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DOE OSTI2024

Tunneling magnetoresistance in MgO tunnel junctions with Fe-based leads in empirically corrected density functional theory

The minority-spin Fe/MgO interface states are at the Fermi level in density functional theory (DFT), but experimental evidence and GW calculations place them slightly higher in energy. This small shift can strongly influence tunneling magnetoresistance (TMR) in junctions with a thin MgO barrier and its dependence on the concentration of Co in the electrodes. Here, in this study, an empirical potential correction to DFT is introduced to shift the interface states up to match the tunnel spectroscopy data. With this shift, TMR in Fe/MgO/Fe junctions exceeds 800% and 3000% at 3 and 4 monolayers (ML) of MgO, respectively. We further consider the effect of alloying of the Fe electrodes with up to 30% Co or 10% V, treating them in the coherent potential approximation (CPA). Alloying with Co broadens the interface states and brings a large incoherent minority-spin spectral weight to the Fermi level. Alloying with V brings the minority-spin resonant states close to the Fermi level. However, in both cases the minority-spin spectral weight at the Fermi level resides primarily at the periphery of the Brillouin zone, which is favorable for spin filtering. Using convolutions of k II -resolved barrier densities of states calculated in CPA, it is found that TMR is strongly reduced by alloying with Co or V but still remains above 500% at 4 ML of MgO up to 30% of Co or 5% V. At 5 ML, the TMR increases above 1000% in all systems considered. However, while TMR declines sharply with increasing bias up to 0.2 eV in the tunnel junctions with pure Fe leads, it remains almost constant up to 0.5 eV if leads are alloyed with Co.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2020

Structure–activity relationship-based chemical classification of highly imbalanced Tox21 datasets

Abstract The specificity of toxicant-target biomolecule interactions lends to the very imbalanced nature of many toxicity datasets, causing poor performance in Structure–Activity Relationship (SAR)-based chemical classification. Undersampling and oversampling are representative techniques for handling such an imbalance challenge. However, removing inactive chemical compound instances from the majority class using an undersampling technique can result in information loss, whereas increasing active toxicant instances in the minority class by interpolation tends to introduce artificial minority instances that often cross into the majority class space, giving rise to class overlapping and a higher false prediction rate. In this study, in order to improve the prediction accuracy of imbalanced learning, we employed SMOTEENN, a combination of Synthetic Minority Over-sampling Technique (SMOTE) and Edited Nearest Neighbor (ENN) algorithms, to oversample the minority class by creating synthetic samples, followed by cleaning the mislabeled instances. We chose the highly imbalanced Tox21 dataset, which consisted of 12 in vitro bioassays for > 10,000 chemicals that were distributed unevenly between binary classes. With Random Forest (RF) as the base classifier and bagging as the ensemble strategy, we applied four hybrid learning methods, i.e., RF without imbalance handling (RF), RF with Random Undersampling (RUS), RF with SMOTE (SMO), and RF with SMOTEENN (SMN). The performance of the four learning methods was compared using nine evaluation metrics, among which F 1 score, Matthews correlation coefficient and Brier score provided a more consistent assessment of the overall performance across the 12 datasets. The Friedman’s aligned ranks test and the subsequent Bergmann-Hommel post hoc test showed that SMN significantly outperformed the other three methods. We also found that a strong negative correlation existed between the prediction accuracy and the imbalance ratio (IR), which is defined as the number of inactive compounds divided by the number of active compounds. SMN became less effective when IR exceeded a certain threshold (e.g., > 28). The ability to separate the few active compounds from the vast amounts of inactive ones is of great importance in computational toxicology. This work demonstrates that the performance of SAR-based, imbalanced chemical toxicity classification can be significantly improved through the use of data rebalancing.

Idakwo, Gabriel↗

DOE OSTI2025

Fiscal Year 2025 Software Quality Assurance Activities for the ARC Software

The continued goal of the ARC SQA project in the Advanced Reactor Technologies program of DOE is to resolve the QA gaps for the ARC software that limit, or prevent, commercialization of the software for industry users. This project started in earnest in fiscal year 2023 which saw the entire code system moved from a SVN repository to a GitLab repository and an associated software quality assurance plan (SQAP) developed and ratified. Most of the QA gaps in the ARC software were identified in collaboration with industry partners and work begin in fiscal year 2023 and continued through 2024 and 2025. The continuous integration testing was extended to RCT, DASSH, and SE2ANL. Minor changes were required to the original continuous integration methodology to make this happen. When full confidence in the methodology is complete, a report will be created to detail the automated regression testing methodology and minor reports will be created to detail the tolerance settings that have been applied to the output for each ARC code. The primary documentation that is missing includes user manuals, user guides, software verification reports, and code coverage assessments. The DASSH, SE2ANL, and SE2RCT manuals were completed this fiscal year. A review of the SE2ANL software identified that it is unrealistic to include updated correlations or different geometry models and it was scheduled for deprecation in favor of DASSH. The SE2ANL manual is essential for SE2RCT as they are similar but quite different in purpose. The only piece of software missing a manual consistent with the source code is NUBOW-3D which is a focus of the coming year. The code coverage report for DIF3D was updated and code coverage reports were created for REBUS, RCT, PERSENT, GAMSRC, and DASSH. Minor coverage issues were identified for all of these pieces of software which did not prevent the work done to transition them to the OneAPI compiler. Because SE2ANL was scheduled for deprecation, it was not transitioned, but it was successfully tested with the OneAPI compiler. This leaves SE2RCT and NUBOW-3D as the only pieces of software not transitioned to OneAPI and further work is required to get SE2RCT to work properly. The SE2RCT software transition will begin early next year while the NUBOW-3D software requires a manual before it can begin. Software verification work has been completed for DIF3D, REBUS, GAMSOR, GAMSRC, VARPOW, EvaluateFlux, and SUMMAR. The PERSENT software verification work was completed this year which was somewhat delayed because of unexpected bugs in the software. The PERSENT manual was updated to detail some of the issues and discuss the bowing reactivity worth feature added in the previous fiscal year. The RCT, DASSH, SE2RCT, and NUBOW-3D software are the only maintained pieces of software without verification reports. The software verification work for DASSH will be a focus in the upcoming fiscal year and it is hoped that some of the test cases created can serve as verification tests for SE2RCT. The NUBOW-3D work will begin when the manual and requirements report are completed. Only minor industry partner software development funds were provided this year. The DASSH software was updated to handle general axial geometry for each assembly and the NUBOW-3D software was updated to incorporate a new input format and better output. Overall progress on resolving the QA gaps has been good this year.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2025

Fiscal Year 2025 Software Quality Assurance Activities for the ARC Software

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Dilute alloy catalysts for electrochemical CO 2 reduction

A product includes a dilute alloy catalyst for carbon dioxide reduction. The catalyst has a majority component and at least one minority component. The majority component is present in a concentration of greater than 90 atomic percent of the catalyst. The majority component is copper, and each minority component is selected from the group consisting of: a transition metal, a main group metal, a lanthanide, and a semimetal. A method includes forming a product on a cathode. The product includes a dilute alloy catalyst for carbon dioxide reduction. The catalyst has a majority component and at least one minority component. The majority component is present in a concentration of greater than 90 atomic percent of the catalyst. The majority component is copper, and each minority component is selected from the group consisting of: a transition metal, a main group metal, a lanthanide, and a semimetal.

Biener, Juergen↗

DOE OSTI2021

Economizing on Precious Metals in Three-Way Catalysts: Thermally Stable and Highly Active Single-Atom Rhodium on Cera for NO Abatement under Dry and Industrially Relevant Conditions

We show for the first time that atomically dispersed Rh cations on ceria, prepared via high-temperature atom trapping synthesis, are the active species for (CO+NO) reaction. This provides a direct link with the organometallic homogeneous Rh(I) complexes capable of catalyzing dry (CO+NO) reaction but without the stability concern. In particular, thermally stable Rh cations in 0.1wt% Rh1/CeO2 achieve full NO conversion with a TOF of ~ 330 hr-1 per Rh atom at 120 °C. Under dry conditions, the main product above 100 °C is N2 with N2O being the minor product. The presence of water promotes low-temperature activity of 0.1wt% Rh1/CeO2 starting at 50 °C with full NO conversion at ~120 °C. In the case with the wet stream, however, ammonia and nitrogen are the main products with only minor N2O amounts. NH3 formation at such low temperatures is attractive because of the potential to use this as a passive SCR system. Because of the uniformity of Rh ions on the support, we are able to observe the intermediates of (CO+NO) reaction via infrared measurements on Rh cations on zeolite and ceria. Furthermore, we show that ammonia formation correlates with the WGS activity of the material and thus, rhodium hydride Rh-H species are involved in this reaction: we detect Rh(CO)Hx species on ceria using isotopic IR measurements. These findings provide new mechanistic understanding for the catalytically active species in TWC catalysis and open up a new avenue for the synthesis of novel emissions control catalysts with 100% atom economy of ultra-expensive precious metals such as Rh.

Khivantsev, Konstantin↗

DOE OSTI2023

Deep reinforcement learning for class imbalance fault diagnosis of equipment in nuclear power plants

In equipment fault diagnosis in nuclear power plants, there may be far more samples in one class (e.g., a health state) than in another class (e.g., a fault state). The distribution of data in each class is highly skewed. Most machine learning algorithms are suitable for balanced training datasets. When faced with imbalanced samples, these algorithms tend to provide good identification for the majority classes and bias for the minority classes. However, the misclassification of minority classes can lead to high costs. To address the above problem, this paper develops a deep reinforcement learning-based diagnosis method that models fault diagnosis as a sequential decision-making process. At each time step, the agent receives the state of the environment represented by the training samples and then takes a diagnosis action guided by a policy. If the action is correct/incorrect, the agent receives a positive/negative reward. The reward for minority classes is higher than that for majority classes. The agent’s goal is to obtain as many cumulative rewards as possible in the process, i.e., to identify the sample as correctly as possible. Six demonstration scenarios are constructed, depending on the selected fault datasets and the designed model structures. Experiments show that the proposed method achieves a higher weighted-averaged F1 score than the classical supervised learning method in most cases of class imbalance. Finally, the proposed method has potential applications in the field of class imbalance fault diagnosis of equipment in nuclear power plants.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2021

An insight on the effect of sodium and silicon on microstructure and crystallography of high alumina cements

In the present study the influence of minor elements (Na{sub 2}O and SiO{sub 2}) on the mineralogy, chemistry and microstructure of High Alumina Cements (HACs) has been investigated. HACs have several advantages respected to Ordinary Portland Cement (OPC) but the shortage of Al-rich raw materials represents a limiting factor: re-use of Al-rich waste as raw material represents a solution but it will add minor elements to the raw meal that could change HACs properties. For the first time, four commercial HACs, doped with sodium and silicon, and one synthetic HAC, only highly doped in sodium, were studied through a multidisciplinary approach by combining conventional and unconventional analytical techniques. Results highlighted that (i) sodium and silicon were mainly incorporated in a sodium-rich phase (Na-phase, NCA{sub 2}, Na{sub 1.9}CaAl{sub 3.9}Si{sub 0.1}O{sub 8}), (ii) no minor phases such as gehlenite and/or mayenite occurred, and (iii) CA (CaAl{sub 2}O{sub 4}) and CA{sub 2} (CaAl{sub 4}O{sub 7}) revealed a limited ionic substitution.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Community vulnerability is the key determinant of diverse energy burdens in the United States

Low-income households generally experience a high energy burden; however, the factors influencing energy burdens are beyond socio-economics. This study explores the relationships between the multidimensionality of community vulnerability factors and energy burden across multiple geospatial levels in the United States. Our study found the distribution of energy burden in 2020 showed a great deal of variety, ranging from a minimum of 2.93 % to a maximum of 30.45 % across 3142 counties. The results of non-spatial and spatial regressions showed that the vulnerability ranks of socioeconomic, household composition and disability, minority and language, household type and transportation, and COVID mortality rate are significant predictors of energy burdens at the national level. However, at the regional level, only socioeconomic, minority and language significantly influence energy burdens. Minority and language negatively impact energy burdens except for the South East-Central region. Additionally, our analyses highlight the need to consider community vulnerability indicators' spatial homogeneity and heterogeneity. At the national level, only the epidemiological factors index is a spatially homogeneous predictor; on the regional and state level, the spatially homogeneous predictors such as socioeconomic status, household composition and disability, and household type and transportation vary by region. Such a region-sensitive relationship between energy burden and the predictors indicates spatial heterogeneity. Here this study suggests policy recommendations through the lens of the multidimensionality of community vulnerability factors. Implementing flexible national energy policies while making particular energy assistance policies for the vulnerable population at the regional or state levels is essential.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Engineering defect energy landscape of CoCrFeNi high-entropy alloys by the introduction of additional dopants

The concept of high-entropy alloys (HEAs) focusing on tuning the overall chemical complexity represents a novel alloy design strategy. In contrast, alloying of a metallic matrix with minor doping elements with limited and localized tunability has been a common practice to improve material performance. Combining the idea of globally engineering defect energy landscape in HEAs and the localized doping strategy in dilute alloys, in this work, we explore doping effects of minor elements in a HEA matrix to further enhance the overall and localized chemical tunability, aiming to improve its irradiation resistance. Specifically, we study the influence of minor Al, Cu, Ti, and Pd substitutional doping elements on defect energetics in a CoCrFeNi model HEA based on density-functional theory (DFT) calculations. The DFT results indicate that the formation and migration energies of vacancies can be strongly influenced when a dopant is introduced at the first nearest neighbor shells around a vacancy. On the other hand, interstitial energetics are only slightly affected. Among the four elements, Ti and Pd generally decrease vacancy formation energies and increase vacancy migration energies more significantly than Al and Cu. The doping effects become more pronounced when the concentration of the substitutional dopants increases. Based on the energy distributions obtained from DFT, we build a kinetic Monte Carlo (kMC) model to assess the impact of dopants on vacancy-mediated diffusivity in the doped HEAs. Our results suggest that Ti and Pd can lower the tracer diffusivity in the considered HEAs and act as trapping sites, whereas Cu may enhance the atomic transport. This work indicates that substitutional doping in HEAs is an effective strategy in metallurgy to further tune the defect and transport properties of complex alloys.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

Testing fast reactor fuels in a thermal reactor: Comparison of transmutation metallic fuel alloys behavior by scanning electron microscopy

To optimize nuclear waste repository performance, the destruction of minor actinide elements, particularly Np and Am, in a neutron fast spectrum reactor is possible by incorporating these elements into nuclear fuel. Evaluating the performance of minor actinide containing fuel is of paramount importance to enabling this technology. However, such a task is challenging without an available domestic fast spectrum test reactor. A comparison of fuel performance tested in an available domestic thermal reactor at the Idaho National Laboratory, the Advanced Test Reactor, and in a fast spectrum reactor in France (Phénix) is presented here in this study. This study evaluates the capability of using a cadmium shrouded test position to mimic the power profile along the fuel radius present in fast spectrum reactors so that thermally driven phenomenon (e.g., constituent redistribution) can be evaluated in a thermal reactor and determined to be prototypical of a fast reactor. Thus, optical microscopy and scanning electron microscopy has been performed on irradiated 35U-29Pu-4Am-2Np-30Zr fuel samples (where the number preceding the element is the weight percent concentration) from the two mentioned reactors that present similar irradiation temperatures and power conditions. The results indicate that fuel performance phenomena are reproducible in the two irradiation conditions. The redistribution of Zr occurred in the same manner for the two samples. Similar partitioning of U-Pu-Zr phases was observed, and the behavior of Am was similar in the analyzed specimens. Finally, the overall microstructure evolution seems not to be affected by minor actinides addition compared to expected behavior of conventional U-19Pu-10Zr ternary metal fuels for both specimens. Slight differences in fuel cladding chemical interaction were, however, observed. This difference is likely driven by difference in cladding composition rather than irradiation conditions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

RSPECT: A PROSPECT-based model incorporating the real structure of rice leaves

Radiative transfer models (RTMs) describe how light is absorbed, scattered, and transmitted within leaves by simulating mechanistic light propagation processes. The PROSPECT model is based on measurable parameters (the leaf biochemical content) and a non-measurable parameter (the leaf anatomical structure represented by the leaf structure parameter (N)). The effect of N on the optical properties of leaves has been investigated through a number of local and global sensitivity analyses. Other studies have directly evaluated the effect of the leaf anatomical structure on spectral reflectance, particularly in the near infrared region. However, the relationship between N and the anatomical structure is unclear. Here, in this study, we leveraged eLeaf, a ray tracing-based 3D rice leaf simulator, to establish relationships between leaf anatomical features and spectral properties, enabling us to replace N in the PROSPECT-4 model with measurable leaf anatomical parameters and develop the RSPECT model. The leaf thickness at minor vein, leaf thickness at bulliform cells, mesophyll thickness at minor vein, and distance between two minor veins could be used to predict N effectively. The RSPECT model achieved spectral simulation accuracy comparable to PROSPECT-4 and was more suitable for parameter inversion of the physical and chemical properties of rice leaves, with relative root mean square errors of 7.4% for chlorophyll content, 5.6% for equivalent water thickness, and 7.5% for dry matter content. In conclusion, RSPECT improves radiative transfer modeling by integrating measurable anatomical features and provides a framework for extending this approach to other vegetation types.

hyperspectral↗

DOE OSTI2020

Evaluating the Utility of Permethylated Polysaccharide Solution NMR Data for Characterization of Insoluble Plant Cell Wall Polysaccharides

Plant cell wall polysaccharide analysis encompasses the utilization of a variety of analytical tools, including gas and liquid chromatography, mass spectrometry (MS), and nuclear magnetic resonance (NMR) spectroscopy. These methods provide complementary data, which enable confident structural proposals of the many complex polysaccharide structures that exist in the complex matrices of plant cell walls. However, cell walls contain fractions of varying solubilities, and a few techniques are available that can analyze all fractions simultaneously. We have discovered that permethylation affords the complete dissolution of both soluble and insoluble polysaccharide fractions of plant cell walls in organic solvents such as chloroform or acetonitrile, which can then be analyzed by a number of analytical techniques including MS and NMR. In this work, NMR structure analysis of 10 permethylated polysaccharide standards was undertaken to generate chemical shift data providing insights into spectral changes that result from permethylation of polysaccharide residues. This information is of especial relevance to the structure analysis of insoluble polysaccharide materials that otherwise are not easily investigated by solution-state NMR methodologies. The preassigned NMR chemical shift data is shown to be vital for NMR structure analysis of minor polysaccharide components of plant cell walls that are particularly difficult to assign by NMR correlation data alone. With the assigned chemical shift data, we analyzed the permethylated samples of destarched, alcohol-insoluble residues of switchgrass and poplar by two-dimensional NMR spectral profiling. Thus, we identified, in addition to the major polysaccharide components, two minor polysaccharides, namely, <5% 3-linked arabinoxylan (switchgrass) and <2% glucomannan (poplar). In particular, the position of the arabinose residue in the arabinoxylan of the switchgrass sample was confidently assigned based on chemical shift values, which are highly sensitive to local chemical environments. Furthermore, the high resolution afforded by the 1H NMR spectra of the permethylated switchgrass and poplar samples allowed facile relative quantitative analysis of their polysaccharide composition, utilizing only a few milligrams of the cell wall material. As a result, the concepts herein developed will thus facilitate NMR structure analysis of insoluble plant cell wall polysaccharides, more so of minor cell wall components that are especially challenging to analyze with current methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Interplay Between Strain and Thickness on the Effective Carrier Lifetime of Buffer-Mediated Epitaxial Germanium Probed by the Photoconductance Decay Technique

We report contactless effective minority carrier lifetime of epitaxially grown unstrained and in-plane <110> biaxially tensile-strained (001) germanium (..epsilon..-Ge) epilayers measured using microwave-reflectance photoconductance decay measurements. Strained Ge epilayers were grown using InxGa1-xAs linearly graded buffers on (001) GaAs substrates. Using homogeneous excitation of unstrained Ge epilayers, thickness-dependent separation of minority carrier lifetime components under low injection conditions yielded a bulk lifetime of 114 +/- 2 ns and low surface recombination velocity of 21.3 +/- 0.04 cm/s. More notably, an effective minority carrier lifetime of >100 ns obtained from sub-50 nm 1.6% tensile-strained Ge epilayers showed no degradation relative to the unstrained counterpart. Detailed material characterization using X-ray diffractometry revealed successful strain transfer of 0.61 and 0.89% to the Ge epilayers via InxGa1-xAs metamorphic buffers and confirms pseudomorphic growth. Lattice coherence observed at the e-Ge epilayer and InxGa1-xAs buffer heterointerfaces via transmission electron microscopy substantiates the prime material quality achieved. The relatively high carrier lifetimes achieved are an indicator of excellent material quality and provide a path forward to realize low-threshold Ge laser sources.

bulk lifetime↗

DOE OSTI2022

An all optical approach for comprehensive in-operando analysis of radiative and nonradiative recombination processes in GaAs double heterostructures

We demonstrate an all optical approach that can surprisingly offer the possibility of yielding much more information than one would expect, pertinent to the carrier recombination dynamics via both radiative and nonradiative processes when only one dominant deep defect level is present in a semiconductor material. By applying a band-defect state coupling model that explicitly treats the inter-band radiative recombination and Shockley–Read–Hall (SRH) recombination via the deep defect states on an equal footing for any defect center occupation fraction, and analyzing photoluminescence (PL) as a function of excitation density over a wide range of the excitation density (e.g., 5–6 orders in magnitude), in conjunction with Raman measurements of the LO-phonon plasmon (LOPP) coupled mode, nearly all of the key parameters relevant to the recombination processes can be obtained. They include internal quantum efficiency (IQE), minority and majority carrier density, inter-band radiative recombination rate (W r ), minority carrier nonradiative recombination rate (W nr ), defect center occupation fraction (f), defect center density (N t ), and minority and majority carrier capture cross-sections (σ t and σ tM ). While some of this information is thought to be obtainable optically, such as IQE and the W r /W nr ratio, most of the other parameters are generally considered to be attainable only through electrical techniques, such as current-voltage (I-V) characteristics and deep level transient spectroscopy (DLTS). Following a procedure developed herein, this approach has been successfully applied to three GaAs double-heterostructures that exhibit two distinctly different nonradiative recombination characteristics. The method greatly enhances the usefulness of the simple PL technique to an unprecedented level, facilitating comprehensive material and device characterization without the need for any device processing.

14 SOLAR ENERGY↗

DOE OSTI2025

Structure and mechanism of biosynthesis of Streptococcus mutans cell wall polysaccharide

Streptococcus mutans, the causative agent of human dental caries, expresses a cell wall attached Serotype c-specific Carbohydrate (SCC) that is critical for cell viability. SCC consists of a polyrhamnose backbone of →3)α-Rha(1 → 2)α-Rha(1→ repeats with glucose (Glc) side-chains and glycerol phosphate (GroP) decorations. This study reveals that SCC has one predominant and two more minor Glc modifications. The predominant Glc modification, α-Glc, attached to position 2 of 3-rhamnose, is installed by SccN and SccM glycosyltransferases and is the site of the GroP addition. The minor Glc modifications are β-Glc linked to position 4 of 3-rhamnose installed by SccP and SccQ glycosyltransferases, and α-Glc attached to position 4 of 2-rhamnose installed by SccN working in tandem with an unknown enzyme. Both the major and the minor β-Glc modifications control bacterial morphology, but only the GroP and major Glc modifications are critical for biofilm formation.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Central star formation in double-peak, gas-rich radio galaxies

The respective contributions of gas accretion, galaxy interactions, and mergers to the mass assembly of galaxies, as well as the evolution of their molecular gas and star-formation activity are still not fully understood. In a recent work, a large sample of double-peak (DP) emission-line galaxies have been identified from the SDSS. While the two peaks could represent two kinematic components, they may be linked to the large bulges that their host galaxies tend to have. Star-forming DP galaxies display a central star-formation enhancement and have been discussed as compatible with a sequence of recent minor mergers. In order to probe merger-induced star-formation mechanisms, we conducted observations of the molecular-gas content of 35 star-forming DP galaxies in the upper part of the main sequence (MS) of star formation (SF) with the IRAM 30 m telescope. Including similar galaxies 0.3 dex above the MS and with existing molecular-gas observations from the literature, we finally obtained a sample of 52 such galaxies. We succeeded in fitting the same kinematic parameters to the optical ionised- and molecular-gas emission lines for ten (19%) galaxies. We find a central star-formation enhancement resulting most likely from a galaxy merger or galaxy interaction, which is indicated by an excess of gas extinction found in the centre. This SF is traced by radio continuum emissions at 150 MHz, 1.4 GHz, and 3 GHz, all three of which are linearly correlated in log with the CO luminosity with the same slope. The 52 DP galaxies are found to have a significantly larger amount of molecular gas and longer depletion times, and hence a lower star-formation efficiency, than the expected values at their distance of the MS. The large bulges in these galaxies might be stabilising the gas, hence reducing the SF efficiency. This is consistent with a scenario of minor mergers increasing the mass of bulges and driving gas to the centre. We also excluded the inwards-directed gas migration and central star-formation enhancement as the origin of a bar morphology. Hence, these 52 DP galaxies could be the result of recent minor mergers that funnelled molecular gas towards their centre, triggering SF, but with moderate efficiency.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Molecular beam epitaxy growth and optoelectronic properties of droplet-free lattice-matched GaInAsSbBi on GaSb with wavelength extension exceeding 5 μ m

GaInAsSbBi alloys are grown lattice-matched on GaSb by molecular beam epitaxy demonstrating smooth surface morphologies, >5 μm wavelength photoluminescence emission, and minority carrier lifetimes >1 μs. At a growth temperature of 400 °C, the Ga flux is systematically increased and the Bi flux systematically decreased to identify GaInAsSbBi growth conditions that yield smooth droplet-free surface morphologies. The minority carrier lifetime is evaluated using time-resolved photoluminescence, where it is observed that GaInAsSbBi samples exhibit minority carrier lifetimes comparable to their Bi-free GaInAsSb counterparts, on the order of 1.5–2 μs. The bandgap and Urbach energy are evaluated from steady-state photoluminescence to gain insight into the impact of the incorporated Bi. Coupled with Rutherford backscattering spectrometry measurements of the Bi mole fraction, bandgap reduction rates of 97 meV/% Bi in InAsSbBi and 150 meV/% Bi in GaInAsSbBi are observed, significantly higher than previous evaluations in InAsSbBi (35–55 meV/% Bi). Detailed comparisons of the Bi mole fraction, bandgap energy, and Urbach energy indicate that the bandgap reduction potential in this alloy system is inhibited by the formation of Bi clusters; however, the inclusion of Ga in the quinary alloy is effective in suppressing Bi's tendency to incorporate in clusters for Ga mole fractions >9%, maximizing the bandgap reduction per unit Bi and overall optoelectronic quality.

Atomic force microscopy↗