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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Twisted A-D-A Type Acceptors with Thermally-Activated Delayed Crystallization Behavior for Efficient Nonfullerene Organic Solar Cells

We report that molecular aggregation and crystallization during film coating play a crucial role in the realization of high-performing organic photovoltaics. Strong intermolecular interactions and high solid-state crystallinity are beneficial for charge transport. However, fast crystallization during thin-film drying often limits the formation of the finely phase-separated morphology required for efficient charge generation. Herein, the authors show that twisted acceptor-donor-acceptor (A-D-A) type compounds, containing an indacenodithiophene (IDT) electron-rich core and two naphthalenediimide (NDI) electron-poor units, leads to formation of mostly amorphous phases in the as-cast film, which can be readily converted into more crystalline domains by means of thermal annealing. This design strategy solves the aforementioned conundrum, leading to an optimal morphology in terms of reduced donor/acceptor domain-separation sizes (ca. 13 nm) and increased packing order. Solar cells based on these acceptors with a PBDB-T polymer donor show a power conversion efficiency over 10% and stable morphology, which results from the combined properties of desirable excited-state dynamics, high charge mobility, and optimal aggregation/crystallization characteristics. These results demonstrate that the twisted A-D-A motif featuring thermally-induced crystallization behavior is indeed a promising alternative design approach toward more morphologically robust materials for efficient organic photovoltaics.

14 SOLAR ENERGY↗
NASA NTRSDate not supplied

How the Open Data Policy of the Landsat Program Has Advanced Our Understanding of Environmental Change

A time series is a sequence of observations of a phenomenon taken sequentially in time. A crucial characteristic of a time series is the dependence among adjacent observations – techniques for analyzing this dependence are referred to as time series analysis. This analytical approach enables us to predict or forecast future values of a time series, study the impact of various inputs on the observed phenomenon, and examine interrelationships among related time series variables. Within the geographical sciences, time series analysis has historically been limited to coarse-resolution satellite data, as constructing time series of data suitable for studying land cover and land use dynamics, such as Landsat data, were prohibitively costly. A transformative shift occurred in 2008 when the U.S. Government decided to make free and open all past and future data collected by the Landsat satellite program. The decision brought about a paradigm shift away from analyzing individual images or observations to continuous monitoring in time. Of particular relevance to environmental remote sensing is the ability to forecast observations – if we can predict how future observations should behave, we can infer information about how the land surface is changing. In this presentation, we will examine literature examples that showcase scientific gains enabled by time series analysis of satellite data. We will delve into how the analysis of dense time series of satellite data revealed that overall rate of forest disturbance in the Amazon has increased despite a reduction in deforestation; how different types of forest degradation, previously unquantified, are now being accurately assessed in the Caucasus region; and how we now can study the highly dynamic and intricate patterns of shifting cultivation in Southeast Asia.

Pontus Olofsson↗
DOE OSTI2022

Enabling Production of Algal Biofuels by Techno-Economic Optimization of Co-Product Suites

Recent techno-economic analysis (TEA) has underscored that for algal biofuels to be cost competitive with petroleum fuels, co-products are necessary to offset the cost of fuel production. The co-product suite must scale with fuel production while also maximizing value from the non-fuel precursor components. The co-product suite also depends on algal biomass composition, which is highly dynamic and depends on environmental conditions during cultivation. Intentional shifts in composition during cultivation are often associated with reduced biomass productivity, which can increase feedstock production costs for the algae-based biorefinery. The optimal algae-based biorefinery configuration is thus a function of many factors. We have found that comprehensive TEA, which requires the construction of process models with detailed mass and energy balances, along with a complete accounting of capital and operating expenditures for a commercial-scale production facility, provides invaluable insight into the viability of a proposed biorefinery configuration. This insight is reflected in improved viability for one biorefining approach that we have developed over the last 10 years, namely, the Combined Algal Processing (CAP) approach. This approach fractionates algal biomass into carbohydrate-, lipid-, and protein-rich fractions, and tailors upgrading chemistry to the composition of each fraction. In particular, transitioning from valorization of only the lipids to a co-product suite from multiple components of high-carbohydrate algal biomass can reduce the minimum fuel selling price (MFSP) from more than $8/gallon of gasoline equivalent (GGE) to $2.50/GGE. This paper summarizes that progress and discusses several surprising implications in this optimization approach.

09 BIOMASS FUELS↗
DOE OSTI2021

Reynolds stress tensor measurements using magnetic resonance velocimetry: expansion of the dynamic measurement range and analysis of systematic measurement errors

This study presents magnetic resonance velocimetry (MRV) Reynolds Stress measurements in a periodic hill channel with a hill Reynolds number of Re = 29,500. The velocity encoding scheme is based on the ICOSA6 method with six icosahedral encoding directions and multiple encoding values are measured to increase the dynamic range. The full Reynolds stress tensor is obtained from a voxel-wise three-dimensional Gaussian fit using the magnitude data of all acquisitions. The MRV results are compared to a wall-resolved large eddy simulation and laser Doppler velocimetry measurements conducted in the same channel. It is shown that the MRV Reynolds stress data have excellent precision and agree qualitatively with the reference data. However, there are apparent systematic deviations. One of the most prominent error contributions is the signal attenuation caused by higher orders of motion, which leads to an overestimation of the turbulence level. Another fundamental error is identified in the assumption that the turbulence is Gaussian distributed. With the presented reconstruction technique, the MRV data are fitted to a statistical model, and depending on the examined flow setup, the Gaussian model can lead to considerable errors. Possible ways of how to reduce all identified errors are presented. In summary, this technique enables Reynolds stress tensor measurements in complex internal flows with high dynamic range and excellent precision. However, several issues need to be resolved to make the turbulence quantification more accurate.

42 ENGINEERING↗
DOE OSTI2023

Data-driven prediction of geometry- and toolpath sequence-dependent intra-layer process conditions variations in laser powder bed fusion

Geometrical features and toolpath sequence are two important factors that cause process condition variations, such as variations in the meltpool temperature or meltpool size, that might lead to undesired material properties in the laser powder bed fusion (LPBF) process. Due to the high dynamics and complex physics of the LPBF process, it is difficult to predict variations in process conditions with simulations alone. Advances in measurement technology and computational technologies open up new possibilities for smart manufacturing. In this paper, a data-driven method to predict intra-layer variations in the processing conditions that source from the toolpath sequence and part geometry is presented. The approach is demonstrated using two-color on-axis pyrometer measurements. Three demonstration cases are presented in which it is demonstrated (1) how the trained predictive model can be used as a filter to ease the interpretation of process variations and discover patterns related to toolpath and part geometry, and (2) how to generate predictions that can be used for feedforward control, i.e., for adjusting laser power or scanning speed along the toolpath using a meltpool temperature prediction model generated based on on-axis measurements. Results show that the developed prediction model is able to meaningfully predict process variations resulted from toolpath sequence and geometry. Predictions are aligned with the results from the related work of others and for the case of 180° laser path turnarounds in our high-speed X-ray imaging experiments. In conclusion, the potential issues related to the current maturity status of the process and measuring equipment that could in practice affect the performance of the proposed solutions are also discussed.

42 ENGINEERING↗
NASA NTRS2020

Overview of Coupon Testing of an IM7/8552 Composite Required to Characterize High-Energy Impact Dynamic Material Models

As part of NASA’s Advanced Composites Project (ACP), a significant research effort was established to develop and mature analysis methods for composite materials particularly applicable to high-energy dynamic impact applications. An overall goal was to develop and advance analysis methods that can be characterized using fundamental coupon level tests. Based on this fundamental characterization, simulations at the higher levels of a building block approach can be purely predictive. The tests described in this report were performed on a unidirectional carbon fiber polymer matrix composite, IM7/8552 tape, as this material system is representative of a modern aerospace grade carbon fiber tape system. These tests were chosen to provide fundamental material characterization data for three representative progressive damage and failure analysis material models available within the LS-DYNA commercial transient dynamic finite element code for use in the simulation of the dynamic and impact response of composite materials. Two of the material models, MAT162 and MAT261, are well established material models within LS-DYNA. The third material model, MAT213, is under active development. Testing consisted primarily of ASTM-type standard tests, and the tests that were performed were consistent with the needs of all three models. Additionally, coupon level tests were performed that can be used to characterize a delamination model (e.g., cohesive zone or tie-break contact). While, the tests described in this report provide fundamental material characterization data for all three of the material models mentioned above, the data is applicable to additional material models not discussed.

Justusson, Brian P.↗
DOE OSTI2021

In Situ X-ray Diffraction of High Density Polyethylene During Dynamic Compression: Polymer Chain Compression and Phase Transformations

Polymers are widely implemented materials often used for safety and security in our daily lives. However, we do not have a thorough understanding of the phase transformations of these materials when exposed to extreme condition, high strain rate, events. To study polymers in these severe environments, we performed plate impact experiments that impart a one-dimensional shock wave, at high pressures and temperatures, to observe the materials response. Generally, velocimetry is the experimental diagnostic used to capture the movement of high velocity interfaces to then calculate the mechanical variables associated with shock compression. However, when a material undergoes a phase transition, such as between two crystalline phases or melting to decomposition during shock compression, velocimetry does not explicitly indicate what structural change occurred. At the Dynamic Compression Sector at the Advanced Photon Source gas gun driven compression has been paired with x-ray diffraction, providing the ability to study both the shock parameters and structural changes concurrently. We explored high density polyethylene (HDPE) both on its reactants Hugoniot (<10.12 GPa) and within its transition region (24.3 GPa) where HDPE is hypothesized to decompose from reactants to products. With x-ray diffraction we observed both polymer chain compression and crystal structure reorientation from orthorhombic to monoclinic above 6 GPa, as well as either a possible phase change or chemical decomposition at 24.3 GPa. With these experiments we were able to determine the crystalline and amorphous Hugoniot loci at pressures below the polymer transition region.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Ecohydrology of wetland plant communities along an estuarine to tidal river gradient

Abiotic filters that interact with wetland plant communities along tidal–fluvial gradients are highly dynamic, and understanding their quantitative thresholds and relationships to interspecific competition is important during an era of sea-level rise and watershed hydrologic change. Yet, landscape-scale studies of major coastal rivers from the river mouth to the head of tide, such as this study, remain rare. Here, we develop a new predictive framework for estuarine–tidal river research and management using a river-specific low-water datum and the wetland inundation indicator SEVg, the growing-season sum exceedance value of hourly surface-water depth. The distribution and variability of the wetland species pool (n = 203) on the 234 river kilometer (rkm) lower Columbia River and estuary floodplain are described for the first time. 4,940 quadrats at 50 marshes were surveyed (2005–2016). Throughout the estuarine–tidal river system, SEVg was well suited to describe the wetland inundation regime and its variability based on the combination of longitudinal river position and elevation. SEVg increased significantly landward. Two primary wetland inundation regimes were identified: the seaward-tidal, usually greatest during the winter months, and landward-fluvial, greatest during the growing season. Nearest the ocean, salinity is the abiotic factor limiting species richness and non-native species. Farther upriver, the daily, seasonal, and interannual variability of the wetting and drying cycle encourage disturbance-tolerant species and non-natives and limit the number of hydrophytes and total vegetative cover. Hence, the average between-year similarity of site-scale areal cover significantly decreased landward. Hierarchical cluster analysis indicated five vegetative groups and five ecohydrologic zones between rkm 0 and 234 were discriminated with 76 significant species–zone associations. All zones had unique indicator species. Species with high indicator values were Carex lyngbyei throughout the estuarine zones, and Eleocharis palustris, Sagittaria latifolia, and the invasive non-native Phalaris arundinacea in the upper estuarine and lower, middle, and upper tidal river zones (IV > 0.90). Competition from C. lyngbyei nearest the ocean and P. arundinacea in the tidal river was associated with reduced species richness when total cover was >65%. This framework of filters informs the design and prediction of future wetland plant communities on coastal river floodplains.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Stabilizing the Grid and Reducing Utility Bills Through Price-Responsive Controls for Heat Pump Water Heaters

The electricity grid is facing increasing challenges in cost-effectively balancing supply and demand. These challenges are exacerbated by increased penetration of photovoltaics, which causes mid-day overproduction, and electrification of gas appliances, which increases peak-period electricity demand. Decarbonization requires shifting building loads from fossil-intensive high-cost times to renewable-intensive low-cost times while maintaining quality of service to occupants. Utilities and ISO’s are investigating new ways of incentivizing this load shifting. One promising method is the use of Highly Dynamic Prices (HDPs). HDPs feature continuously changing prices that reflect real-time grid generation and distribution costs and capacity constraints, and thus incentivize consumers to shift their loads. California’s CPUC CalFUSE proposal and Hawaii’s recent changes demonstrate that electricity tariffs are moving towards this model. For this to work however, loads must have the capability to respond to these prices. Heat pump water heaters (HPWHs) are an ideal device for this purpose because their storage tanks decouple delivery of domestic hot water from electricity consumption. The storage enables control strategies that consume midday solar power to increase the energy stored in the tank, then provide evening peak domestic hot water services using the stored energy. Berkeley Lab's CalFlexHub project is pioneering price-driven load flexibility by developing and deploying cost-minimizing controls for many flexible loads - including HPWHs - in response to HDP. Control development is based on simulations using the Flexible Heat Pump Water Heater Performance Predictor which captures the control decisions of the on-board controller in a residential, integrated HPWH . The price-responsive controls a) shift load in ways that consume additional midday solar power to help stabilize the grid and reduce overall emissions, b) ensure that occupants receive equal or better hot water delivery service, and c) minimize the operating cost for each home in the fleet. On the grid level, the resulting shift will reduce utility operating costs and emissions, and can avoid expensive system capacity expansions. The control approach is customized to each home based on typical hot water consumption patterns. HPWH controllers, whether on the device or remotely, will receive a schedule of CTA-2045-B signals or set temperature adjustments customized to the current HDP price schedule and home. Simulation results for a fleet of 148 HPWHs on a summer day in Berkeley, California show cost savings of 29% and high price electricity consumption reductions of 80%, while maintaining full quality of service.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Digital coded exposure formation of frames from event-based imagery

Abstract Event-driven neuromorphic imagers have a number of attractive properties including low-power consumption, high dynamic range, the ability to detect fast events, low memory consumption and low band-width requirements. One of the biggest challenges with using event-driven imagery is that the field of event data processing is still embryonic. In contrast, decades worth of effort have been invested in the analysis of frame-based imagery. Hybrid approaches for applying established frame-based analysis techniques to event-driven imagery have been studied since event-driven imagers came into existence. However, the process for forming frames from event-driven imagery has not been studied in detail. This work presents a principled digital coded exposure approach for forming frames from event-driven imagery that is inspired by the physics exploited in a conventional camera featuring a shutter. The technique described in this work provides a fundamental tool for understanding the temporal information content that contributes to the formation of a frame from event-driven imagery data. Event-driven imagery allows for the application of arbitrary virtual digital shutter functions to form the final frame on a pixel-by-pixel basis. The proposed approach allows for the careful control of the spatio-temporal information that is captured in the frame. Furthermore, unlike a conventional physical camera, event-driven imagery can be formed into any variety of possible frames in post-processing after the data is captured. Furthermore, unlike a conventional physical camera, coded-exposure virtual shutter functions can assume arbitrary values including positive, negative, real, and complex values. The coded exposure approach also enables the ability to perform applications of industrial interest such as digital stroboscopy without any additional hardware. The ability to form frames from event-driven imagery in a principled manner opens up new possibilities in the ability to use conventional frame-based image processing techniques on event-driven imagery.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Static and dynamic properties of atomic nuclei with high-resolution potentials

Here, we compute ground-state and dynamical properties of 4 He and 16 O nuclei using as input high-resolution, phenomenological nucleon-nucleon and three-nucleon forces that are local in coordinate space. The nuclear Schrodinger equation for both nuclei is accurately solved employing the auxiliary-field diffusion Monte Carlo approach. For the 4 He nucleus, detailed benchmarks are carried out with the hyperspherical harmonics method. In addition to presenting results for the binding energies and radii, we also analyze the momentum distributions of these nuclei and their Euclidean response function corresponding to the isoscalar density transition. The latter quantity is particularly relevant for lepton-nucleus scattering experiments, as it paves the way to quantum Monte Carlo calculations of electroweak response functions of 16 O.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Terahertz Detection Using Enhanced Two‐Step Absorption in Photoconductive Metasurfaces Gated at λ = 1.55 µm

Abstract Superior ultrafast photoconductive properties make low temperature grown (LT) GaAs one of the best materials for photoconductive terahertz (THz) detection. However, the large bandgap of LT‐GaAs limits its operation to gating at wavelengths shorter than 870 nm. Here, it is demonstrated for the first time that nanostructuring the LT‐GaAs into a highly absorbing metasurface enables THz photoconductive detection with a pulsed laser at λ = 1.55 µm. The very weak sub‐bandgap absorption mediated by midgap states in LT‐GaAs is strongly enhanced using the concept of perfect absorption via degenerate critical coupling. Integrated with a THz antenna, the LT‐GaAs metasurface enables high sensitivity THz detection with a high dynamic range of 60 dB and large bandwidth up to 4.5 THz. The LT‐GaAs metasurface has the potential to serve as a universal ultrafast switching element for THz applications, enabling low‐cost, turn‐key THz systems for a variety of real‐world applications.

Jung, Hyunseung↗
DOE OSTI2025

Materials Selection Principles for Designing Electro‐Thermal Neurons

Artificial neurons exhibiting volatile threshold switching and action potential‐like oscillations are crucial for brain‐inspired computing. While Complimentary Metal‐Oxide‐Semiconductor (CMOS)‐based strategies require hundreds of transistors to simulate each neuron, neuronal oscillations arise spontaneously in individual electro‐thermal devices due to nonlinearities like the Mott transition in VO 2 . Despite improved understanding of the physics, quantitative connections between neuronal performance and material properties remain under‐explored, preventing predictive neuron design and rational materials selection. In this work, a physics‐aware forward design methodology is developed for interrogating a wide palette of materials with properties varying by orders of magnitude, and their performance (high frequency, high dynamical reconfigurability and low power) under external circuit and device geometry constraints is assessed. The space of viable materials is identified to be much larger than previously recognized, with candidates from a range of materials classes, including Ge, GaP and MoS 2 . CMOS‐compatible performance (such as 100 GHz oscillating frequencies) can be achieved with CMOS‐compatible node sizes (≈10 nm). Finally, combinations of material properties yielding desired neuronal performance under uncertain design constraints are considered. This work solidifies forward design principles for electro‐thermal neuron devices, a necessary pre‐condition for inverse design from desired neuronal performance to required materials properties.

compact model↗
DOE OSTI2025

Why are Lead Iodide‐Based Perovskite Precursor Inks Yellow?

A challenge faced by metal halide perovskite (MHP) photovoltaics is scaling up solution deposition processes to realize rapid and inexpensive manufacturing. The challenge lies in completely understanding and controlling solution speciation, nucleation, and self-assembly of iodoplumbate complexes during solvent evaporation as the liquid transforms into gels and solids. An accurate description of solution species, at all points in the transformation, is a prerequisite to design robust and reliable processes. Here, in this study, the common assumption that initial monoplumbate solution species typically invoked (e.g., [PbI 6 ] 4− ) are certainly not the origin of optical absorbance at >400 nm wavelengths is disproved, as are many large particles of common “intermediate” iodoplumbate phases with face- or edge-sharing connectivity. Instead, a new perspective is offered, involving (partially) corner-sharing iodo(poly)plumbates (>1 Pb 2+ per complex) that experience highly dynamic chemical environments. It is outlined how the MHP field would benefit by elucidating these phenomena. Future work is required to determine the size and kinetic behavior of polyplumbate species, and contextualize these findings in relation to broader trends in materials chemistry beyond MHPs. Ultimately, a complete explanation for the solution speciation, optical absorbance signatures, and the color of MHP precursor inks remains an open challenge to the community.

14 SOLAR ENERGY↗
DOE OSTI2023

Real-time control of connected vehicles in signalized corridors using pseudospectral convex optimization

Recent advances in Connected and Automated Vehicle (CAV) technologies have opened up new opportunities to enable safe, efficient, and sustainable transportation systems. However, developing reliable and rapid speed control algorithms in highly dynamic environments with complex inter-vehicle interactions and nonlinear vehicle dynamics is still a daunting task. In this paper, we develop a novel speed control method for CAVs to produce optimal speed profiles that minimize the fuel consumption and avoid idling at signalized intersections. To this end, an optimal control problem is formulated using the information of the upcoming traffic signal to adapt vehicles' speeds to avoid frequent stop-and-go driving patterns. Here, by applying the pseudospectral discretization method and the sequential convex programming method, the computational efficiency is greatly improved, enabling potential real-time on-vehicle applications. In addition, the algorithm is implemented under a model predictive control framework to ensure online control with instant response for collision avoidance and robust vehicle coordination. The proposed algorithm is verified through numerical simulations of three different traffic scenarios. The convergence and accuracy of the proposed approach are demonstrated by comparing with a popular nonlinear solver. Furthermore, the benefit of the proposed method in both traffic mobility and fuel efficiency is validated using the speed profile determined from a traffic following model in a simulation software as the baseline.

42 ENGINEERING↗
DOE OSTI2022

The Arabidopsis T‐DNA mutant SALK_008491 carries a 14‐kb deletion on chromosome 3 that provides rare insights into the plant response to dynamic light stress

Abstract In nature, plants experience rapid changes in light intensity and quality throughout the day. To maximize growth, they have established molecular mechanisms to optimize photosynthetic output while protecting components of the light‐dependent reaction and CO 2 fixation pathways. Plant phenotyping of mutant collections has become a powerful tool to unveil the genetic loci involved in environmental acclimation. Here, we describe the phenotyping of the transfer‐DNA (T‐DNA) insertion mutant line SALK_008491, previously known as nhd1‐1 . Growth in a fluctuating light regime caused a loss in growth rate accompanied by a spike in photosystem (PS) II damage and increased non‐photochemical quenching (NPQ). Interestingly, an independent nhd1 null allele did not recapitulate the NPQ phenotype. Through bulk sequencing of a backcrossed segregating F 2 pool, we identified an ~14‐kb large deletion on chromosome 3 (Chr3) in SALK_008491 affecting five genes upstream of NHD1 . Besides NHD1 , which encodes for a putative plastid Na + /H + antiporter, the stromal NAD‐dependent D‐3‐phosphoglycerate dehydrogenase 3 ( PGDH3 ) locus was eradicated. Although some changes in the SALK_008491 mutant's photosynthesis can be assigned to the loss of PGDH3, our follow‐up studies employing respective single mutants and complementation with overlapping transformation‐competent artificial chromosome (TAC) vectors reveal that the exacerbated fluctuating light sensitivity in SALK_008491 mutants result from the simultaneous loss of PGDH3 and NHD1. Altogether, the data obtained from this large deletion‐carrying mutant provide new and unintuitive insights into the molecular mechanisms that function to protect the photosynthetic machinery. Moreover, our study renews calls for caution when setting up reverse genetic studies using T‐DNA lines. Although second‐site insertions, indels, and SNPs have been reported before, large deletion surrounding the insertion site causes yet another problem. Nevertheless, as shown through this research, such unpredictable genetic events following T‐DNA mutagenesis can provide unintuitive insights that allow for understanding complex phenomena such as the plant acclimation to dynamic high light stress.

Lopez, Laura S.↗
DOE OSTI2023

Functional analysis of Salix purpurea genes support roles for ARR17 and GATA15 as master regulators of sex determination

Abstract The Salicaceae family is of growing interest in the study of dioecy in plants because the sex determination region (SDR) has been shown to be highly dynamic, with differing locations and heterogametic systems between species. Without the ability to transform and regenerate Salix in tissue culture, previous studies investigating the mechanisms regulating sex in the genus Salix have been limited to genome resequencing and differential gene expression, which are mostly descriptive in nature, and functional validation of candidate sex determination genes has not yet been conducted. Here, we used Arabidopsis to functionally characterize a suite of previously identified candidate genes involved in sex determination and sex dimorphism in the bioenergy shrub willow Salix purpurea . Six candidate master regulator genes for sex determination were heterologously expressed in Arabidopsis, followed by floral proteome analysis. In addition, 11 transcription factors with predicted roles in mediating sex dimorphism downstream of the SDR were tested using DAP‐Seq in both male and female S. purpurea DNA. The results of this study provide further evidence to support models for the roles of ARR17 and GATA15 as master regulator genes of sex determination in S. purpurea , contributing to a regulatory system that is notably different from that of its sister genus Populus . Evidence was also obtained for the roles of two transcription factors, an AP2 / ERF family gene and a homeodomain‐like transcription factor, in downstream regulation of sex dimorphism.

60 APPLIED LIFE SCIENCES↗