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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 199 records · Page 11

Cross-national analysis of food security drivers: comparing results based on the Food Insecurity Experience Scale and Global Food Security Index

Abstract The second UN Sustainable Development Goal establishes food security as a priority for governments, multilateral organizations, and NGOs. These institutions track national-level food security performance with an array of metrics and weigh intervention options considering the leverage of many possible drivers. We studied the relationships between several candidate drivers and two response variables based on prominent measures of national food security: the 2019 Global Food Security Index (GFSI) and the Food Insecurity Experience Scale’s (FIES) estimate of the percentage of a nation’s population experiencing food security or mild food insecurity (FI ). We compared the contributions of explanatory variables in regressions predicting both response variables, and we further tested the stability of our results to changes in explanatory variable selection and in the countries included in regression model training and testing. At the cross-national level, the quantity and quality of a nation’s agricultural land were not predictive of either food security metric. We found mixed evidence that per-capita cereal production, per-hectare cereal yield, an aggregate governance metric, logistics performance, and extent of paid employment work were predictive of national food security. Household spending as measured by per-capita final consumption expenditure (HFCE) was consistently the strongest driver among those studied, alone explaining a median of 92% and 70% of variation (based on out-of-sample R 2 ) in GFSI and FI , respectively. The relative strength of HFCE as a predictor was observed for both response variables and was independent of the countries used for model training, the transformations applied to the explanatory variables prior to model training, and the variable selection technique used to specify multivariate regressions. The results of this cross-national analysis reinforce previous research supportive of a causal mechanism where, in the absence of exceptional local factors, an increase in income drives increase in food security. However, the strength of this effect varies depending on the countries included in regression model fitting. We demonstrate that using multiple response metrics, repeated random sampling of input data, and iterative variable selection facilitates a convergence of evidence approach to analyzing food security drivers.

42 ENGINEERING↗

Modern Approaches to Exact Diagonalization and Selected Configuration Interaction with the Adaptive Sampling CI Method

Recent advances in selected configuration interaction methods have made them competitive with the most accurate techniques available and, hence, creating an increasingly powerful tool for solving quantum Hamiltonians. In this work, we build on recent advances from the adaptive sampling configuration interaction (ASCI) algorithm. We show that a useful paradigm for generating efficient selected CI/exact diagonalization algorithms is driven by fast sorting algorithms, much in the same way iterative diagonalization is based on the paradigm of matrix vector multiplication. We present several new algorithms for all parts of performing a selected CI, which includes new ASCI search, dynamic bit masking, fast orbital rotations, fast diagonal matrix elements, and residue arrays. The ASCI search algorithm can be used in several different modes, which includes an integral driven search and a coefficient driven search. The algorithms presented here are fast and scalable, and we find that because they are built on fast sorting algorithms they are more efficient than all other approaches we considered. After introducing these techniques, we present ASCI results applied to a large range of systems and basis sets to demonstrate the types of simulations that can be practically treated at the full-CI level with modern methods and hardware, presenting double- and triple-ζ benchmark data for the G1 data set. The largest of these calculations is Si$_2$H$_6$ which is a simulation of 34 electrons in 152 orbitals. We also present some preliminary results for fast deterministic perturbation theory simulations that use hash functions to maintain high efficiency for treating large basis sets.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Structural mode coupling in perovskite oxides using hypothesis-driven active learning

Abstract Finding the ground-state structure with minimum energy is paramount to designing any material. In ABO 3 -type perovskite oxides with Pnma symmetry, the lowest energy phase is driven by an inherent trilinear coupling between the two primary order parameters such as rotation and tilt with antiferroelectric displacement of the A-site cations as established via hybrid improper ferroelectric mechanism. Conventionally, finding the relevant mode coupling driving phase transition requires performing first-principles calculations which is computationally time-consuming as well as expensive. It involves following an intuitive iterative hit and trial method of (a) adding two or multiple mode vectors, followed by (b) evaluating which combination would lead to the ground-state energy. In this study, we show how a hypothesis-driven active learning framework can identify suitable mode couplings within the Landau free energy expansion with minimal information on amplitudes of modes for a series of double perovskite oxides with A-site layered, columnar and rocksalt ordering. This scheme is expected to be applicable universally for understanding atomistic mechanisms derived from various structural mode couplings behind functionalities, for e.g. polarization, magnetization and metal–insulator transitions.

36 MATERIALS SCIENCE↗

Optimal shield mass distribution for space radiation protection

Computational methods have been developed and successfully used for determining the optimum distribution of space radiation shielding on geometrically complex space vehicles. These methods have been incorporated in computer program SWORD for dose evaluation in complex geometry, and iteratively calculating the optimum distribution for (minimum) shield mass satisfying multiple acute and protected dose constraints associated with each of several body organs.

Billings, M. P.↗

Sharply curved turn around duct flow predictions using spectral partitioning of the turbulent kinetic energy and a pressure modified wall law

Computational predictions of turbulent flow in sharply curved 180 degree turn around ducts are presented. The CNS2D computer code is used to solve the equations of motion for two-dimensional incompressible flows transformed to a nonorthogonal body-fitted coordinate system. This procedure incorporates the pressure velocity correction algorithm SIMPLE-C to iteratively solve a discretized form of the transformed equations. A multiple scale turbulence model based on simplified spectral partitioning is employed to obtain closure. Flow field predictions utilizing the multiple scale model are compared to features predicted by the traditional single scale k-epsilon model. Tuning parameter sensitivities of the multiple scale model applied to turn around duct flows are also determined. In addition, a wall function approach based on a wall law suitable for incompressible turbulent boundary layers under strong adverse pressure gradients is tested. Turn around duct flow characteristics utilizing this modified wall law are presented and compared to results based on a standard wall treatment.

Santi, L. Michael↗

Managing Science Operations During Planetary Surface: The 2010 Desert RATS Test

Desert Research and Technology Studies (Desert RATS) is a multi-year series of hardware and operations tests carried out annually in the high desert of Arizona on the San Francisco Volcanic Field. Conducted since 1997, these activities are designed to exercise planetary surface hardware and operations in conditions where long-distance, multi-day roving is achievable. Such activities not only test vehicle subsystems through extended rough-terrain driving, they also stress communications and operations systems and allow testing of science operations approaches to advance human and robotic surface capabilities. Desert RATS is a venue where new ideas can be tested, both individually and as part of an operation with multiple elements. By conducting operations over multiple yearly cycles, ideas that make the cut can be iterated and tested during follow-on years. This ultimately gives both the hardware and the personnel experience in the kind of multi-element integrated operations that will be necessary in future human planetary exploration.

Eppler, Dean B.↗

Technology Infusion in U.S. Spacesuits - A Comparative System Analysis

The National Aeronautics and Space Administration (NASA) has evolved multiple spacesuit systems for performing extravehicular activity (EVA) or space walks. These spacesuit systems include the Apollo Extravehicular Mobility Unit (EMU), Space Shuttle and International Space Station (ISS) EMU, and Exploration EMU (xEMU). Each spacesuit system is like the other for functionality. However, each spacesuit system is different in configuration based on the technology infused into the system associated with the purpose of the mission. Each spacesuit system is made up of many components and the integrate environment targeted for operations leads to an integrated system that is complex. Since Apollo, NASA has invested in multiple technologies that make up these spacesuit systems in different iterations. The Apollo EMU was designed in the 1960’s with a focus to facilitate the first human to walk on the moon. The Space Shuttle EMU was designed in the 1970’s for reusable microgravity operations that began in the early 1980’s. The Space Shuttle EMU was enhanced to facilitate extended operation on the ISS. Over the last 15 years, NASA has been designing, developing, and testing a new spacesuit system, the xEMU which is considered a design, verification, and test unit. NASA is planning to land the first woman and first person of color on the Moon. NASA recently engaged industry through a new contractual arrangement to provide EVA services needed to return to the Moon and to continue operations on the ISS. Spacesuit systems are complex. Understanding the requirements, operational environment, the necessary technologies, and the integrated spacesuit system are paramount. In addition, understanding the technology infusion process to meet the mission objectives is critical. This paper will review the spacesuit systems for EVA and several component functions within the spacesuits, along with a system comparison of those technologies from Apollo to xEMU.

Extravehicular Activity (EVA)↗

A Novel Multi-Spacecraft Interplanetary Global Trajectory Optimization Transcription

As the frontier of space exploration continues to advance, so does the design complexity of future interplanetary missions. One avenue of this increasing complexity includes a class of designs known as "Distributed Spacecraft Missions"; missions where multiple spacecraft coordinate to perform shared objectives. Current approaches for the global trajectory optimization of these Multi-Vehicle Missions (MVMs) are prone to shortcomings including laborious iterative design, considerable human-in-the-loop effort, treatment of the multi-vehicle problem as multiple separate trajectory optimization subproblems (resulting in suboptimal solutions where the whole is less than the sum of its parts), and poor handling of coordination objectives and constraints. There are only a handful of software platforms in existence capable of fully-automated, rapid, interplanetary mission and systems global optimization including the Parallel Global Multiobjective Optimizer (PaGMO), the Gravity Assisted Low-thrust Local Optimization Program (GALLOP), and the Evolutionary Mission Trajectory Generator (EMTG). However, none of these tools is capable of performing such tasks for MVM designs. The work outlined in this paper lays the groundwork for a technique to begin addressing these shortcomings. We present a fully-automated technique which frames interplanetary MVMs as Multi-Objective, Multi-Agent Hybrid Optimal Control Problems (MOMA HOCP). First, the basic functionality of this technique is validated on the single-vehicle problem of reproducing the Cassini interplanetary cruise.

Interplanetary↗

A Novel Multi-Spacecraft Interplanetary Global Trajectory Optimization Transcription

As the frontier of space exploration continues to advance, so does the design complexity of future interplanetary missions. One avenue of this increasing complexity includes a class of designs known as ``Distributed Spacecraft Missions"; missions where multiple spacecraft coordinate to perform shared objectives. Current approaches for the global trajectory optimization of these Multi-Vehicle Missions (MVMs) are prone to shortcomings including laborious iterative design, considerable human-in-the-loop effort, treatment of the multi-vehicle problem as multiple separate trajectory optimization subproblems (resulting in suboptimal solutions where the whole is less than the sum of its parts), and poor handling of coordination objectives and constraints. There are only a handful of software platforms in existence capable of fully-automated, rapid, interplanetary mission and systems global optimization including the Parallel Global Multiobjective Optimizer (PaGMO), the Gravity Assisted Low-thrust Local Optimization Program (GALLOP), and the Evolutionary Mission Trajectory Generator (EMTG). However, none of these tools is capable of performing such tasks for MVM designs. The work outlined in this paper lays the groundwork for a technique to begin addressing these shortcomings. We present a fully-automated technique which frames interplanetary MVMs as Multi-Objective, Multi-Agent Hybrid Optimal Control Problems (MOMA HOCP). First, the basic functionality of this technique is validated on the single-vehicle problem of reproducing the Cassini interplanetary cruise.

Napier, Sean W.↗

Articulated figure positioning by multiple constraints

A problem that arises in positioning an articulated figure is the solution of three-dimensional joint positions (kinematics) when goal positions, rather than joint angles, are given. If more than one such goal is to be achieved, the problem is often solved interactively by positioning or solving one component of the linkage, then adjusting another, then redoing the first, and so on. This iterative process is slow and tedious. The paper presents a method that automatically solves multiple simultaneous joint position goals. The user interface offers a six-degree-of-freedom input device to specify joint angles and goal positions interactively. Examples are used to demonstrate the power and efficiency of this method for key-position animation.

Badler, Norman I.↗

A Mixed Integer Efficient Global Optimization Algorithm with Multiple Infill Strategy - Applied to a Wing Topology Optimization Problem

With the advancement in high performance computing and numerical optimization techniques,engineering design optimization problems are becoming more complex, larger scale,higher fidelity, and computationally more demanding, requiring longer run times than ever before. There exists methodologies and techniques that can address some of these challenges but very few can address all, and most are limited in the extent that these concerns can be addressed. With the goal of addressing such challenging engineering problems, we developed anew optimization framework, named AMIEGO, that combines concepts from surrogate-based optimization approaches, gradient-based numerical methods, Partial Least Squares, evolutionary algorithms, and Branch-and-Bound, providing newer capabilities that were not previouslyperceived. However, the original version of this framework, in the process of adaptive samplingto explore and exploit the design space, finds only a single sample point per iteration. The efforthere builds upon this previously developed optimization framework to include multiple infillsampling capability that combines the concept of generalized expected improvement function,unsupervised learning, and multi-objective evolutionary technique. To demonstrate, AMIEGOwith the multiple infill capability (called AMIEGO-MIMOS) solves a series of increasingly difficultengineering design optimization problems. The results reveal the performance of the newapproach is problem dependent. When applied to a ten-bar truss problem, the newly proposedmultiple infill strategy consistently leads to a better design solutions when compared to theexisting CPTV method (implemented with the context of the AMIEGO framework). On theother hand, when applied to a mixed-integer high fidelity wing topology optimization problem- MIMOS, despite showing a steeper convergence at the start, eventually leads to an inferiorsolution as compared to CPTV approach. These results also reveal that a small number ofstarting points, in general, are sufficient to lead to a good overall solution.

Mixed-integer optimization↗

Procedure for Determining One-Dimensional Flow Distributions in Arbitrarily Connected Passages Without the Influence of Pumping

A calculation procedure is presented which allows the one-dimensional determination of flow distributions in arbitrarily connected (branching) flow passages having multiple inlets and exits. The procedure uses an adaptation of the finite element technique, iteratively coupled with an accurate one-dimensional flow solver. The procedure eliminates the usual restrictions inherent with finite element flow calculations. Unlike existing one-dimensional methods, which require simplifications to the flow equations (uncoupling the momentum and energy equations), to allow for arbitrary branching and multiple inlets and exits, the only limitation of the described methodology is that, at present, it can only accommodate non-rotating configurations (no pumping effects). The calculation procedure is robust, and will always converge for physically possible flow. The procedure is described, and its use is illustrated by an example.

Meitner, Peter L.↗

Phasing of a space based segmented submillimeter wavelength telescope using focal plane measurements

As part of a technology development program for realizing a space based submillimeter telescope, two different approaches to the absolute phasing of a segmented primary mirror using focal plane measurements have been implemented for feasibility. The method of optimization by simulated annealing evaluates the image quality of a point spread function after all the telescope segments have been randomly moved. It accepts each iteration which improves the image quality, as well as a random number of iterations which do not, thus keeping the Strehl in the initialization procedure from falling into local maxima. Methods for determining the annealing schedule, and the step size for random segment movements are presented and discussed. Using phase diversity and a model for the telescope imaging system, a nonlinear least squares algorithm has also been implemented which parameterizes each of the segment actuator movements. Using multiple out of focus images, the segment actuator positions are estimated using an iterative procedure. Nonlinear least squares, although computationally intensive, offers a large savings in the actuator movements over simulated annealing and pairwise phasing methods for large numbers of segments. These algorithms have been integrated into a general simulation program which models the behavior of the telescope under anticipated space conditions.

Levine, B. M.↗

Simulation of shell pellet injection strategies for ITER-scale tokamaks

Dispersive shell pellet (DSP) injection is considered as an alternative to shattered pellet injection as a disruption mitigation system for ITER, and strategies for penetration of a shell pellet into ITER are modeled with the 3D MHD code NIMROD. Because the high plasma temperatures lead to rapid ablation of the shell, delivery of the dispersive payload to the core of ITER will be very challenging. Two strategies to increase payload delivery depth are modeled: first, multiple staggered pellets are simulated in DIII-D, to assess the ability for one DSP to "piggy-back" on another to reach deeper into the core; second, DSP injection after pre-dilution-cooling with deuterium is simulated in ITER, in order to reduce the plasma temperature before shell pellet arrival. The DIII-D simulations show that a second, slower pellet can penetrate much deeper once the release of the first payload strongly cools the mid-radius region. When the pellets are staggered, deeper penetration of the second pellet leads to higher radiation fraction and larger runaway electron loss fraction, consistent with single pellet results. However, simultaneously released pellets at mid-radius that do not trigger a large n=1 mode produce an even higher radiation fraction. The ITER simulations show that an inside-out TQ can be produced with a payload release just inside of the q=2 surface, which is achieved at a speed of 800 m/s after pre-dilution cooling. Although stochastization of the core leads to a complete thermal quench, the edge flux surfaces are surprisingly robust in the ITER simulations, regardless of payload release location. As a result, runaway electron losses would not be expected.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Plasma Wall Interaction with 3-D Plasma Boundaries

The interaction of the edge plasma and the material surfaces is one of the most critical challenges on the path to harness fusion power as new, fundamental energy source. This challenge typically combines the thrust to reach high density, low temperature (detached) plasmas in front of the divertor target plates as well as understanding the plasma material interaction (PMI) in particular in this regime. The combination of both research thrusts represents an extraordinarily challenging subject encompassing spatial scales spanning nanometers to meters in all states of matter and across a broad energy range. Modeling capabilities, which help to interpret data from nowadays experiments and enable extrapolation to future devices are urgently required. This is in particular true for toroidal magnetic confinement devices with three-dimensional (3D) plasma boundaries. Such plasma boundary geometries occur in tokamaks, when small amplitude magnetic perturbations are used to stabilize the unruly edge plasma or in stellarators, that are inherently 3D plasma confinement devices. In this project, the impact of 3D plasma boundaries on the plasma material interaction (PMI) was assessed. This work focused on plasma boundary conditions, in which high-density conditions at the material surfaces yield mitigation of the otherwise immense heat and particle loads that these materials would see. These so-called high recycling and eventually detached plasma regimes are of great interest for future reactor operation. In the project, key features that are unique to 3D boundaries were explored in comparison to canonically assumed axisymmetric plasma edge situations in tokamaks. In particular, the relevance of the 3D boundary situation in the extrapolation to the plasma boundary solution at ITER, the next step fusion energy experiment under construction as a multi-national, world-wide large-science experiment in southern France, has been explored. The EMC3-EIRENE plasma edge fluid and kinetic neutral transport code has been advanced to cope with the challenging and unprecedented conditions in the ITER boundary plasma including 3D fields that are planned to be used to suppress harmful edge instabilities, the so-called edge localized modes. This is a vital integration challenge for ITER and the results from this grant have provide a leading capability for this assessment. It was shown that the detachment process in a 3D edge solution for ITER follows the recycling regimes that are known from axisymmetric solutions, but that multiple plasma exhaust channels connected to the material surfaces are established which feature individual recycling characteristics. Because these channels touch the material surfaces in the divertor in a 3D geometry, the compatibility with the plasma material interaction (PMI), including erosion and impurity generation has been found to be an important part of the integration challenge. To address this, the fully 3D plasma material interaction code ERO2 has been adapted to these ITER specific geometries and a homogeneous mixing model was implemented, that allows to consider the mixing of Be and Was used at ITER in the PMI modeling. This model enhancement has been used to study non-local migration of Be in the JET ITER like wall configuration and it has been shown that with this model such complex migration processes in ITER relevant plasma shapes and with ITER relevant plasma boundary conditions can be addressed. The combined modeling approach using EMC3-EIRENE as a plasma boundary transport code and the ERO2 specialized PMI model will be an asset for the continued preparations of ITER operation as well as for Fusion Pilot Plant efforts that have emerged in the U.S. during the evolution of this grant. The predictive capability of this numerical tool has been validated at the DIII-D US national fusion facility. Here, dedicated plasma edge diagnostics were implemented to measure the impurity household around a 3D edge plasma during ELM suppression by 3D fields. Dedicated experiments with local material probes using these diagnostics and the state-of-the-art suite of boundary measurements at DIII-D have shown that the 3D perturbation of the plasma edge that is excreted by such 3D control fields yield a perturbation of the plasma boundary flux structure and hence also of the resulting PMI. The 3D boundary plasma is composed out of helical magnetic flux channels that intersect the divertor targets at an angle relative to the main guiding field, i.e., the toroidal magnetic field component of the tokamak. A similar effect has been measured as well on limiter surfaces during the startup campaign at the new stellarator experiment Wendelstein 7-X. These experiments ad initial analysis with the ERO plasma material interaction model, suggested that the place of erosion for a given particle from the surface and its re-deposition can be different in such 3D field geometries yielding potentially a significant level of net-erosion. This is not the case for axisymmetric solutions, where it was shown in the past that the eroded particles are effectively re-deposited into gaps produced by erosion at the same position and hence the net-erosion levels are small. For ITER, the quest to suppress the ELMs and at the same time maintain the integrity of the divertor is an issue, which these fundamental findings will help to resolve. The coupling of this work to the extrapolation in the ITER program has been addressed by both the PI and the lead numerical scientist being ITER Science Fellows in the duration of the contract and forward. A second focus in the exploration of 3D boundary effects on tokamaks and stellarators has been set on the measurement of helium exhaust features with such 3D fields. This is important because He represents the ash of the fusion process and needs to be exhausted. It was shown that 3D field application compatible with suppression of ELMs yields an increase of the helium exhaust performance. The ratio of the effective helium confinement time over the energy confinement time was reduced by almost 50% which demonstrated that the impact of helium accumulation in the plasma core with respect to the confinement of energy to sustain the fusion reaction is significantly improved with such 3D control fields. It was shown that this is the case for tokamaks as well as stellarators. At the Large helical Device in Japan, a similar enhancement of the helium exhaust features when small amplitude additional 3D fields were applied was measured. This is an important additional function of 3D field application and its impact on ITER is presently being studied in combination with investigations of helium exhaust in 3D field geometries of stellarator devices.

3D plasma edge transport↗

Understanding and Leveraging the I/O Patterns of Emerging Machine Learning Analytics

The scientific community is currently experiencing unprecedented amounts of data generated by cutting-edge science facilities. Soon facilities will be producing up to 1 PB/s which will force scientist to use more autonomous techniques to learn from the data. The adoption of machine learning methods, like deep learning techniques, in large-scale workflows comes with a shift in the workflow’s computational and I/O patterns. These changes often include iterative processes and model architecture searches, in which datasets are analyzed multiple times in different formats with different model configurations in order to find accurate, reliable and efficient learning models. This shift in behavior brings changes in I/O patterns at the application level as well at the system level. These changes also bring new challenges for the HPC I/O teams, since these patterns contain more complex I/O workloads. In this paper we discuss the I/O patterns experienced by emerging analytical codes that rely on machine learning algorithms and highlight the challenges in designing efficient I/O transfers for such workflows. We comment on how to leverage the data access patterns in order to fetch in a more efficient way the required input data in the format and order given by the needs of the application and how to optimize the data path between collaborative processes. We will motivate our work and show performance gains with a study case of medical applications.

Gainaru, Ana↗

Multi-objective sizing and dispatch for building thermal and battery storage towards economic and environmental synergy

The role of building thermal and battery storage is pivotal in advancing smart cities and achieving sustainability goals through effective energy management. Despite their significance, there are several limitations in the sizing approach and value stream analysis with various objectives for their widespread adoption in buildings. This work proposes a flexible and scalable multi-objective optimization framework for optimal sizing and dispatch of building thermal and battery storage, addressing conflicting objectives simultaneously using mixed-integer linear programming. The weighted-sum method is adapted, combining multiple objectives into a single function. The two-stage procedure iterates over different weights, generating optimal solutions and forming the Pareto front. Case studies are performed to assess the energy, economic, and environmental benefits of building energy storage systems for a large office building in three climate locations. The results demonstrate that the proposed framework efficiently determines optimal sizing and dispatch strategies, addressing the balance between economic viability and emission reduction. The dynamic relationship between time-of-use energy charges and emission factors leads to significantly different strategies based on whether economic or environmental concerns are prioritized. This research enhances our understanding of the benefits of TES and BES systems in buildings, providing valuable guidance to stakeholders.

25 ENERGY STORAGE↗

Synthetic hybrids of six yeast species

Abstract Allopolyploidy generates diversity by increasing the number of copies and sources of chromosomes. Many of the best-known evolutionary radiations, crops, and industrial organisms are ancient or recent allopolyploids. Allopolyploidy promotes differentiation and facilitates adaptation to new environments, but the tools to test its limits are lacking. Here we develop an iterative method of Hybrid Production (iHyPr) to combine the genomes of multiple budding yeast species, generating Saccharomyces allopolyploids of at least six species. When making synthetic hybrids, chromosomal instability and cell size increase dramatically as additional copies of the genome are added. The six-species hybrids initially grow slowly, but they rapidly regain fitness and adapt, even as they retain traits from multiple species. These new synthetic yeast hybrids and the iHyPr method have potential applications for the study of polyploidy, genome stability, chromosome segregation, and bioenergy.

59 BASIC BIOLOGICAL SCIENCES↗