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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

High-throughput and data-driven search for stable optoelectronic AMSe 3 materials

The rapid advancement in emerging optoelectronic technologies demands highly efficient, affordable, and ecofriendly materials. In this context, ternary chalcogenides, especially ternary selenides, show early promise as a material class due to their stability and remarkable electronic, optical, and transport properties. In this work, we integrate first-principles-based high-throughput computations with machine learning (ML) techniques to predict the thermodynamic stability and optoelectronic properties of 920 valency-satisfied selenide compounds. Through investigating polymorphism, our study reveals the edge-sharing orthorhombic Pnma phase (NH 4 CdCl 3 -type) as the most stable structure for most ternary selenides. High-fidelity supervised ML models are trained and tested to accelerate stability and band gap predictions. These data-driven models pin down the most influential features that dominantly control key material characteristics. The multistep high-throughput computations identify the ternary selenides with optimal direct band gaps, light carrier masses, and strong optical absorption edges. The extensive materials screening considering phase stability, toxicity, and defect tolerance, finally identifies the seven most suitable candidates for photovoltaic applications. Two of these final compounds, SrZrSe 3 and SrHfSe 3 , have already been synthesized in a single-phase form, with the latter showing an optically suitable band gap, aligning well with our findings. The non-adiabatic molecular dynamics reveal sufficiently long photoexcited charge carrier lifetimes (on the order of nanoseconds) in some of these selected selenide materials, indicating their exciting characteristics. Overall, our study suggests a robust in silico framework that can be extended to screen large datasets of various material classes for identifying promising photoactive candidates.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Influence of shape on crystal structure and optical properties of heterocyclic conjugated molecules

Organic optoelectronics are increasingly important due to their tunablilty, flexibility, and solution processability. Tuning optical properties of these materials as solids relies on the balance of weak non-covalent interactions that dictate crystal structure, but are difficult to predict. Our research aims to improve our understanding of how electrostatic interactions can direct and facilitate intramolecular interactions that dictate emergent properties of crystalline materials. This paper focuses on exploring how multi-fused thiophene ring systems that are popular in modern organic optoelectronic materials impact intramolecular interactions, while also investigating the role of molecular shape. In these examples, the shape of heterocyclic systems correlate with the crystal structures: while the bent heterocyclics show no discrete and discernable intramolecular interactions, those with bent shapes interact cofacially with one of the electron poor ArF pendants by twisting the arylene ethynylene backbone. Two of the control molecules, which bear non-fluorinated benzyl ester substituents, show intramolecular edge-face interactions, and several of these molecules show clear polymorphic behavior. Furthermore, these findings further our understanding of how discrete interactions can be altered not only by electrostatics, but also by shape, allowing for increasingly nuanced control over the crystal structures and optical properties of optoelectronic materials.

Guzmán, Elisa↗
DOE OSTI2025

Boron monoxide is a one-dimensional polymer

It was recently reported that boron monoxide (BO) is formed through the cross-linking of B 4 O 2 structural building units. Multiple theoretical phases agree with this description. Using pycnometry, multidimensional 17 O NMR spectroscopy, and plane-wave DFT calculations we determined the likely polymorph to be a one-dimensional polymer initially proposed in 1955.

Thuma, Joseph F. [Iowa State Univ., Ames, IA (Unit↗
DOE OSTI2026

High-pressure neutron powder diffraction study of an arsenolite deuterium inclusion compound: structure and formation kinetics

High-pressure variable-temperature neutron powder diffraction was employed to investigate the synthesis and structural properties of arsenolite (As 4 O 6 ), a cubic arsenic( III ) oxide polymorph, and its inclusion compound with deuterium. The compound forms with the stoichiometry As 4 O 6 ·2D 2 , consistent with earlier findings. At 295 K and 1.96(2) GPa, D 2 molecules occupy the 16c site (0, 0, 0) and are aligned along the <111> direction. The diffraction data suggest that the D 2 molecules at this site become rotationally disordered upon decompression to 0.78(2) GPa at 120 K, while no occupancy is observed at the 8a position (⅛, ⅛, ⅛) under any of the studied conditions. The kinetic data of the high-pressure inclusion compound synthesis at 1.56(2) and 1.96(2) GPa were analyzed using the Avrami model. The Avrami exponent, 0.135(16), remains invariant with pressure, demonstrating that the reaction topochemistry is unaffected by compression. Similarly, the reaction rates, 0.29(3) and 0.23(3) min −0.135 at 1.56(2) and 1.96(2) GPa, respectively, exhibit negligible pressure dependence and suggest a surprisingly low activation volume of 1.6 cm 3 mol −1 for the reaction. These results provide detailed insight into the structural dynamics and kinetics of deuterium inclusion in arsenolite under high pressure.

Guńka, Piotr A. [Warsaw University of Technology (↗
DOE OSTI2025

Alloying multiple halide perovskites on the same sublattice in search of stability and target band gaps

Single-component halide perovskites (HPs) rarely satisfy all the necessary criteria for optoelectronic applications, such as achieving an optimal band gap while maintaining high chemical and structural stability. Alloying halide perovskites has emerged as a promising strategy, not only to enhance stability but also to fine-tune their electronic and optical properties. In this work, we explore multiple degrees of freedom in alloy design, considering different substitution sublattices sites (A, B, or X in ABX3 perovskites), various chemical species (isovalent and hetero-valent elements), and multi-component compositions on a given sublattice. Using first-principles calculations based on density functional theory (DFT), we investigate how compositional variations influence the electronic (band gap) and structural properties (mixing enthalpy) of HP alloys. Our approach employs the polymorphous cell model, allowing full local relaxation which breaks local symmetry while preserving global cubic symmetry—an essential framework for accurately modeling HPs. Our results reveal that X-site mixing (halogen substitution) primarily affects the valence band maximum, allowing target band gap engineering. Additionally, variations in halogen radii introduce internal strain through octahedral distortions, influencing the mixing enthalpy. A-site substitution, while not directly contributing to the band edge states, modifies structural stability via volume effects, indirectly impacting the band gap. B-site alloying plays a dominant role in band gap modulation, leading to either positive or negative band gap bowing. Specifically, isovalent B-site mixing (Sn–Pb) induces strong positive bowing, where the alloy band gap is smaller than the average gap of parent compounds, whereas hetero-valent mixing (Cd–Pb) results in pronounced negative bowing. As an aside, we investigate the competition between the excess energy of disordered alloys vs. that of long-range ordered double perovskites of the same compositions, seeking examples of ordered phases emerging from disordered alloys. Furthermore, our findings provide fundamental insights into the electronic and structural behavior of HP alloys, offering valuable design principles for the development of stable and efficient materials for next-generation photovoltaic and optoelectronic devices.

14 SOLAR ENERGY↗
DOE OSTI2025

Advanced spectroscopic studies of (PPh 4 ) 2 [Co(N 3 ) 4 ], a field-induced single-ion magnet

The high-spin Co II complex (PPh 4 ) 2 [Co(N 3 ) 4 ] (Co-N 3 )has been investigated using advanced spectroscopic techniques [far-IR magneto-spectroscopy (FIRMS), high-frequency and high-field EPR (HFEPR), and inelastic neutron scattering (INS)] to study its zero-field-splitting (ZFS), giving spin-Hamiltonian (SH) parameters. The analysis of multi-frequency HFEPR reveals the easy-axis anisotropy with a D value of −10.39(5) cm −1 and a rhombic ratio (E/D) of 0.21(1). The magnetic properties have also been probed by direct-current (DC) magnetometry, suggesting minor differences in anisotropy from the previously reported polymorph (Co-N 3 ′). Ligand-field theory (LFT) analysis indicates that the structures of Co-N 3 and Co-N 3 ′ are closer to D 2d symmetry than other symmetries considered. Alternate-current (AC) susceptibility reveals slow magnetic relaxation under an applied field, indicating that Co-N 3 is a field-induced single-ion magnet (SIM). Here, while both Co-N 3 and Co-N 3 ′ were studied by DC magnetometry, one unusual aspect of the current work on Co-N 3 is that advanced spectroscopies HFEPR, FIRMS, and INS were used to directly observe transitions between ZFS split states, giving accurate SH parameters.

Hand, Adam T. [Univ. of Tennessee, Knoxville, TN (↗
DOE OSTI2026

Structure prediction of porous organic crystals

In this work, we explore the possibility of applying automated crystal structure prediction to reproduce the experimentally identified metastable porous polymorphs. Using our recently developed High-Throughput Organic Crystal Structure Prediction ( HTOCSP ) framework, we conducted a systematic study on five representative organic crystalline systems including hydrogen-bonded frameworks (HOFs), featured by the presence of significant porosity, in conjunction with different choices of energy models from classical, machine learning force fields, tight binding to density functional theory. Our results suggest that the current structure generation framework, with careful selection of symmetry conditions, is likely to generate rather complex and abundant metastable crystal candidates for porous crystals. In conjunction with the recent advance in universal machine learning force fields, it becomes possible to identify experimental structures as the energetically favorable candidates from a simple energy versus density analysis, thus paving the way for computational design of complex porous materials with the target systems prior to the experimental synthesis and characterization.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Population structure limits the use of genomic data for predicting phenotypes and managing genetic resources in forest trees

There is overwhelming evidence that forest trees are locally adapted to climate. Thus, genecological models based on population phenotypes have been used to measure local adaptation, infer genetic maladaptation to climate, and guide assisted migration. However, instead of phenotypes, there is increasing interest in using genomic data for gene resource management. We used whole-genome resequencing and common-garden experiments to understand the genetic architecture of adaptive traits in black cottonwood. We studied the potential of using genome-wide association studies (GWAS) and genomic prediction to detect causal loci, identify climate-adapted phenotypes, and inform gene resource management. We analyzed population structure by partitioning phenotypic and genomic (single-nucleotide polymorphism) variation among 840 genotypes collected from 91 stands along 16 rivers. Most phenotypic variation (60 to 81%) occurred among populations and was strongly associated with climate. Population phenotypes were predicted well using genomic data (e.g., predictive abilityr> 0.9) but almost as well using climate or geography (r> 0.8). In contrast, genomic prediction within populations was poor (r< 0.2). We identified many GWAS associations among populations, but most appeared to be spurious based on pooled within-population analyses. Hierarchical partitioning of linkage disequilibrium and haplotype sharing suggested that within-population genomic prediction and GWAS were poor because allele frequencies of causal loci and linked markers differed among populations. Given the urgent need to conserve natural populations and ecosystems, our results suggest that climate variables alone can be used to predict population phenotypes, delineate seed zones and deployment zones, and guide assisted migration.

Science & Technology - Other Topics↗
DOE OSTI2025

Multistage nucleation pathway in LiF molten salt mirrors the crystal–melt interface structure

Despite over a century of studies, fundamental questions remain about the processes governing crystal nucleation from melts or solutions. Research over the past three decades has presented mounting evidence for kinetic pathways of crystal nucleation that are more complex than envisioned by the simplest forms of classical theory. Such observations have been presented for colloidal and elemental systems with covalent and metallic bonding. Despite the technological and geochemical importance of molten salts, similar studies for these ionically bonded systems are currently lacking. Here we develop a machine learning interatomic potential for a model ionic system: LiF. The potential features quantum-level accuracy for both liquid and multiple solid polymorphs over wide temperature and pressure ranges and accurately reproduces experimentally measured properties. Thanks to the efficiency of the potential, which enables microsecond-scale molecular dynamics simulations, induction times for nucleation of LiF solids from their melts are computed over a range of undercoolings. With the aid of a set of robust local order parameters established here, the simulations reveal that homogeneous crystal nucleation in undercooled melts preferentially initiates from liquid regions showing slow dynamics and high bond orientational order simultaneously, and the second-shell order of both precritical nuclei and the surface of postcritical nuclei is dominated by hexagonal close packing and body-centered cubic local structure, even though the nucleus core is dominated by face-centered cubic structure corresponding to the stable rocksalt crystal structure. Finally, we establish a connection between the crystallization pathway and the equilibrium crystal-melt interface structure.

Applied Physical Sciences↗
DOE OSTI2025

Properties of different LLM-105 preparations

LLM-105 (2,6-diamino-3,5-dinitropyrazine-1-oxide) has been prepared at several different size quantities (~10–70 Kg) and not subjected to further purification, such as recrystallization. Chemical and physical properties were compared—small-scale safety testing (impact, friction, ESD), thermal (chemical reactivity, differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), one-dimensional time-to-explosion (ODTX)), morphological (particle-size distribution (PSD), scanning electron microscopy (SEM), powder x-ray diffraction (PXRD), skeletal density). Each preparation had similar properties to the other preparations except for PSD and PXRD. For PSD, all preparations exhibited a mono-modal distribution with a variation in median values from ~ 40 μm to over 80 μm. All PXRD values indicated the same morphology with minor variations in crystal orientations. Possible polymorphism was also observed in a few cases. SEM images and PXRD indicate all preparations to be diamond-type and X-type crystals with some twinning. Impact, friction, and ESD and thermal sensitivities values are consistent with these type of crystal habits as seen in vast literature studies.

Explosive characterization↗
DOE OSTI2024

Induced and natural variation affect traits independently in hybrid Populus

Abstract The genetic control of many plant traits can be highly complex. Both allelic variation (sequence change) and dosage variation (copy number change) contribute to a plant's phenotype. While numerous studies have investigated the effect of allelic or dosage variation, very few have documented both within the same system, leaving their relative contribution to phenotypic effects unclear. The Populus genome is highly polymorphic, and poplars are fairly tolerant of gene dosage variation. Here, using a previously established Populus hybrid F1 population, we assessed and compared the effect of natural allelic variation and induced dosage variation on biomass, phenology, and leaf morphology traits. We identified QTLs for many of these traits, but our results indicate limited overlap between the QTLs associated with natural allelic variation and induced dosage variation. Additionally, the integration of data from both allelic and dosage variation identifies a larger set of QTLs that together explain a larger percentage of the phenotypic variance. Finally, our results suggest that the effect of the large indels might mask that of allelic QTLs. Our study helps clarify the relationship between allelic and dosage variation and their effects on quantitative traits.

Guo, Weier (ORCID:0000000251789334)↗
DOE OSTI2025

MINE: maximally informative next experiment—toward a new GWAS experimental design and methodology

Abstract The computational methodology of Genome Wide Association Studies (GWAS) currently has several limitations: (i) the number of observations (rows) on a quantitative trait tends to be smaller than the number of single nucleotide polymorphisms (SNPs) (columns) in the design matrix; (ii) each SNP is usually modeled separately, failing to acknowledge interaction between each other (ie epistasis); (iii) there is implicit linkage disequilibrium (LD) between neighboring SNPs due to their linkage. To overcome these issues, we developed a tool that uses ensemble methods to fit mixed linear models to GWAS data, and these ensemble methods include the development of a new experimental design approach in GWAS, which uses the resultant models and data to select the next informative experiment over time. This new adaptive and staged approach for GWAS experimental design was developed and tested in a 3 yr adaptive model-guided discovery experiment against a fixed classical design. In Sorghum bicolor a total of 79, 86, and 78 accessions were tested in years 1, 2, and 3, respectively out of 343 accessions available in the Bioenergy Association Panel (BAP) each identified for 232,303 SNPs, 1 every 2–3 kb in the genomes. We demonstrated the feasibility of MINE enacted with 8 people in the field per year over 3 yr vs in 1 large classical design enacted with 20 people in 1 yr. The MINE results for chromosomal regions identified controlling dry weight were confirmed against results from previous sorghum GWAS experiments and 1 large classical design for the BAP panel.

Genetics & Heredity↗
DOE OSTI2025

Testing for the Genomic Footprint of Conflict Between Life Stages in an Angiosperm and Moss Species

Abstract The maintenance of genetic variation by balancing selection is of considerable interest to evolutionary biologists. An important but understudied potential driver of balancing selection is antagonistic pleiotropy between diploid and haploid stages of the plant life cycle. Despite sharing a common genome, sporophytes (2n) and gametophytes (n) may undergo differential or even opposing selection. Theoretical work suggests antagonistic pleiotropy between life stages can generate balancing selection and maintain genetic variation. Despite the potential for far-reaching consequences of gametophytic selection, empirical tests of its pleiotropic effects (neutral, synergistic, or antagonistic) on sporophytes are generally lacking. Here, we examined the population genomic signals of selection across life stages in the angiosperm Rumex hastatulus and the moss Ceratodon purpureus. We compared gene expression between life stages and sexes, combined with neutral diversity statistics and the analysis of the distribution of fitness effects. In contrast to what would be predicted under balancing selection due to antagonistic pleiotropy, we found that unbiased genes between life stages were under stronger purifying selection, likely explained by a predominance of synergistic pleiotropy between life stages and strong purifying selection on broadly expressed genes. In addition, we found that 30% of candidate genes under balancing selection in R. hastatulus were located within inversion polymorphisms. Our findings provide novel insights into the genome-wide characteristics and consequences of plant gametophytic selection.

Evolutionary Biology↗
DOE OSTI2026

MAL33 drives natural variation in maltose metabolism in Saccharomyces eubayanus

Maltose is one of the most abundant sugars in brewer’s wort, and its efficient utilization is critical for successful fermentation. However, maltose consumption varies naturally among Saccharomyces eubayanus strains isolated from different host trees, such as Quercus and Nothofagus. To identify the genetic determinants underlying these phenotypic differences, we performed bulk segregant analysis (BSA) and quantitative trait loci (QTL) mapping using an F 2 offspring derived from QC18 (Quercus-associated) and CL467.1 (Nothofagus-associated) strains. QTL mapping identified two significant genomic regions on subtelomeric loci of chromosomes V-R and XVI-L, each containing complete MAL loci composed of MAL32 (encoding maltase), MAL31 (transporter), and MAL33 (transcriptional activator) genes. Comparative polymorphism analyses identified mutations in MAL32 and MAL33 of QC18, including frameshift mutations resulting in premature stop codons. Functional validation demonstrated that the heterologous expression of MAL33 ChrV from CL467.1 fully restored maltose utilization in QC18, indicating the functional presence of MAL33 cis-regulatory sequences and MAL32 and MAL31 genes in QC18. While structural protein predictions identified truncation and impaired functionality in the maltose-responsive activation domain of Mal33p from QC18, overexpression of QC18’s own MAL33 ChrV allele also improved maltose metabolism, suggesting dosage-dependent transcriptional limitations rather than complete functional loss. These results indicate that allelic variations in the maltose-responsive activation domain of Mal33p result in differences in maltose consumption between strains. Here, we hypothesized that reduced maltose metabolism in QC18 is an adaptive response to the distinct sugar composition in Quercus robur bark, contrasting with the starch-rich environment of Nothofagus pumilio. These findings highlight subtelomeric MAL gene diversity as a reservoir of genetic variation, representing a key evolutionary mechanism that influences maltose adaptation among natural Saccharomyces isolates.

evolutionary plasticity↗
DOE OSTI2026

A single genomic region controls primocane fruiting in tetraploid blackberry

The fresh-market blackberry ( Rubus subgenus Rubus ) industry has expanded dramatically in the past 2 decades, driven in part by improved cultivars. Introgression of the primocane-fruiting (PF; annual flowering) trait into elite germplasm has enabled dual cropping in a single year, season extension, and cultivation in tropical and subtropical regions. Despite its economic performance, the genetic basis of PF is not well understood. It has been proposed that the PF trait is controlled by a major recessive locus, but its genomic location is unclear. Here, a genome-wide association study (GWAS) of 365 tetraploid blackberry genotypes identified a single genomic region on chromosome Ra03 (∼33 Mb) strongly associated with PF. Genetic linkage analysis in a biparental population confirmed that the same interval (32–35 Mb) was linked to the PF phenotype. Ten putative candidate genes were identified in this region. Allele mining using whole-genome resequencing of 17 genotypes highlighted 2 high-priority candidates: a CCCH-type zinc finger gene and an ubiquitin-specific protease gene. Use of an improved Rubus argutus “Hillquist” genome annotation (v1.2) enabled refined variant interpretation, including identification of regulatory 3′ UTR polymorphisms in the zinc finger homolog. Two diagnostic KASP markers (PF1 and PF2), designed from the most significant GWAS SNPs, predicted the PF phenotype with over 96% accuracy in a validation panel of 494 tetraploid blackberries from multiple breeding programs. Together, these results provide the first high-resolution mapping of the PF locus in blackberry, identify candidate genes for flowering regulation in Rubus , and deliver diagnostic markers that can be immediately deployed in breeding programs.

GWAS↗
DOE OSTI2025

LinkML: an open data modeling framework

Background Scientific research relies on well-structured, standardized data; however, much of it is stored in formats such as free-text lab notebooks, nonstandardized spreadsheets, or data repositories. This lack of structure challenges interoperability, making data integration, validation, and reuse difficult. Findings LinkML (Linked Data Modeling Language) is an open framework that simplifies the process of authoring, validating, and sharing data. LinkML can describe a range of data structures, from flat, list-based models to complex, interrelated, and normalized models that utilize polymorphism and compound inheritance. It offers an approachable syntax that is not tied to any one technical architecture and can be integrated seamlessly with many existing frameworks. The LinkML syntax provides a standard way to describe schemas, classes, and relationships, allowing modelers to build well-defined, stable, and optionally ontology-aligned data structures. Once defined, LinkML schemas may be imported into other LinkML schemas. These key features make LinkML an accessible platform for interdisciplinary collaboration and a reliable way to define and share data semantics. Conclusions LinkML helps reduce heterogeneity, complexity, and the proliferation of single-use data models while simultaneously enabling compliance with FAIR (Findable, Accessible, Interoperable, and Reusable) data standards. LinkML has seen increasing adoption in various fields, including biology, chemistry, biomedicine, microbiome research, finance, electrical engineering, transportation, and commercial software development. In short, LinkML makes implicit models explicitly computable and allows data to be standardized at their origin. LinkML documentation and code are available at https://linkml.io/.

AI-ready data↗
DOE OSTI2024

Identification of 2 Novel Subtypes of Hepatitis C Virus Genotype 8 and a Potential New Genotype Successfully Treated With Direct Acting Antivirals

Abstract Background Hepatitis C virus (HCV) has high genetic diversity and is classified into 8 genotypes and >90 subtypes, with some endemic to specific world regions. This could compromise direct-acting antiviral efficacy and global HCV elimination. Methods We characterized HCV subtypes “rare” in the United Kingdom (non-1a/1b/2b/3a/4d) by means of whole-genome sequencing via a national surveillance program. Genetic analyses to determine the genotype of samples with unresolved genotypes were undertaken by comparison with International Committee on Taxonomy of Viruses HCV reference sequences. Results Two HCV variants were characterized as being closely related to the recently identified genotype (GT) 8, with >85% pairwise genetic distance similarity to GT8 sequences and within the typical intersubtype genetic distance range. The individuals infected by the variants were UK residents originally from Pakistan and India. In contrast, a third variant was only confidently identified to be more similar to GT6 compared with other genotypes across 6% of the genome and was isolated from a UK resident originally from Guyana. All 3 were cured with pangenotypic direct-acting antivirals (sofosbuvir-velpatasvir or glecaprevir-pibrentasvir) despite the presence of resistance polymorphisms in NS3 (80K/168E), NS5A (28V/30S/62L/92S/93S) and NS5B (159F). Conclusions This study expands our knowledge of HCV diversity by identifying 2 new GT8 subtypes and potentially a new genotype.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Protoplast fusion as a strategy to increase ploidy in Rhodotorula toruloides for strain development

Rhodotorula toruloides is a red oleaginous yeast with growing commercial interest because of its hardiness and exceptional lipid production capacity. Because it is a basidiomycete yeast with a complex life cycle, many of the classical breeding methods used with ascomycetes are unavailable for strain improvement. However, we have been able to construct polyploid yeast by fusing protoplasts of parents with the same mating type. Fusing of Y-6985 (A2) and Y-48190 (A2), which had been transformed with complementary antibiotic markers, led to the recovery of two diploids and one triploid. The stability of the fusion yeasts was tested by plating them on non-selective medium after several growth cycles under antibiotics and then testing five colonies per strain for nuclear DNA contents using flow cytometry and standard cell cycle analysis: the triploid and one diploid were stable. Fusants inherited their mitochondria from a single parent, which was demonstrated using restriction fragment length polymorphism (RFLP) of mitochondrial DNA. The phenotypic properties of the parents and fusants were compared in glucose fed-batch bioreactor studies and cellulosic sugar batch cultures. The final lipid titers for the fed-batch cultures were 24.9–39.7 g/L with Y-6985 and the diploid and triploid performing the best and worst, respectively. The fusants demonstrated intermediate hardiness for growth on hydrolysate prepared with dilute-acid pretreated switchgrass and were outperformed by Y-48190. Unlike one of the haploid parents, the fusants grew in 70% v/v concentrated hydrolysate. Furthermore, they did not grow as fast as the other haploid. In this study, a modernized protoplast fusion method is resurrected a useful tool for strain development in this yeast, which is complementary with other available methods.

Lignocellulose↗