaction (HTL). Here, in this work, we evaluated the ability of hydrocyclone pre-processing to remove inorganic ash from wastewater algae. The pH of the algae slurry was adjusted to 9.5 to encourage the formation of precipitates and create a density differential between ash particles and algal cells. Hydrocyclone processing successfully concentrated ash particles in the underflow fraction and reduced the total ash percentage in the overflow fraction. Overall, hydrocyclone processing reduced the total ash by 21%, while only 8% of organics were lost. Elemental and mineral analysis showed that Mg and P were concentrated in the underflow in the form of baricite (an isomorph of vivianite). Future research should focus on improving vivianite and/or baricite formation, and therefore ash removal, by providing a reducing environment. The addition of multiple hydrocyclones in series could also improve the removal of ash. We concluded that hydrocyclone treatment of wastewater algae is a feasible method to remove inorganic ash, but further process optimization is required.

09 - BIOMASS FUELS

Leveraging explainable AI to characterize floating-point exceptions in linear solvers

Linear solver packages are central to many scientific, engineering, and machine learning applications. When floating-point exceptions occur in these solvers, e.g., division by zero or overflow, numerical results are compromised and become unreliable. Existing static and dynamic analysis tools can detect such exceptions, but they do not explain why the exceptions occur in terms of the solver inputs. Here, we present a study to characterize the inputs that cause numerical exceptions in linear solver packages. Our approach uses explainable AI (XAI) to find the most relevant characteristics of input matrices that explain the occurrence of exceptions in the solvers. Since training data in this domain is scarce, we perform extensive data gathering and data augmentation to obtain exception-inducing inputs. Our approach uses a repair strategy on the features blamed by XAI to validate that such features indeed explain the exceptions. We compare the LIME and SHAP XAI techniques using a dozen matrix features with three classifiers. We evaluate the approach on three widely used linear solver packages and find that some input characteristics can explain the occurrence of exceptions 100% of the time, in specific solvers and preconditioners.

Explainable AI

Persistent urinary metabolic signatures in children with type 1 diabetes

There are an estimated 3.7 million people with undiagnosed type 1 diabetes (T1D), living primarily in poor areas of the globe. Therefore, there is a need for non-invasive, affordable tests to provide accurate diagnosis despite the time post-disease onset and fasting state. Here, we studied persistent urinary T1D biomarkers that can be used to develop such tests. Here, we analyzed the urine metabolomes of three independent cohorts of samples collected within 48 h (from Indiana University), and 1 year (from University of Colorado) and 1–10 years (6 years in average) (from Children’s National Medical Center) post-diagnosis. Samples were submitted to gas chromatography-mass spectrometry and machine learning an0alyses to determine diagnostic metabolite panels. The data were also mapped into a metabolic pathway to understand persistently regulated processes in T1D. Seven metabolites showed consistent increases in all three cohorts: d-glucose, d-mannose, myo-inositol, 3-hydroxyisobutyric acid, gluconolactone, d-gluconic acid, and d-glucuronic acid. A combination of machine learning analysis and metabolite ratios as biomarker candidates diagnosed T1D with high sensitivity and specificity across different cohorts and times. Mapping the regulated metabolites into a pathway showed impairment in glycolysis and overflow of glucose towards other pathways in subjects with T1D that was persistent over time. We identified and cross-validated highly specific and sensitive urinary biomarkers. This opens opportunities to develop affordable, robust, and non-invasive tests. The results also show that most of the biomarkers were signatures of dysregulated glucose metabolism.

Type 1 diabetes

A nonhydrostatic formulation for MPAS-Ocean

The Model for Prediction Across Scales-Ocean (MPAS-Ocean) is an open-source, global ocean model and is one component of a family of climate models within the MPAS framework, including atmosphere, sea-ice, and land-ice models. Here, in this work, a new formulation for the ocean model is presented that solves the nonhydrostatic, incompressible Boussinesq equations on an unstructured, staggered, z-level grid. The introduction of this nonhydrostatic capability is necessary for the resolution of internal wave dynamics and large eddy simulations. Compared to the standard, hydrostatic formulation, a nonhydrostatic pressure solver and a vertical momentum equation are added, where the PETSc (Portable Extensible Toolkit for Scientific Computation) library is used for the inversion of a large sparse system for the nonhydrostatic pressure. Numerical results on a stratified seiche, internal solitary wave, overflow and lock-exchange test cases are presented, and the parallel efficiency of the code is evaluated using up to 1024 processors.

3D Poisson equation

A nonhydrostatic formulation for MPAS-Ocean

The Model for Prediction Across Scales-Ocean (MPAS-Ocean) is an open-source, global ocean model and is one component of a family of climate models within the MPAS framework, including atmosphere, sea-ice, and land-ice models. Here, in this work, a new formulation for the ocean model is presented that solves the nonhydrostatic, incompressible Boussinesq equations on an unstructured, staggered, z-level grid. The introduction of this nonhydrostatic capability is necessary for the resolution of internal wave dynamics and large eddy simulations. Compared to the standard, hydrostatic formulation, a nonhydrostatic pressure solver and a vertical momentum equation are added, where the PETSc (Portable Extensible Toolkit for Scientific Computation) library is used for the inversion of a large sparse system for the nonhydrostatic pressure. Numerical results on a stratified seiche, internal solitary wave, overflow and lock-exchange test cases are presented, and the parallel efficiency of the code is evaluated using up to 1024 processors.

3D Poisson equation

Branched-chain amino acid specialization drove diversification within Calditenuaceae ( Caldarchaeia ) and enables their cultivation

Many thermophiles that are abundant in high-temperature geothermal systems have never been cultivated and are poorly understood, including deeply branching members of the archaeal phylum Thermoproteota. Here, we describe the genome-guided cultivation of one such organism, Calditenuis ramacidaminiphagus, and show that it has evolved a heterotrophic metabolism focused on branched-chain amino acids (BCAAs). Initially, fluorescence in situ hybridization and nanoscale secondary ion mass spectrometry (FISH-nanoSIMS) showed that Cal. ramacidaminiphagus assimilated amino acids rapidly in casamino acid-amended enrichment cultures. Metagenome and metaproteome analyses showed a high abundance and expression of BCAA transporter genes, suggesting a BCAA-focused metabolism. This inference was supported by the subsequent enrichment of Cal. ramacidaminiphagus in BCAA-fed cultures, reaching 2.66×10 6 cells/mL and 48.7% of the community, whereas it was outcompeted when polar amino acids were included. Metabolic reconstruction and metaproteomics suggest that BCAAs are channeled into the mevalonate pathway for lipid biosynthesis and fuel ATP production through the TCA cycle coupled with aerobic respiration and through production of branched-chain organic acids by overflow metabolism. Ancestral state reconstructions and phylogenetic analyses of 62 Caldarchaeales genomes revealed multiple horizontal transfers of BCAA transporters to the ancestor of the genus Calditenuis. Our study highlights the crucial role of BCAAs in the early evolution and niche of this genus, and suggests a high degree of resource partitioning even within low-diversity thermophilic communities.

Biological and medical sciences

Floods of Egypt’s Nile in the 21st century

Extreme precipitation and flooding events are rising globally, necessitating a thorough understanding and sustainable management of water resources. One such setting is the Nile River’s source areas, where high precipitation has led to the filling of Lake Nasser (LN) twice (1998–2003; 2019–2022) in the last two decades and the diversion of overflow to depressions west of the Nile, where it is lost mainly to evaporation. Using temporal satellite-based data, climate models, and continuous rainfall-runoff models, we identified the primary contributor to increased runoff that reached LN in the past two decades and assessed the impact of climate change on the LN’s runoff throughout the twenty-first century. Findings include: (1) the Blue Nile subbasin (BNS) is the primary contributor to increased downstream runoff, (2) the BNS runoff was simulated in the twenty-first century using a calibrated (1965–1992) rainfall-runoff model with global circulation models (GCMs), CCSM4, HadGEM3, and GFDL-CM4.0, projections as model inputs, (3) the extreme value analysis for projected runoff driven by GCMs’ output indicates extreme floods are more severe in the twenty-first century, (4) one adaptation for the projected twenty-first century increase in precipitation (25–39%) and flood (2%-20%) extremes is to recharge Egypt’s fossil aquifers during high flood years.

Climate change

A multi-omic characterization of the physiological responses to salt stress in Scenedesmus obliquus UTEX393

Scenedesmus obliquus UTEX393 is a promising microalgal candidate for sustainable biomanufacturing but its limited halotolerance hinders large-scale cultivation in saline environments. To investigate the molecular basis of salt stress responses, we conducted a comprehensive multi-omic analysis integrating genomics, transcriptomics, proteomics, lipidomics, metabolomics, and DNA affinity purification sequencing (DAP-seq). An improved nuclear genome assembly and annotation yielded 19,017 gene models and a 97% BUSCO completeness score, enabling construction of a genome-scale metabolic model. Comparing 15 ppt salinity stress to 5 ppt control, growth and productivity were significantly reduced, accompanied by widespread transcriptomic and proteomic changes. Transcriptomic analysis revealed downregulation of photosynthetic machinery and energy conservation genes, and upregulation of stress-responsive elements such as expansins, flavodoxins, and osmoprotectants. Lipidomic profiling showed accumulation of triacylglycerols (TAGs) and degradation of galactosyl lipids, consistent with a shift toward lipid biosynthesis to mitigate redox imbalance. Depletion of key polar metabolites and branched-chain amino acids suggested a rerouting of central carbon metabolism under stress. DAP-seq identified key transcription factors, including LHY1 and SPL12, that target central metabolic enzymes involved in redox balancing, such as glyceraldehyde-3-phosphate dehydrogenase (GAPDH) and malate dehydrogenase (MDH). These findings establish a regulatory-metabolic framework linking redox stress to lipid accumulation and reveal potential engineering targets to enhance salt tolerance. Overall, the multi-omic analysis supports the “overflow” hypothesis, where impaired photosynthesis results in excess reducing equivalents being diverted into TAG synthesis and highlights transcriptional regulators as candidates for improving algal robustness in brackish environments.

09 BIOMASS FUELS

Comparing multi-source urban flood indicators: satellite, simulation, and citizen-reported data

Urban flooding arises from complex mechanisms, making it challenging to capture accurately with a single detection method. This study evaluates three complementary approaches to detect flooding across three Chicago neighborhoods: (i) Sentinel-1 synthetic aperture radar (SAR), offering weather-independent, high-resolution (10 m) imagery of surface inundation; (ii) the storm water management model (SWMM), simulating combined sewer overflow and drainage performance; and (iii) citizen-generated 311 service requests, capturing observed flooding impacts. By analyzing six storms ranging from severe to mild, we examine how each source uniquely contributes to identifying urban flood events. SAR imagery effectively identifies standing water but can miss brief flooding due to satellite revisit constraints. SWMM provides detailed insights into system-wide drainage behavior yet may underestimate localized street-level flooding. Meanwhile, 311 calls reflect real-world flooding impacts but are vulnerable to underreporting. Statistical overlap analysis highlights chronic flood hotspots repeatedly identified across multiple detection methods, indicating persistent infrastructure and topographic vulnerabilities. Temporal analysis further reveals that while SWMM flooding aligns closely with rainfall peaks, 311 calls typically precede or persist beyond these peaks. Our findings emphasize the value of using satellite observations, hydrological modeling, and resident-reported data in a complementary manner to better interpret patterns in flood timing, severity, and spatial distribution—providing insights that can inform targeted infrastructure improvements and contribute to urban flood resilience planning.

311

Trap-assisted Auger-Meitner recombination in GaN p-i-n diodes

Most properties of semiconductor devices are dominated by shallow impurities. However, deep defects often play an important role, for instance, in recombination processes or high field transport. While a variety of techniques are available to assess the density and energy levels of impurities, other properties, such as the recombination mechanisms of the defects, escape observation. We report on the direct measurement of hot electrons generated by trap-assisted Auger-Meitner recombination (TAAR) in GaN p-i-n diodes. By performing electron emission spectroscopy (EES) on diodes with surfaces activated to negative electron affinity by cesium, we observe the expected overflow electrons of p-i-n diodes under low current injection. However, when operating the devices at higher current densities, as low as ∼25 A/c⁢m 2 , we measure the emission of high-energy electrons. At variance with the observed hot electrons in light-emitting diodes (LEDs) using EES, the hot electrons generated in p-i-n diodes at our tested currents cannot be from eeh Auger-Meitner recombination due to the diodes' significantly lower carrier densities compared to those in LEDs. During our measurements, we observe the emission of accumulated electrons with energies ∼0.42 eV, ∼0.99 eV, ∼1.43 eV, and ∼2.32 eV above the conduction-band minimum (CBM) at various bias conditions, suggesting the existence of conduction-band features in GaN at these energies where electrons can be long-lived, such as satellite-valley minima and inflection points. We also measure incompletely relaxed hot electrons approaching energies 1.97 ± 0.13 eV and 2.94 ± 0.13 eV above the CBM, as the diodes are biased to high currents, suggesting at least some of the TAAR partaking defects have an energy level ≳1.97 eV and ≳2.94 eV away from either the conduction or valence band edges. Additionally, at our highest operating currents, we measure hot electrons with energies 3.28 ± 0.13 eV above the CBM, providing direct evidence of TAAR processes involving shallow impurities. This unexpected observation of TAAR in GaN p-i-n diodes spotlights the importance of further studies of defects in GaN and the necessity to incorporate the multi-phonon emission, radiative, and TAAR capture steps of defect-assisted recombination cycles into device modeling. Furthermore, this experiment demonstrates the applicability of the simplest semiconductor structures, p-i-n diodes, as a test bed to study the rich recombination physics of semiconductor materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND

Securing Federated Learning Against Active Reconstruction Attacks

Federated Learning (FL) has amassed notable attention for its ability to preserve user privacy while emphasizing the retainment of model training efficiency. Due to this potential, FL has been integrated in many domains, such as healthcare, finance, law, and industrial engineering, where data cannot be easily exchanged due to sensitive information and strict privacy laws. However, current research has indicated that FL protocols are easily compromised by active data reconstruction attacks employed by actively dishonest servers. The malicious modification of global model parameters allows an actively dishonest server to obtain a direct copy of users’ private data via gradient inversion. Here, this class of attacks is highly underexplored and continues to be a major challenge due to the intense threat model. In this paper, we propose OASIS as a scalable and modality-agnostic defense based on data augmentation that counteracts active data reconstruction attacks while preserving model performance. To generalize our defense, we uncover the intuition behind gradient inversion that enables these attacks and theoretically establish the conditions by which the defense can be considered robust regardless of attack design. From this, we formulate our defense with data augmentation that illustrates its ability to undermine the attack principle. We evaluate OASIS on five real-world datasets–two image-based (ImageNet and CIFAR100) and three text-based (Wikitext, Stack Overflow, and Shakespeare)–which span diverse uses cases such as vision tasks and language modeling. Comprehensive evaluations on these datasets exhibit the efficacy of OASIS and highlight its feasibility as a solution.

97 MATHEMATICS AND COMPUTING

The Scaling and Units of the Elastic Response Term for Rayleigh Waves that is Output by Computer Programs in Seismology (CPS)

We report on the scaling and units of the Rayleigh wave elastic response function A R (ω) that is output from the widely used Computer Programs in Seismology (CPS) to aid in the modeling of ground motion sourced by atmospheric explosions. The program uses mixed units (km, second, km/s, gm/cc) to keep A R (ω) near 10 0 and prevent any numerical underflow or overflow. We compare two models for the response of an elastic half space to the output from CPS. Our application inputs the recommended, mixed unit geological models to determine how researchers must scale this output to obtain physical units for A R (ω) that represents the amplitude scaling for the minimum group velocity (Airy phase) contribution to Rayleigh waves. We determine that a CPS user must scale the output for A R (ω) by 10 -12 (m/km) 2 (g/cc/m 3 /kg) to obtain MKS (meter, kg, second) units and then must multiply this result by the vertical component eigenfunction squared, that is evaluated at the free surface.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF

Simulations of Interacting Binary Systems—Pathways to Radio-bright Gamma-Ray Burst Progenitors

Although the association of gamma-ray bursts (GRBs) with massive stellar death is on firm footing, the nature of the progenitor system and the key ingredients required for a massive star to produce a GRB remain open questions. Here, we investigate the evolution of a 15–25M ⊙ massive star with a 10–15M ⊙ black hole (BH) using Modules for Experiments in Stellar Astrophysics. We quantify companion-influenced angular-momentum evolution over a stellar lifetime for orbital periods where tides are significant, varying stellar and BH masses, initial stellar spin, and accretion and dynamo prescriptions while tracking mass loss and angular momentum. The final spin is set by tidal torques versus stellar winds. For binaries that initially avoid Roche-lobe overflow, tides can spin up the star, but a late-stage expansion can drive tidal stripping; associated mass and angular-momentum loss can suppress spin-up. We find that massive-star BH binaries at comparable mass ratios may be potential GRB progenitors for short orbital periods (∼20–5 × 10 2 days) and long orbital periods (∼2 × 10 3 –4 × 10 3 days), where our suite of lifetime simulations reveals a favored parameter space with negligible mass loss and enough spin angular momentum to power a GRB jet. For initially nonrotating stars, this provides a lower limit on the final spin above a threshold estimate consistent with forming a postcollapse BH mass of 5–10M ⊙ with a spin parameter ≥ 0.5. For initially rapidly rotating stars, tidal interactions may sustain high spin when mass loss is negligible because the binary is not tidally synchronized.

Hernandez, Angel [Univ. of Colorado, Boulder, CO (