Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “complexes”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Methods and algorithms for computer synthesis of holographic elements to obtain a complex impulse response of optical information processing systems based on modern spatial light modulators

The possibilities of designing optical devices for data processing and imaging based on the manipulation of coherent light beams by means of spatial light modulators (SLMs) are investigated. A review of commercially available SLMs is presented and the limitations of their complex modulation characteristics are analysed. The main problem of using present-day SLMs is the lack of the ability to modulate directly all states within a unit circle in the complex plane. In this regard, the characteristics of current methods for the synthesis of holographic elements are described that implement a given complex impulse response of the optical system and are optimal for using SLMs with purely amplitude, purely phase, and hybrid amplitude – phase modulation. (paper)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Structure of a paramyxovirus polymerase complex reveals a unique methyltransferase-CTD conformation

Paramyxoviruses are enveloped, nonsegmented, negative-strand RNA viruses that cause a wide spectrum of human and animal diseases. The viral genome, packaged by the nucleoprotein (N), serves as a template for the polymerase complex, composed of the large protein (L) and the homo-tetrameric phosphoprotein (P). The ~250-kDa L possesses all enzymatic activities necessary for its function but requires P in vivo. Structural information is available for individual P domains from different paramyxoviruses, but how P interacts with L and how that affects the activity of L is largely unknown due to the lack of high-resolution structures of this complex in this viral family. In this study we determined the structure of the L–P complex from parainfluenza virus 5 (PIV5) at 4.3-Å resolution using cryoelectron microscopy, as well as the oligomerization domain (OD) of P at 1.4-Å resolution using X-ray crystallography. P-OD associates with the RNA-dependent RNA polymerase domain of L and protrudes away from it, while the X domain of one chain of P is bound near the L nucleotide entry site. The methyltransferase (MTase) domain and the C-terminal domain (CTD) of L adopt a unique conformation, positioning the MTase active site immediately above the poly-ribonucleotidyltransferase domain and near the likely exit site for the product RNA 5' end. Our study reveals a potential mechanism that mononegavirus polymerases may employ to switch between transcription and genome replication. This knowledge will assist in the design and development of antivirals against paramyxoviruses.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Electronic structure and photophysics of a supermolecular iron complex having a long MLCT-state lifetime and panchromatic absorption

Exploiting earth-abundant iron-based metal complexes as high-performance photosensitizers demands long-lived electronically excited metal-to-ligand charge-transfer (MLCT) states, but these species suffer typically from femtosecond timescale charge-transfer (CT)-state quenching by low-lying nonreactive metal-centered (MC) states. Here, we engineer supermolecular Fe(II) chromophores based on the bis(tridentate-ligand)metal(II)-ethyne-(porphinato)zinc(II) conjugated framework, previously shown to give rise to highly delocalized low-lying 3 MLCT states for other Group VIII metal (Ru, Os) complexes. Electronic spectral, potentiometric, and ultrafast pump–probe transient dynamical data demonstrate that a combination of a strong σ-donating tridentate ligand and a (porphinato)zinc(II) moiety with low-lying π*-energy levels, sufficiently destabilize MC states and stabilize supermolecular MLCT states to realize Fe(II) complexes that express 3 MLCT state photophysics reminiscent of their heavy-metal analogs. The resulting Fe(II) chromophore archetype, FeNHCPZn, features a highly polarized CT state having a profoundly extended 3MLCT lifetime (160 ps), 3 MLCT phosphorescence, and ambient environment stability. Density functional and domain-based local pair natural orbital coupled cluster [DLPNO-CCSD(T)] theory reveal triplet-state wavefunction spatial distributions consistent with electronic spectroscopic and excited-state dynamical data, further underscoring the dramatic Fe metal-to-extended ligand CT character of electronically excited FeNHCPZn. This design further prompts intense panchromatic absorptivity via redistributing high-energy absorptive oscillator strength throughout the visible spectral domain, while maintaining a substantial excited-state oxidation potential for wide-ranging photochemistry––highlighted by the ability of FeNHCPZn to photoinject charges into a SnO 2 /FTO electrode in a dye-sensitized solar cell (DSSC) architecture. Concepts enumerated herein afford opportunities for replacing traditional rare-metal–based emitters for solar-energy conversion and photoluminescence applications.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

Structure of pre-miR-31 reveals an active role in Dicer–TRBP complex processing

As an essential posttranscriptional regulator of gene expression, microRNA (miRNA) levels must be strictly maintained. The biogenesis of many miRNAs is mediated by trans-acting protein partners through a variety of mechanisms, including remodeling of the RNA structure. miR-31 functions as an oncogene in numerous cancers, and interestingly, its biogenesis is not known to be regulated by protein-binding partners. Therefore, the intrinsic structural properties of the precursor element of miR-31 (pre-miR-31) can provide a mechanism by which its biogenesis is regulated. We determined the solution structure of pre-miR-31 to investigate the role of distinct structural elements in regulating processing by the Dicer–TRBP complex. We found that the presence or absence of mismatches within the helical stem does not strongly influence Dicer–TRBP processing of the pre-miRNAs. However, both the apical loop size and structure at the Dicing site are key elements for discrimination by the Dicer–TRBP complex. Interestingly, our NMR-derived structure reveals the presence of a triplet of base pairs that link the Dicer cleavage site and the apical loop. Mutational analysis in this region suggests that the stability of the junction region strongly influences processing by the Dicer–TRBP complex. Our results enrich our understanding of the active role that RNA structure plays in regulating miRNA biogenesis, which has direct implications for the control of gene expression.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Viral afterlife: SARS-CoV-2 as a reservoir of immunomimetic peptides that reassemble into proinflammatory supramolecular complexes

It is unclear how severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection leads to the strong but ineffective inflammatory response that characterizes severe Coronavirus disease 2019 (COVID-19), with amplified immune activation in diverse cell types, including cells without angiotensin-converting enzyme 2 receptors necessary for infection. Proteolytic degradation of SARS-CoV-2 virions is a milestone in host viral clearance, but the impact of remnant viral peptide fragments from high viral loads is not known. Here, we examine the inflammatory capacity of fragmented viral components from the perspective of supramolecular self-organization in the infected host environment. Interestingly, a machine learning analysis to SARS-CoV-2 proteome reveals sequence motifs that mimic host antimicrobial peptides (xenoAMPs), especially highly cationic human cathelicidin LL-37 capable of augmenting inflammation. Such xenoAMPs are strongly enriched in SARS-CoV-2 relative to low-pathogenicity coronaviruses. Moreover, xenoAMPs from SARS-CoV-2 but not low-pathogenicity homologs assemble double-stranded RNA (dsRNA) into nanocrystalline complexes with lattice constants commensurate with the steric size of Toll-like receptor (TLR)-3 and therefore capable of multivalent binding. Such complexes amplify cytokine secretion in diverse uninfected cell types in culture (epithelial cells, endothelial cells, keratinocytes, monocytes, and macrophages), similar to cathelicidin’s role in rheumatoid arthritis and lupus. The induced transcriptome matches well with the global gene expression pattern in COVID-19, despite using <0.3% of the viral proteome. Delivery of these complexes to uninfected mice boosts plasma interleukin-6 and CXCL1 levels as observed in COVID-19 patients.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Scientific machine learning for modeling and simulating complex fluids

The formulation of rheological constitutive equations—models that relate internal stresses and deformations in complex fluids—is a critical step in the engineering of systems involving soft materials. While data-driven models provide accessible alternatives to expensive first-principles models and less accurate empirical models in many engineering disciplines, the development of similar models for complex fluids has lagged. The diversity of techniques for characterizing non-Newtonian fluid dynamics creates a challenge for classical machine learning approaches, which require uniformly structured training data. Consequently, early machine-learning based constitutive equations have not been portable between different deformation protocols or mechanical observables. Here, we present a data-driven framework that resolves such issues, allowing rheologists to construct learnable models that incorporate essential physical information, while remaining agnostic to details regarding particular experimental protocols or flow kinematics. These scientific machine learning models incorporate a universal approximator within a materially objective tensorial constitutive framework. By construction, these models respect physical constraints, such as frame-invariance and tensor symmetry, required by continuum mechanics. We demonstrate that this framework facilitates the rapid discovery of accurate constitutive equations from limited data and that the learned models may be used to describe more kinematically complex flows. This inherent flexibility admits the application of these “digital fluid twins” to a range of material systems and engineering problems. We illustrate this flexibility by deploying a trained model within a multidimensional computational fluid dynamics simulation—a task that is not achievable using any previously developed data-driven rheological equation of state.

Science & Technology - Other Topics↗
DOE OSTI2025

An unusual Co–S bond links B 12 chaperones in an interprotein complex

Chaperones in trafficking pathways ensure specificity of transition metal loading and protection against adventitious side reactions. In B 12 , an essential cofactor for humans, a cobalt ion is coordinated to a >1.3 kDa tetrapyrrolic scaffold, posing logistical challenges for its translocation. In this study, we report the 3.4 Å crystal structure of the human MMACHC and MMADHC B 12 chaperones, tethered via a rarely seen covalent cobalt–sulfur bond. B 12 is bound in the base-off state to MMACHC, with Cys-261 on MMADHC serving as the upper axial ligand; the lower-axial position is vacant. The propensity of thiolato-cobalamin derivatives bound to MMACHC to undergo spontaneous decomposition via general acid catalysis or reduction/oxidation chemistry is averted in the interprotein complex with MMADHC. An exposed face in the complex suggests an exit route for B 12 . No known clinical variants localize to the interprotein interface, consistent with the cobalt–sulfur bond being key to forming the high-affinity complex.

Science & Technology - Other Topics↗
DOE OSTI2025

Action at a distance: The remarkable coupling of CO 2 uptake to electron transfer in specialized cyanobacterial NDH-1 complexes

Cyanobacteria achieve highly efficient photosynthesis using a CO 2 -concentrating mechanism relying on specialized Type I (NDH-1) complexes. Among these, NDH-1 3 and NDH-1 4 catalyze redox-coupled hydration of CO 2 to bicarbonate, supporting carbon fixation in carboxysomes. The mechanism of coupling electron transfer to CO 2 -hydration by these variant NDH-1 complexes remains unknown. We engineered a Synechococcus PCC7942 strain that expresses exclusively the high flux/low affinity NDH-14 complex, enabling the observation of the coupling of CO 2 hydration to cyclic electron flow in isolation from the other NDH-1 isoforms normally present in cells. We found that inhibition of the CupB protein by the carbonic anhydrase inhibitor ethoxzolamide (EZ) suppressed CO 2 uptake, slowed photosystem I rereduction, and abolished proton pumping as probed by acridine orange fluorescence. These effects were absent in strains lacking Cup proteins, confirming specificity. The results demonstrate that CO 2 hydration and electron transfer through NDH-14 are tightly coupled via proton translocation across the thylakoid membrane. These findings provide direct evidence for the bidirectional interaction in bioenergetic coupling between the plastoquinone reduction and the CO 2 uptake at the distal Zn-site over a span of ~150 Å and support a proton-removal hypothesis involving the proton transfer pathways from the Zn-site of CO2 hydration to an energetically coupled proton loading site evolutionarily repurposed from the ancestral proton pumping mechanism to enable energetic CO 2 uptake.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Cryogenic and Temperature-Dependent Photoelectron Spectroscopy of Metal Complexes

Negative ion photoelectron spectroscopy (NIPES) coupled with electrospray ionization (ESI) has been proved to be a powerful gas-phase spectroscopic tool for characterizing electronic structures and chemical bonding of a variety of cluster anions and corresponding neutral radicals involved in the condensed phase reactions and transformations. Since the acquisition of cryogenic and temperature-controlling capabilities, broader range of research scope has been covered. This review summarizes our recent investigations on metal complexes employing cryogenic ESI-NIPES that provide us essential information towards understanding complicated condensed phase reactions including hydrocarbon activations and electron transfer reactions, and afford us spectroscopic probe of highly reactive transient species and intimate redox pairs. Special attention has been drawn to connect gas phase photodetachment processes with solution phase redox reactions. Photodetachment of transition metal-EDTA complexes has been systematically investigated to model the sequential oxidation reactions of these species in solutions. The obtained gas phase electron affinity (EA) is compared with the solution redox potential (E1/2) and the metal ionization potential (IP) for several series of homologous metal complexes to emphasize their intrinsic correlations with deviations being largely modulated by different degrees of ligand participations.

Yuan, Qinqin↗
DOE OSTI2021

Microstate distinguishability, quantum complexity, and the eigenstate thermalization hypothesis

In this work, we use quantum complexity theory to quantify the difficulty of distinguishing eigenstates obeying the eigenstate thermalization hypothesis (ETH). After identifying simple operators with an algebra of low-energy observables and tracing out the complementary high-energy Hilbert space, the ETH leads to an exponential suppression of trace distance between the coarse grained eigenstates. Conversely, we show that an exponential hardness of distinguishing between states implies ETH-like matrix elements. Finally, the BBBV lower bound on the query complexity of Grover search then translates directly into a complexity-theoretic statement lower bounding the hardness of distinguishing these reduced states

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Understanding polaronic transport in complex oxides by combining precise synthesis and first-principles many-body theory

In complex oxides, charge carriers often couple strongly with lattice vibrations to form polarons–entangled electron–phonon quasiparticles whose transport properties remain difficult to characterize. Experimental access to intrinsic polaronic transport requires ultraclean samples, while theoretical description demands methods beyond low-order perturbation theory. Here, we show a predictive theory–experiment workflow to study polaron transport in complex oxides. Focusing on a prototypical polaronic oxide, anatase TiO 2 , we combine growth of high-quality oxygen-vacancy-doped films using hybrid molecular beam epitaxy with a first-principles electron–phonon diagrammatic Monte-Carlo (FEP-DMC) framework recently developed for accurate polaron predictions. Our films exhibit record-high electron mobility for anatase TiO 2 , in excellent agreement with FEP-DMC calculations conducted prior to experiment, which predict a room-temperature mobility of 45 ± 15 cm −2 V −1 s −1 and a mobility-temperature scaling of μ ∝ T −1.9 ± 0.077 . Microscopic analysis using scanning transmission electron microscopy and x-ray photoelectron spectroscopy reveals the role of oxygen vacancies in modulating transport at lower temperatures. FEP-DMC further provides quantitative insight into polaron formation energy, phonon cloud distribution, lattice distortion around the polaron, and the polaronic contribution to mobility. Together, these results provide a deeper microscopic understanding of large-polaron transport in a complex oxide and provide the blueprint to characterize other polaronic materials.

anatase TiO2↗
DOE OSTI2025

Many-body expansion based machine learning models for octahedral transition metal complexes

Abstract Graph-based machine learning (ML) models for material properties show great potential to accelerate virtual high-throughput screening of large chemical spaces. However, in their simplest forms, graph-based models do not include any 3D information and are unable to distinguish stereoisomers such as those arising from different orderings of ligands around a metal center in coordination complexes. In this work we present a modification to revised autocorrelation descriptors, a molecular graph featurization method, for predicting spin state dependent properties of octahedral transition metal complexes (TMCs). Inspired by analytical semi-empirical models for TMCs, the new modeling strategy is based on the many-body expansion (MBE) and allows one to tune the captured stereoisomer information by changing the truncation order of the MBE. We present the necessary modifications to include this approach in two commonly used ML methods, kernel ridge regression and feed-forward neural networks. On a test set composed of all possible isomers of binary TMCs, the best MBE models achieve mean absolute errors (MAEs) of 2.75 kcal mol −1 on spin-splitting energies and 0.26 eV on frontier orbital energy gaps, a 30%–40% reduction in error compared to models based on our previous approach. We also observe improved generalization to previously unseen ligands where the best-performing models exhibit MAEs of 4.00 kcal mol −1 (i.e. a 0.73 kcal mol −1 reduction) on the spin-splitting energies and 0.53 eV (i.e. a 0.10 eV reduction) on the frontier orbital energy gaps. Because the new approach incorporates insights from electronic structure theory, such as ligand additivity relationships, these models exhibit systematic generalization from homoleptic to heteroleptic complexes, allowing for efficient screening of TMC search spaces.

Meyer, Ralf (ORCID:0000000322360261)↗
DOE OSTI2025

Leveraging dendritic complexity for neuromorphic computing

Abstract Beyond-von Neumann computing approaches are necessary to sustain the growth of microelectronics and the increasing appetite for artificial intelligence/machine learning algorithms. Neuromorphic computing is an emerging paradigm that takes inspiration from the brain to provide a path forward to improve the computational efficiency and computational density of next-generation computing architectures. In nature, we observe brains performing complex computations with a much smaller energy footprint than conventional computing approaches. Current neuromorphic systems are focused primarily on scalability, namely, increasing the number of computational units (neurons) and connections between units (synapses). However, for brain-like cognition and efficiency in next-generation computing hardware, we need increased complexity in function, as well as improved connection density for scalability. Here, we present our work that aims to incorporate dendrites for ‘compute-on-wire’ in neuromorphic architectures to increase the computational complexity (e.g. number of programmable parameters, nonlinear dynamics) as well as computational efficiency (energy/compute) of artificial neural networks (ANNs). We do this by showcasing neuromorphic dendrite elements that can be leveraged for various applications. We will present examples of neuroscience-inspired direction-selective circuits and an ANN with active dendrites leveraging shunting inhibition. We also demonstrate the benefits of using dendrites in deep neural networks. To conclude, we discuss how we can utilize emerging hardware devices in these systems and design next-generation neuromorphic architectures with dendrites.

Cardwell, Suma G. (ORCID:0000000226575545)↗
DOE OSTI2022

Inexact Newton-CG algorithms with complexity guarantees

Abstract We consider variants of a recently developed Newton-CG algorithm for nonconvex problems (Royer, C. W. & Wright, S. J. (2018) Complexity analysis of second-order line-search algorithms for smooth nonconvex optimization. SIAM J. Optim., 28, 1448–1477) in which inexact estimates of the gradient and the Hessian information are used for various steps. Under certain conditions on the inexactness measures, we derive iteration complexity bounds for achieving $\epsilon $-approximate second-order optimality that match best-known lower bounds. Our inexactness condition on the gradient is adaptive, allowing for crude accuracy in regions with large gradients. We describe two variants of our approach, one in which the step size along the computed search direction is chosen adaptively, and another in which the step size is pre-defined. To obtain second-order optimality, our algorithms will make use of a negative curvature direction on some steps. These directions can be obtained, with high probability, using the randomized Lanczos algorithm. In this sense, all of our results hold with high probability over the run of the algorithm. We evaluate the performance of our proposed algorithms empirically on several machine learning models. Our approach is a first attempt to introduce inexact Hessian and/or gradient information into the Newton-CG algorithm of Royer & Wright (2018, Complexity analysis of second-order line-search algorithms for smooth nonconvex optimization. SIAM J. Optim., 28, 1448–1477).

Mathematics↗
DOE OSTI2022

Elucidation of complex respiratory chains: a straightforward strategy to monitor electron transfer between cytochromes

Abstract Cytochromes are electron transfer (ET) proteins essential in various biological systems, playing crucial roles in the respiratory chains of bacteria. These proteins are particularly abundant in electrogenic microorganisms and are responsible for the efficient delivery of electrons to the cells’ exterior. The capability of sending electrons outside the cells open new avenues to be explored for emerging biotechnological applications in bioremediation, microbial electrosynthesis, and bioenergy fields. To develop these applications, it is critical to identify the different redox partners and to elucidate the stepwise ET along the respiratory paths. However, investigating direct ET events between proteins with identical features in nearly all spectroscopic techniques is extremely challenging. Nuclear magnetic resonance (NMR) spectroscopy offers the possibility to overcome this difficulty by analysing the alterations of the spectral signatures of each protein caused by electron exchange events. The uncrowded NMR spectral regions containing the heme resonances of the cytochromes display unique and distinct signatures in the reduced and oxidized states, which can be explored to monitor ET within the redox complex. In this study, we present a strategy for a fast and straightforward monitorization of ET between c-type cytochromes, using as model a triheme periplasmic cytochrome and a membrane-associated monoheme cytochrome from the electrogenic bacterium Geobacter sulfurreducens. The comparison between the 1D 1H NMR spectra obtained for samples containing the two cytochromes and for samples containing the individual proteins clearly demonstrated a unidirectional ET within the redox complex. This strategy provides a simple and straightforward means to elucidate complex biologic respiratory ET chains.

Morgado, Leonor (ORCID:0000000237605180)↗
DOE OSTI2020

Mycobacterial DNA polymerase I: activities and crystal structures of the POL domain as apoenzyme and in complex with a DNA primer-template and of the full-length FEN/EXO–POL enzyme

Mycobacterial Pol1 is a bifunctional enzyme composed of an N-terminal DNA flap endonuclease/5' exonuclease domain (FEN/EXO) and a C-terminal DNA polymerase domain (POL). Here we document additional functions of Pol1: FEN activity on the flap RNA strand of an RNA:DNA hybrid and reverse transcriptase activity on a DNA-primed RNA template. We report crystal structures of the POL domain, as apoenzyme and as ternary complex with 3'-dideoxy-terminated DNA primer-template and dNTP. The thumb, palm, and fingers subdomains of POL form an extensive interface with the primer-template and the triphosphate of the incoming dNTP. Progression from an open conformation of the apoenzyme to a nearly closed conformation of the ternary complex entails a disordered-to-ordered transition of several segments of the thumb and fingers modules and an inward motion of the fingers subdomain—especially the O helix—to engage the primer-template and dNTP triphosphate. Distinctive structural features of mycobacterial Pol1 POL include a manganese binding site in the vestigial 3' exonuclease subdomain and a non-catalytic water-bridged magnesium complex at the protein-DNA interface. We report a crystal structure of the bifunctional FEN/EXO–POL apoenzyme that reveals the positions of two active site metals in the FEN/EXO domain.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Pot1 promotes telomere DNA replication via the Stn1-Ten1 complex in fission yeast

Abstract Telomeres are nucleoprotein complexes that protect the chromosome-ends from eliciting DNA repair while ensuring their complete duplication. Pot1 is a subunit of telomere capping complex that binds to the G-rich overhang and inhibits the activation of DNA damage checkpoints. In this study, we explore new functions of fission yeast Pot1 by using a pot1-1 temperature sensitive mutant. We show that pot1 inactivation impairs telomere DNA replication resulting in the accumulation of ssDNA leading to the complete loss of telomeric DNA. Recruitment of Stn1 to telomeres, an auxiliary factor of DNA lagging strand synthesis, is reduced in pot1-1 mutants and overexpression of Stn1 rescues loss of telomeres and cell viability at restrictive temperature. We propose that Pot1 plays a crucial function in telomere DNA replication by recruiting Stn1-Ten1 and Polα-primase complex to telomeres via Tpz1, thus promoting lagging-strand DNA synthesis at stalled replication forks.

Carvalho Borges, Pâmela C. (ORCID:0000000244919874↗
DOE OSTI2025

Optimizing genomic prediction for complex traits via investigating multiple factors in switchgrass

Genomic prediction has accelerated breeding processes and provided mechanistic insights into the genetic bases of complex traits. To further optimize genomic prediction, we assess the impact of genome assemblies, genotyping approaches, variant types, allelic complexities, polyploidy levels, and population structures on the prediction of 20 complex traits in switchgrass (Panicum virgatum L.), a perennial biofuel feedstock. Surprisingly, short read-based genome assembly performs comparably to or even better than long read-based assembly. Due to higher gene coverage, exome capture and multi-allelic variants outperform genotyping-by-sequencing and bi-allelic variants, respectively. Tetraploid models show higher prediction accuracy than octoploid models for most traits, likely due to the greater genetic distances among tetraploids. Depending on the trait in question, different types of variants need to be integrated for optimal predictions. Furthermore, our study provides insights into the factors influencing genomic prediction outcomes, guiding best practices for future studies and for improving agronomic traits in switchgrass and other species through selective breeding.

60 APPLIED LIFE SCIENCES↗