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At least 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Enabling Efficient Water Splitting with Advanced Materials Designed for High pH Membrane Interface

This research focuses on durable, high-performance materials and interfaces for advanced water splitting, enabling a clear pathway for achieving <$2/KgH2 (on scale) via anion exchange membrane (AEM)-based electrolysis. We aim to advance this goal via an improved fundamental understanding of both hydrogen and oxygen evolution reactions (HER/OER) leading to platinum group metal (PGM)-free catalyst materials. Here, we use NiFeCo and NiMo as OER and HER catalysts, respectively, in a full alkaline electrolysis cell. A thermally stable, multi-cation AEM is used to operate the cell at elevated temperatures thereby lowering the operating potential by increasing the kinetics of the respective catalytic reactions. The transition metal catalysts, paired with this novel AEM, have been used to achieve an operating potential of 1.79 V at 1 A/cm2. This potential is 300 mV lower than similar electrolysis cells equipped with PGM-based catalysts. We have also demonstrated the efficacy of the less caustic potassium carbonate solution as a replacement for potassium hydroxide as an electrolyte. By using a carbonate-based electrolyte, the hydroxide ion required for the anodic reaction is continuously replenished by re-establishing an equilibrium with water. This consideration, coupled with the reduced alkalinity of the carbonate solution, yields an electrolysis cell capable of sustained operation with minimal increase in operating potential.

Kendrick, Ian↗
DOE OSTI2023

Genome‐wide association and genomic prediction for yield and component traits of Miscanthus sacchariflorus

Abstract Accelerating biomass improvement is a major goal of Miscanthus breeding. The development and implementation of genomic‐enabled breeding tools, like marker‐assisted selection (MAS) and genomic selection, has the potential to improve the efficiency of Miscanthus breeding. The present study conducted genome‐wide association (GWA) and genomic prediction of biomass yield and 14 yield‐components traits in Miscanthus sacchariflorus . We evaluated a diversity panel with 590 accessions of M. sacchariflorus grown across 4 years in one subtropical and three temperate locations and genotyped with 268,109 single‐nucleotide polymorphisms (SNPs). The GWA study identified a total of 835 significant SNPs and 674 candidate genes across all traits and locations. Of the significant SNPs identified, 280 were localized in mapped quantitative trait loci intervals and proximal to SNPs identified for similar traits in previously reported Miscanthus studies, providing additional support for the importance of these genomic regions for biomass yield. Our study gave insights into the genetic basis for yield‐component traits in M. sacchariflorus that may facilitate marker‐assisted breeding for biomass yield. Genomic prediction accuracy for the yield‐related traits ranged from 0.15 to 0.52 across all locations and genetic groups. Prediction accuracies within the six genetic groupings of M. sacchariflorus were limited due to low sample sizes. Nevertheless, the Korea/NE China/Russia ( N = 237) genetic group had the highest prediction accuracy of all genetic groups (ranging 0.26–0.71), suggesting that with adequate sample sizes, there is strong potential for genomic selection within the genetic groupings of M. sacchariflorus . This study indicated that MAS and genomic prediction will likely be beneficial for conducting population‐improvement of M. sacchariflorus .

09 BIOMASS FUELS↗
NASA NTRS1992

Analysis of the effect of initial conditions on the initial development of a turbulent jet

The effect of the initial condition at the jet exit on the downstream evolution, particularly within the potential core length, were numerically investigated as well as with available experimental data. In order to select the most dependable computational model for the present numerical experiment, a comparative study has been performed with different turbulence models at k-epsilon level, and it was found that the k-epsilon-gammma model yields superior prediction accuracy over other conventional models. The calculated results show that the potential core length and the spreading rate the initial mixing layer are dependent on the initial length scale as well as the turbulent kinetic energy at the jet exit. Such effect of the initial length scale increases with higher initial turbulence level. An empirical parameter has been devised to collapse the calculated data of the potential core length and the spreading rate with various initial conditions onto a single curve.

Kim, Soong KI↗
DOE OSTI2023

Techno-economic assessment and life cycle assessment of three potential pathways for biomass liquefaction

Biomass liquefaction can enhance corn-stover slurry transportation by reducing yield stress and overall viscosity, easing biomass handling, especially for slurries at high solids loading (≥30 % (w/v). Implementing a liquefaction process at the front-end of the biorefinery could reduce downtime caused by equipment fouling. Furthermore, liquefaction reduces process complexity by transforming high fiber mass into a pumpable slurry. Three scenarios for liquefaction of corn stover pellets: enzyme process, enzyme mimetic process, and a combined process of enzyme and enzyme mimetic were assessed. The ideal process will have the best performance-to-cost ratio, with minimal impact on the environment. Techno-economic and life-cycle analyses were used to understand the economic and environmental effects of the three liquefaction scenarios and to determine if one or more can achieve cost parity. Here, results show that the enzyme process had the best performance in terms of cost and emissions (gCO 2 -equivalent/kg slurry)compared to the other scenarios.

09 BIOMASS FUELS↗
NASA NTRS1995

MP2 Studies of Relativistic Effects on the Linear Stationary Points of the H+Cl2 Yields HCl+Cl and Cl+HCl Yields ClH+Cl Reactions

The influence of relativistic effects on the linear stationary points of the potential energy surfaces of the ClHCl and HCl2 systems is studied. Scalar relativistic effects have little influence on the geometries and the energies of these points. Spin-orbit effects have no influence on the barrier of the forward reaction of H with Cl2, but increase the reaction energy. The total relativistic effect is an increase of the reaction energy by 2.3 kJ /mol. The barrier for the iso-energetic exchange reaction of HCl with Cl is decreased by 0.5 kJ /mol due to the scalar relativistic effects. This small decrease is cancelled by the larger increase of 2.5 kJ /mol due to spin-orbit effects, giving a total relativistic effect of 2.0 kJ /mol.

Visscher, L.↗
DOE OSTI2021

Modelling yield cap evolution in sandstone based on brittle creep experiments

The Zenifim Formation is being considered as a potential disposal formation for a deep borehole nuclear repository concept in Israel. Site selection and repository construction are intended to ensure that waste is separated from circulating groundwater, but long-term deformation of the wellbore could potentially create fluid flow pathways. To understand how time-dependent rock strength could affect wellbore stability, here we conducted creep tests under low to moderate confining pressures on retrieved core from the Zenifim formation. During creep, samples strain slowly as gradual damage accumulation progressively weakens the samples. Failure eventually occurred through the near-instantaneous formation of a shear fracture. Experimental results were used to calibrate a continuum damage poro-elastic model for sandstones. The calibrated damage-poro-elastic model successfully simulates different types of loading experiments including quasi-static and creep. The state of strain in experiments is close to yield during loading as the yield cap continuously evolves with damage accumulation. For creep tests, most damage occurs during triaxial loading. Minor damage accumulation occurs under constant load until the final stage of creep, where damage accelerates and promotes unstable fracturing.

58 GEOSCIENCES↗
NASA NTRS1991

The Nickel(111)/Alkaline Electrolyte Interface

The electrochemical properties of Ni (111) prepared and characterized in ultra high vacuum, UHV, by surface analytical techniques have been examined in alkaline media by cyclic voltammetry using an UHV-electrochemical cell transfer system designed and built in this laboratory. Prior to the transfer, the Ni(111) surfaces were exposed to saturation coverages of CO in UHV in an attempt to protect the surface from possible contamination with other gases during the transfer. Temperature Programmed Desorption, TPD, of CO-dosed Ni (111) surfaces displaying sharp c(4x2), LEED patterns, subsequently exposed to water-saturated Ar at atmospheric pressure in an auxiliary UHV compatible chamber and finally transferred back to the main UHV chamber, yielded CO2 and water as the only detectable products. This indicates that the CO-dosed surfaces react with water and/or bicarbonate and hydroxide as the most likely products. Based on the integration of the TPD peaks, the combined amounts of H2O and CO2 were found to be on the order of a single monolayer. The reacted c(4x2)CO/Ni(111) layer seems to protect the surface from undergoing spontaneous oxidation in strongly alkaline solutions. This was evidenced by the fact that the open circuit potential observed immediately after contact with deaerated 0.1 M KOH was about 0.38 V vs. DHE, drifting slightly towards more negative values prior to initiating the voltametric scans. The average ratio of the integrated charge obtained in the first positive linear scan in the range of 0.35 to 1.5 V vs. DHE (initiated at the open circuit potential) and the first (and subsequent) linear negative scans in the same solution yielded for various independent runs a value of 3.5 +/- 0.3. Coulometric analysis of the cyclic voltammetry curves indicate that the electrochemically formed oxyhydroxide layer involves a charge equivalent to 3.2 +/- 0.4 layers of Ni metal.

Wang, Kuilong↗
DOE OSTI2022

Fabric-enriched continuum breakage mechanics (F-CBM )

A fabric-enriched continuum breakage mechanics (F-CBM) framework is developed to examine the relation between elastic and inelastic anisotropy in granular materials subjected to high pressure. For this purpose, emphasis is given to the influence of the anisotropic fabric on the plastic cap regime – that is, a macroscopic signature of the inelasticity of granular materials widely dependent on the particle crushability. Anisotropic behaviour prior to yielding is introduced through a symmetric second-order fabric tensor embedded in the expression of the elastic energy potential. It is shown that, thanks to its energy-based formulation, the F-CBM framework provides a platform to predict the rotation and distortion of the yield cap of granular materials as an outcome of anisotropic strain energy storage prior to grain crushing. Parametric analyses indicate that both the degree of anisotropy and the orientation of the fabric have an impact on the energy release resulting from grain crushing and contribute to the resulting stress–strain behaviour. It is shown that, despite the use of very few parameters, the proposed framework can accurately predict the anisotropic yielding and inelastic stress–strain response solely on the basis of the directional properties inferred from measurements of elastic anisotropy.

Engineering↗
NASA NTRS2012

Finding Near-Earth Asteroid (NEA) Destinations for Human Exploration: Implications for Astrobiology

The current number of known potential NEA targets for HSF is limited to those objects whose orbital characteristics are similar to that of the Earth. This is due to the projected capabilities of the exploration systems currently under consideration and development at NASA. However, NEAs with such orbital characteristics often have viewing geometries that place them at low solar elongations and thus are difficult to detect from the vicinity of Earth. While ongoing ground-based surveys and data archives maintained by the NEO Program Observation Program Office and the Minor Planet Center (MPC) have provided a solid basis upon which to build, a more complete catalog of the NEO population is required to inform a robust and sustainable HSF exploration program. Since all the present NEO observing assets are currently confined to the vicinity of the Earth, additional effort must be made to provide capabilities for detection of additional HSF targets via assets beyond Earth orbit. A space-based NEO survey telescope located beyond the vicinity of the Earth, has considerable implications for planetary science and astrobiology. Such a telescope will provide foundational knowledge of our Solar System small body population and detect targets of interest for both the HSF and scientific communities. Data from this asset will yield basic characterization data on the NEOs observed (i.e., albedo, size determination, potential for volatiles and organics, etc.) and help down select targets for future HSF missions. Ideally, the most attractive targets from both HSF and astrobiology perspectives are those NEAs that may contain organic and volatile materials, and which could be effectively sampled at a variety of locations and depths. Presented here is an overview of four space-based survey concepts; any one of which after just a few years of operation will discover many highly accessible NEO targets suitable for robotic and human exploration. Such a space-based survey mission will reveal incredible returns for several disciplines including: exploration, in situ resource utilization, planetary defense, and science. Of particular, interest to the scientific

Landis, Rob↗
DOE OSTI2021

Regulating Exciton–Phonon Coupling to Achieve a Near‐Unity Photoluminescence Quantum Yield in One‐Dimensional Hybrid Metal Halides

Abstract Low‐dimensional hybrid metal halides are emerging as a highly promising class of single‐component white‐emitting materials for their unique broadband emission from self‐trapped excitons (STEs). Despite substantial progress in the development of these metal halides, many challenges remain to be addressed to obtain a better fundamental understanding of the structure–property relationship and realize the full potentials of this class of materials. Here, via pressure regulation, a near 100% photoluminescence quantum yield (PLQY) of broadband emission is achieved in a corrugated 1D hybrid metal halide C 5 N 2 H 16 Pb 2 Br 6 , which possesses a highly distorted structure with an initial PLQY of 10%. Compression reduces the overlap between STE states and ground state, leading to a suppressed phonon‐assisted non‐radiative decay. The PL evolution is systematically demonstrated to be controlled by the pressure‐regulated exciton–phonon coupling which can be quantified using Huang–Rhys factor S . Detailed studies of the S ‐PLQY relation for a series of 1D hybrid metal halides (C 5 N 2 H 16 Pb 2 Br 6 , C 4 N 2 H 14 PbBr 4 , C 6 N 2 H 16 PbBr 4 , and (C 6 N 2 H 16 ) 3 Pb 2 Br 10 ) reveal a quantitative structure–property relationship that regulating S factor toward 28 leads to the maximum emission.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Unraveling the effects of management and climate on carbon fluxes of U.S. croplands using the USDA Long-Term Agroecosystem (LTAR) network

Understanding the carbon fluxes and dynamics from a broad range of agricultural systems has the potential to improve our ability to increase carbon sequestration while maintaining crop yields. Short-term, single-location studies have limited applicability, but long-term data from a network of many locations can provide a broader understanding across gradients of climate and management choices. Here we examine eddy covariance measured carbon dioxide (CO 2 ) fluxes from cropland sites across the United States Department of Agriculture's Long-Term Agroecosystem Research (LTAR) network. The dataset was collected between 2001 and 2020, spanning 13 sites for a total of 182 site-years. Average seasonal patterns of net ecosystem CO 2 exchange (NEE), gross primary productivity (GPP), and ecosystem respiration (R eco ) were determined, and subsequent regression analysis on these “flux climatologies” was used to identify relationships to mean annual temperature (MAT), mean annual precipitation (MAP), cropping systems, and management practices. At rainfed sites, carbon fluxes were better correlated with MAP (r2 ≤ 0.5) than MAT (r2 ≤ 0.22). Net carbon balance was different among cropping systems (p < 0.001), with the greatest net carbon uptake occurring in sugarcane (Saccharum spp. hybrids) and the least in soybean (Glycine max) fields. Crop type had a greater effect on carbon balance than irrigation management at a Nebraska site. Across cropping systems, grain crops often had higher GPP and were more likely to have net uptake when compared to legume crops. This multi-site analysis highlights the potential of the LTAR network to further carbon flux research using eddy covariance measurements.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Enhanced Guest@MOF Interaction via Stepwise Thermal Annealing: TCNQ@Cu 3 (BTC) 2

Confinement of guest molecules in porous materials such as metal organic frameworks (MOFs) promises to deliver emergent properties separate from those of the individual components. Understanding the confinement mechanism is therefore important for the development of new synthesis routes that adjust MOF properties for specific applications. In this work, we developed a new synthetic method to confine guest molecules into MOF pores through a stepwise thermal annealing process, wherein the confinement of 7,7,8,8-tetracyanoquinodimethane (TCNQ) guest molecules into Cu 3 (BTC) 2 (BTC = benzene-1,3,5-tricarboxylic acid) MOF host is used as an example of how novel materials can be created with new physical properties. The stepwise thermal annealing process includes 1) an activation process of pristine Cu 3 (BTC) 2 MOF to maximizes the TCNQ guest loading in the MOF host by effectively removing the residual solvents and 2) post-annealing of the TCNQ infiltrated MOF to enhances the interaction of the confined guest molecules with the MOF host. Obtained experimental results based on thermogravimetric analysis, N 2 gas adsorption, electron microscopy, X-ray diffraction and infrared absorption, combined with density functional theory calculations provide evidence that the use of a stepwise thermal annealing process yields enhancements in the guest loading, packing and interaction between the TCNQ guest and the MOF host. The new hybrid TCNQ@Cu 3 (BTC) 2 system is stable and shows no significant signs of structural degradation even after submersion in water. This is due to the presence of significantly stronger interactions of TCNQ with the frame-work metal ions compared to those of the water molecules competing for the same framework binding sites. It was also found that TCNQ@Cu 3 (BTC) 2 system maintains a significant CO 2 and CH 4 adsorption potential compared to the pristine MOF. The synthetic route developed in this work yields novel guest@MOF hybrid systems that will be useful for many MOF-based applications such as gas separations and chemical sensors performed under humid conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Early Detection of Drought Stress in Durum Wheat Using Hyperspectral Imaging and Photosystem Sensing

Wheat, being the third largest U.S. crop and the principal food grain, faces significant risks from climate extremes such as drought. This necessitates identifying and developing methods for early water-stress detection to prevent yield loss and improve water-use efficiency. This study investigates the potential of hyperspectral imaging to detect the early stages of drought stress in wheat. The goal is to utilize this technology as a tool for screening and selecting drought-tolerant wheat genotypes in breeding programs. Additionally, this research aims to systematically evaluate the effectiveness of various existing sensors and methods for detecting early stages of water stress. The experiment was conducted in a durum wheat experimental field trial in Maricopa, Arizona, in the spring of 2019 and included well-watered and water-limited treatments of a panel of 224 replicated durum wheat genotypes. Spectral indices derived from hyperspectral imagery were compared against other plant-level indicators of water stress such as Photosystem II (PSII) and relative water content (RWC) data derived from proximal sensors. Our findings showed a 12% drop in photosynthetic activity in the most affected genotypes when compared to the least affected. The Leaf Water Vegetation Index 1 (LWVI1) highlighted differences between drought-resistant and drought-susceptible genotypes. Drought-resistant genotypes retained 43.36% more water in leaves under well-watered conditions compared to water-limited conditions, while drought-susceptible genotypes retained only 15.69% more. The LWVI1 and LWVI2 indices, aligned with the RWC measurements, revealed a strong inverse correlation in the susceptible genotypes, underscoring their heightened sensitivity to water stress in earlier stages. Several genotypes previously classified based on their drought resistance showed spectral indices deviating from expectations. Results from this research can aid farmers in improving crop yields by informing early management practices. Moreover, this research offers wheat breeders insights into the selection of drought-tolerant genotypes, a requirement that is becoming increasingly important as weather patterns continue to change.

Roy, Bishal (ORCID:0000000199125505)↗
DOE OSTI2025

Estimating Switchgrass Biomass Yield and Lignocellulose Composition from UAV-Based Indices

Innovative methods for estimating commercial-scale switchgrass yields and feedstock quality are essential to optimize harvest logistics and biorefinery efficiency for sustainable aviation fuel production. This study utilized vegetation indices (VIs) derived from multispectral images to predict biomass yield and lignocellulose concentrations of advanced bioenergy-type switchgrass cultivars (“Liberty” and “Independence”) under two N rates (28 and 56 kg N ha –1 ). Field-scale plots were arranged in a randomized complete block design (RCBD) and replicated three times at Urbana, IL. Multispectral images captured during the 2021–2023 growing seasons were used to extract VIs. The results show that linear and exponential models outperformed partial least square and random forest models, with mid-August imagery providing the best predictions for biomass, cellulose, and hemicellulose. The green normalized difference vegetation index (GNDVI) was the best univariate predictor for biomass yield (R 2 = 0.86), while a multivariate combination of the GNDVI and normalized difference red-edge index (NDRE) enhanced prediction accuracy (R 2 = 0.88). Cellulose was best predicted using the NDRE (R 2 = 0.53), whereas hemicellulose prediction was most effective with a multivariate model combining the GNDVI, NDRE, NDVI, and green ratio vegetation index (GRVI) (R 2 = 0.44). These findings demonstrate the potential of UAV-based VIs for the in-season estimation of biomass yield and cellulose concentration.

09 BIOMASS FUELS↗
DOE OSTI2023

Data for Genome-Wide Association and Genomic Prediction for Yield and Component Traits of Miscanthus sacchariflorus

Accelerating biomass improvement is a major goal of miscanthus breeding. The development and implementation of genomic-enabled breeding tools, like marker-assisted selection (MAS) and genomic selection, has the potential to improve the efficiency of miscanthus breeding. The present study conducted genome-wide association (GWA) and genomic prediction of biomass yield and 14 yield-components traits in Miscanthus sacchariflorus . We evaluated a diversity panel with 590 accessions of M. sacchariflorus grown across four years in one subtropical and three temperate locations and genotyped with 268,109 single-nucleotide polymorphisms (SNPs). The GWA study identified a total of 835 significant SNPs and 674 candidate genes across all traits and locations. Of the significant SNPs identified, 280 were localized in mapped quantitative trait loci intervals and proximal to SNPs identified for similar traits in previously reported miscanthus studies, providing additional support for the importance of these genomic regions for biomass yield. Our study gave insights into the genetic basis for yield-component traits in M. sacchariflorus that may facilitate marker-assisted breeding for biomass yield. Genomic prediction accuracy for the yield-related traits ranged from 0.15 to 0.52 across all locations and genetic groups. Prediction accuracies within the six genetic groupings of M. sacchariflorus were limited due to low sample sizes. Nevertheless, the Korea/NE China/Russia (N = 237) genetic group had the highest prediction accuracy of all genetic groups (ranging 0.26–0.71), suggesting that with adequate sample sizes, there is strong potential for genomic selection within the genetic groupings of M. sacchariflorus . This study indicated that MAS and genomic prediction will likely be beneficial for conducting population-improvement of M. sacchariflorus .

Biomass Analytics↗
DOE OSTI2023

Investigating boosted decision trees as a guide for inertial confinement fusion design

Inertial confined fusion experiments at the National Ignition Facility have recently entered a new regime approaching ignition. Improved modeling and exploration of the experimental parameter space were essential to deepening our understanding of the mechanisms that degrade and amplify the neutron yield. The growing prevalence of machine learning in fusion studies opens a new avenue for investigation. Here in this paper, we have applied the Gradient-Boosted Decision Tree machine-learning architecture to further explore the parameter space and find correlations with the neutron yield, a key performance indicator. We find reasonable agreement between the measured and predicted yield, with a mean absolute percentage error on a randomly assigned test set of 35.5%. This model finds the characteristics of the laser pulse to be the most influential in prediction, as well as the hohlraum laser entrance hole diameter and an enhanced capsule fabrication technique. We used the trained model to scan over the design space of experiments from three different campaigns to evaluate the potential of this technique to provide design changes that could improve the resulting neutron yield. While these data-driven model cannot predict ignition without examples of ignited shots in the training set, it can be used to indicate that an unseen shot design will at least be in the upper range of previously observed neutron yields.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Methodology for assessing the maximum potential impact of separations opportunities in industrial processes

Separation technologies currently used in U.S. manufacturing industries are estimated to account for more than 20% of plant energy consumption. However, accurately determining the impact of new separation technology solutions can sometimes be difficult, especially when evaluating a slate of new candidate separation technologies, each of which has its own separation performance, energy demand, and capital cost. In these cases, a typical approach is to assess each new separation technology by collecting performance and cost information and then using that information to develop a techno-economic analysis to identify overall benefits. While this approach is thorough, it can be time consuming and can hinder reaching a critical understanding of the potential of a given separation challenge, especially when there is no known solution. To address these issues, we developed an assessment methodology, using industrial screening processes, that can be used to better understand the potential impacts of addressing a given separation challenge. This paper presents an overview of our separation challenge stream assessment methodology. The methodology involves defining an “ideal” separator and deriving the associated minimum separation energy. The “ideal” separator represents the most optimistic outlook of a given opportunity so the maximum impact from existing and not-yet-developed solutions can be assessed. Using established biorefinery models, we applied the methodology to 10 different separation challenge streams from two different biomass conversion platforms to identify the type of information that can be obtained. Three of the ten challenge streams assessed had maximum possible cost savings predictions >20%, and associated reductions in process energy carbon intensity ranging from 0 to 54%. Two streams had cost and energy savings potential that were < 5%. Some of the opportunity drivers from the various assessments include higher product yields, reduction or elimination of downstream equipment, new co-products, and cost savings associated with raw materials and energy consumption. The information from these assessments can help guide the selection or development of new separation technology solutions based on the various potential factors that drive the projected benefits.

09 BIOMASS FUELS↗
DOE OSTI2024

Engineered reduction of S-adenosylmethionine alters lignin in sorghum

Abstract Background Lignin is an aromatic polymer deposited in secondary cell walls of higher plants to provide strength, rigidity, and hydrophobicity to vascular tissues. Due to its interconnections with cell wall polysaccharides, lignin plays important roles during plant growth and defense, but also has a negative impact on industrial processes aimed at obtaining monosaccharides from plant biomass. Engineering lignin offers a solution to this issue. For example, previous work showed that heterologous expression of a coliphage S -adenosylmethionine hydrolase (AdoMetase) was an effective approach to reduce lignin in the model plant Arabidopsis. The efficacy of this engineering strategy remains to be evaluated in bioenergy crops. Results We studied the impact of expressing AdoMetase on lignin synthesis in sorghum ( Sorghum bicolor L. Moench). Lignin content, monomer composition, and size, as well as biomass saccharification efficiency were determined in transgenic sorghum lines. The transcriptome and metabolome were analyzed in stems at three developmental stages. Plant growth and biomass composition was further evaluated under field conditions. Results evidenced that lignin was reduced by 18% in the best transgenic line, presumably due to reduced activity of the S -adenosylmethionine-dependent O -methyltransferases involved in lignin synthesis. The modified sorghum features altered lignin monomer composition and increased lignin molecular weights. The degree of methylation of glucuronic acid on xylan was reduced. These changes enabled a ~20% increase in glucose yield after biomass pretreatment and saccharification compared to wild type. RNA-seq and untargeted metabolomic analyses evidenced some pleiotropic effects associated with AdoMetase expression. The transgenic sorghum showed developmental delay and reduced biomass yields at harvest, especially under field growing conditions. Conclusions The expression of AdoMetase represents an effective lignin engineering approach in sorghum. However, considering that this strategy potentially impacts multiple S -adenosylmethionine-dependent methyltransferases, adequate promoters for fine-tuning AdoMetase expression will be needed to mitigate yield penalty.

Tian, Yang↗