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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 1,387 records · Page 77
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Ground support for Space Shuttle earth observations by the NASA environment remote sensing analysis facility (ERSAF)

The functions and capabilities of the NASA Environment Remote Sensing Analysis Facility (ERSAF) located at the Johnson Space Center are described. ERSAF provides dedicated support to earth-observation activities and Earth-looking payloads conducted aboard the Space Shuttle. This support merges environmental satellite imagery with high-resolution film products and digital imagery acquired aboard the Space Shuttle. ERSAF utilizes several computer systems with specialized software to process and analyze environmental information as well as data acquired from the Space Shuttle. These computer systems and the image analysis capabilities are discussed.

Chambers, M. A.↗
DOE OSTI2021

Machine Learning of Bacterial Transcriptomes Reveals Responses Underlying Differential Antibiotic Susceptibility

In vitro antibiotic susceptibility testing often fails to accurately predict in vivo drug efficacies, in part due to differences in the molecular composition between standardized bacteriologic media and physiological environments within the body. Here, we investigate the interrelationship between antibiotic susceptibility and medium composition in Escherichia coli K-12 MG1655 as contextualized through machine learning of transcriptomics data. Application of independent component analysis, a signal separation algorithm, shows that complex phenotypic changes induced by environmental conditions or antibiotic treatment are directly traced to the action of a few key transcriptional regulators, including RpoS, Fur, and Fnr. Integrating machine learning results with biochemical knowledge of transcription factor activation reveals medium-dependent shifts in respiration and iron availability that drive differential antibiotic susceptibility. By extension, the data generation and data analytics workflow used here can interrogate the regulatory state of a pathogen under any measured condition and can be applied to any strain or organism for which sufficient transcriptomics data are available.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Life Cycle Analysis of Natural Gas Extraction and Power Generation: U.S. 2020 Emissions Profile

This analysis expands upon previous life cycle analyses (LCAs) of natural gas systems performed by the National Energy Technology Laboratory (NETL). It provides a complete inventory of emissions to air and water, water consumption, and land use change. These environmental burdens are detailed for all supply chain steps from natural gas production through natural gas distribution. This package includes the report, the NETL Natural Gas Model, and appendices that include several Excel workbooks and a python script to provide transparent access to the calculations and resulting data. This is revision 1 of the 2024 study (published December 17, 2024 and updated on January 24, 2025) and corrects a modeling error in natural gas composition. See the errata on page 2 for more information.

03 NATURAL GAS↗
NASA NTRS2011

Post-Flight Microbial Analysis of Samples from the International Space Station Water Recovery System and Oxygen Generation System

The Regenerative, Environmental Control and Life Support System (ECLSS) on the International Space Station (ISS) includes the the Water Recovery System (WRS) and the Oxygen Generation System (OGS). The WRS consists of a Urine Processor Assembly (UPA) and Water Processor Assembly (WPA). This report describes microbial characterization of wastewater and surface samples collected from the WRS and OGS subsystems, returned to KSC, JSC, and MSFC on consecutive shuttle flights (STS-129 and STS-130) in 2009-10. STS-129 returned two filters that contained fluid samples from the WPA Waste Tank Orbital Recovery Unit (ORU), one from the waste tank and the other from the ISS humidity condensate. Direct count by microscopic enumeration revealed 8.38 x 104 cells per mL in the humidity condensate sample, but none of those cells were recoverable on solid agar media. In contrast, 3.32 x lOs cells per mL were measured from a surface swab of the WRS waste tank, including viable bacteria and fungi recovered after S12 days of incubation on solid agar media. Based on rDNA sequencing and phenotypic characterization, a fungus recovered from the filter was determined to be Lecythophora mutabilis. The bacterial isolate was identified by rDNA sequence data to be Methylobacterium radiotolerans. Additional UPA subsystem samples were returned on STS-130 for analysis. Both liquid and solid samples were collected from the Russian urine container (EDV), Distillation Assembly (DA) and Recycle Filter Tank Assembly (RFTA) for post-flight analysis. The bacterium Pseudomonas aeruginosa and fungus Chaetomium brasiliense were isolated from the EDV samples. No viable bacteria or fungi were recovered from RFTA brine samples (N= 6), but multiple samples (N = 11) from the DA and RFTA were found to contain fungal and bacterial cells. Many recovered cells have been identified to genus by rDNA sequencing and carbon source utilization profiling (BiOLOG Gen III). The presence of viable bacteria and fungi from WRS and OGS subsystems demonstrates the need for continued monitoring of ECLSS during future ISS operations and investigation of advanced antimicrobial controls.

Birmele, Michele N.↗
DOE OSTI2020

URBANopt: An Open-Source Software Development Kit for Community and Urban District Energy Modeling: Preprint

Urban building modeling tools are developing rapidly; these tools use emerging simulation workflows for specific urban environmental design tasks, such as assessing the impacts of energy efficiency technologies at a district scale. However, with the emergence of new environmental design tasks, addressing all possible use cases and tasks is challenging and cannot be covered by a single tool. Urban-scale analysis at this level of complexity often requires linking multiple emerging tools, rather than using a single tool, to adequately evaluate a variety of possible fields in urban environmental design. To achieve this, flexible platforms are needed to support multiple input formats (e.g., geometric and non-geometric building properties), enabling the mapping of such inputs to underlying simulation engines. This paper provides an overview of the open-source URBANopt Software Development Kit (SDK) for modeling high-performance buildings and energy systems at a district scale. URBANopt's flexible SDK is composed of several modules that can be customized to integrate with other tools and generate new workflows to perform urban environmental design tasks, such as capturing interactions between individual buildings, district energy systems, distributed energy resources, and the electric distribution grid. We describe the functionality of the core SDK modules in URBANopt (called Core Gem, GeoJSON Gem, and Scenario Gem) and discuss the flexibility of these modules as a means of integration with a variety of tools. We also document and demonstrate technical details of writing and combining new modules to create customized workflows. Finally, we present a case study that uses the URBANopt SDK to model a hypothetical mixed-use urban project and simulate various scenarios to meet district energy performance goals.

buildings↗
DOE OSTI2020

Genomics of sorghum local adaptation to a parasitic plant

Host–parasite coevolution can maintain high levels of genetic diversity in traits involved in species interactions. In many systems, host traits exploited by parasites are constrained by use in other functions, leading to complex selective pressures across space and time. Here, we study genome-wide variation in the staple crop Sorghum bicolor (L.) Moench and its association with the parasitic weed Striga hermonthica (Delile) Benth., a major constraint to food security in Africa. We hypothesize that geographic selection mosaics across gradients of parasite occurrence maintain genetic diversity in sorghum landrace resistance. Suggesting a role in local adaptation to parasite pressure, multiple independent loss-of-function alleles at sorghum LOW GERMINATION STIMULANT 1 (LGS1) are broadly distributed among African landraces and geographically associated with S. hermonthica occurrence. However, low frequency of these alleles within S. hermonthica-prone regions and their absence elsewhere implicate potential trade-offs restricting their fixation. LGS1 is thought to cause resistance by changing stereochemistry of strigolactones, hormones that control plant architecture and below-ground signaling to mycorrhizae and are required to stimulate parasite germination. Consistent with trade-offs, we find signatures of balancing selection surrounding LGS1 and other candidates from analysis of genome-wide associations with parasite distribution. Experiments with CRISPR–Cas9-edited sorghum further indicate that the benefit of LGS1-mediated resistance strongly depends on parasite genotype and abiotic environment and comes at the cost of reduced photosystem gene expression. Our study demonstrates long-term maintenance of diversity in host resistance genes across smallholder agroecosystems, providing a valuable comparison to both industrial farming systems and natural communities.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2004

Analysis of Asian Outflow over the Western Pacific using Observations from Trace-P

Our analysis of the TRACE-P data focused on answering the following questions: 1) How do anthropogenic sources in Asia contribute to chemical outflow over the western Pacific in spring? 2) How does biomass burning in southeast Asia contribute to this outflow? 3) How can the TRACE-P observations be used to better quantify the sources of environmentally important gases in eastern Asia? Our strategy drew on a combination of data analysis and global 3-D modeling, as described below. We also contributed to the planning and execution of TRACE-P through service as mission scientist and by providing chemical model forecasts in the field.

Jacob, Daniel J.↗
DOE OSTI2023

Coal-based Bricks & Blocks (CBBs): Process Development to Prototype Fabrication Coupled with Techno-Economic Analysis and Market Survey

The decline of coal use for energy production provides an abundance of local feedstock for new innovative uses and value-added products. Expanding the U.S. coal-value chain to manufacture high-value carbon products can strengthen the nation’s energy and mineral security, enhance the U.S. national defense security, increase the United States’ economic prosperity, while achieving U.S. environmental objectives. The primary project goal is a relatively light-weight composite product with superior (or comparable) compressive strength. Both virgin and, where available, post-consumer recycled thermoplastic versions are tested for each thermoplastic species. A useful attribute of thermoplastics as binders is that they can be heated to their melting point, cooled, and reheated again without significant degradation. A key advantage of thermoset CBBs is that they require only mixing and molding. CBB advantages include low cost, availability, binding ability and processability. Coal-based bricks and blocks (CBBs) weigh about 50% less than clay bricks and can be manufactured with an interlocking design to promote ease of use for the novice builder. CBB formulation is evaluated according to a design-of-experiments (DoE) approach. DoE variables are a) relative weight fractions of binder, b) relative proportions of large versus small (milled) anthracite size fractions, and c) additive percentage. Fabrication methods include hot-press molding and extrusion, the later being the most commercially viable. CBBs are tested for compressive strength, modulus of rupture (by flexure test) and water absorption per ASTM C67, with density determined by the Archimedes drainage method. Fractured interfaces are examined by SEM (Scanning Electron Microscopy) to resolve fracture dynamics and interior microstructure uniformity. Differential scanning calorimetry (DSC) is used to compare plastic transition temperatures i.e., glass and melting temperatures to contrast virgin with post-consumer recycled thermoplastics and optimize their usage. These results are used in the DoE analysis to identify the binder and relative weight percentages for optimum strength, density, and porosity. Overall, CBBs possess strength comparable to clay-based bricks but are non-permeable and hydrophobic, and hence resistant to degradation by freeze-fracturing, corrosion, and efflorescence. The strongest composites have been made with the following thermoplastic binders (in order of strength): thermoset, high-density polyethylene crosslink resin, high-density polyethylene, nylon 6/6, and polypropylene. Results from a techno-economic analysis TEA show economy of scale for CBBs by modularization and reveal the binder as the cost driver for material costs. Ideally, the incorporation of post-consumer recycled thermoplastic will decrease material acquisition costs and increase product sustainability. Notably, CBBs do not require the high temperature calcination needed to produce cement, nor do they require firing in the 1600-2400 °F range for three days using natural gas, as do clay brick equivalents. Instead, CBBs are heated to a modest <600 °F according to the melt flow index of the thermoplastic binder. Existing anthracite mines can be expanded to produce CBBs to reduce aggregate transportation costs and emissions that exist for clay bricks. TEA reflects this reduced energy cost while a comparative CO2 emission analysis quantifies the reduced environmental footprint. The market survey identifies several commercialization opportunities, dependent upon the brick classification.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

Technical and Economic Assessment and Gap Analysis of Advanced Nuclear Reactor Integration with a Reference Oil Refinery

Efforts to identify the most-economic methods to decarbonize several sectors of the U.S. economy are underway. Industrial processes such as crude-oil refining rely heavily on energy-dense and easily stored and transported fossil fuels for powering their operations. Refineries use large amounts of energy, primarily derived from fossil sources to separate crude-oil components, break down heavier hydrocarbons into lighter compounds, remove impurities, reform hydrocarbon molecules, and generate steam and electricity for pumps and compressors and other various auxiliary systems. Crude-oil refining operations such as distillation, cracking, desulfurization, reforming, utilities systems and some offsite facilities collectively account for most of the energy consumption. Other operations such as hydrocracking or hydrotreating also require hydrogen for developing hydrogenation reactions which involve substantial heating to keep the reactors at high-temperature and pressure levels. All heat and energy demands are typically provided by natural gas (NG), oil, or other fuels, which makes refinery industry one of the most-difficult sectors to decarbonize. Nuclear power is a viable and energy-dense source of clean electricity, heat, and hydrogen to provide the large, sustainable energy supply that the refining industry demands. The U.S. Department of Energy’s (DOE’s) Integrated Energy Systems (IES) program is working to perform research and development, design, economic siting, and risk analysis. This state-of-the-art work will enable the first on-site demonstrations and commercial deployments of advanced small modular nuclear reactors (SMNRs) integrated with industries such as chemical production, refining, iron and steel making, and more. IES seeks to demonstrate the ability of advanced nuclear reactors to meet the heat and power demands of these industries while reducing carbon emissions in a sustainable and cost-competitive way. The primary objective of this research effort is to analyze industrial-scale SMNR integration intended to decarbonize refining facilities. The foreseen outcome is the provision of reliable, cost-competitive, and sustainable clean energy, alongside a reduction of carbon emissions. Specifically, the focus of this work lies on meeting the reference facilities’ heat and electricity demands with nuclear power while also supplying clean hydrogen via integrated high-temperature steam electrolysis (HTSE). This report presents a comprehensive technical and economic assessment of the integration of advanced nuclear reactors into a reference refinery, leveraging financial incentives from the Inflation Reduction Act (IRA). The evaluation aims to explore the potential economic benefits and challenges associated with incorporating advanced nuclear reactors into refinery operations, particularly in terms of energy efficiency, economic implications and environmental impact. By examining both the technical feasibility and economic viability, this analysis seeks to identify existing gaps and propose solutions for successful nuclear integration implementation. The findings are intended to provide valuable insights for stakeholders considering the adoption of advanced nuclear reactors in the refining sector. A refinery reference-plant was developed, using an open-source refinery model, Petroleum Refinery Lifecycle Inventory Model (PRELIM) and expert assessment, as a base case for comparison with various nuclear integration options. The capacity of 100 kbd/day (KBD) of heavy crude-oil feed was selected to represent a general coking-type refinery with deep conversion capabilities (incorporating heavy-oil upgrading with FCC, coking, and associated hydrotreating process units), using a heavy crude-oil feed, which represents about 70% of U.S. refineries configurations. A summary of all cases considered in this study is shown in Table 1.

13 HYDRO ENERGY↗
DOE OSTI2025

Whole Algae Hydrothermal Liquefaction and Upgrading: A review of progress and challenges and insight into the future

This report summarizes the research at Pacific Northwest National Laboratory (PNNL) to evaluate the economic viability and environmental impact of using microalgae to produce fuels and other products via hydrothermal liquefaction (HTL). Over the past several years, PNNL has examined key aspects of feedstock cost and availability, formatting and conversion techniques, and the utilization of all HTL products. Investigations of feedstock cost led to opportunities to work with cost-advantaged algal feedstocks that can be provided at minimal cost for HTL processing. Cost-advantaged algae include wastewater-grown algae and harvested algal blooms. Although farm-cultivated algae offer the best possible biomass composition and scalability for HTL processing, the cost of the feedstock is too high to yield an economically competitive biofuel. Processing cost-advantaged feedstocks creates other unique challenges in adapting HTL to upgrade biomass with higher than typical ash content and less preferred composition (low lipid). Despite the challenges, HTL of cost-advantaged algae results in economically competitive pricing scenarios and significant advantages in reducing net emissions below 70% of the petroleum baseline. The utilization of a variety of potential non-fuel products from algal HTL, such as the use of HTL solids as a cement additive, provides a significant reduction in net emissions by offsetting emissions from other carbon-intense products. This report presents an analysis of the research conducted at PNNL to develop an economically and environmentally beneficial process for algae HTL.

09 BIOMASS FUELS↗
NASA NTRS1988

The N2-P3 complex of the evoked potential and human performance

The N2-P3 complex and other endogenous components of human evoked potential provide a set of tools for the investigation of human perceptual and cognitive processes. These multidimensional measures of central nervous system bioelectrical activity respond to a variety of environmental and internal factors which have been experimentally characterized. Their application to the analysis of human performance in naturalistic task environments is just beginning. Converging evidence suggests that the N2-P3 complex reflects processes of stimulus evaluation, perceptual resource allocation, and decision making that proceed in parallel, rather than in series, with response generation. Utilization of these EP components may provide insights into the central nervous system mechanisms modulating task performance unavailable from behavioral measures alone. The sensitivity of the N2-P3 complex to neuropathology, psychopathology, and pharmacological manipulation suggests that these components might provide sensitive markers for the effects of environmental stressors on the human central nervous system.

Odonnell, Brian F.↗
DOE OSTI2019

Intracellular Dynamics of Superparamagnetic Iron Oxide Nanoparticles for Magnetic Partical Imaging

Superparamagnetic iron oxide nanoparticles (SPIONs) are a foundational platform for a variety of biomedical applications. Of particular interest is Magnetic Particle Imaging (MPI), which is a growing area of research and development due to its advantages including high resolution and sensitivity with positive contrast. There has been signicant work in the area of in vivo optimization of SPIONs for MPI as well as their biodistribution in and clearance from the body. However, little is known about the dynamics of SPIONs following cellular internalization which may limit their usefulness in a variety of potential imaging and treatment applications. This work shows a clear 20% decrease in magnetic performance of SPIONs, as observed by Magnetic Particle Spectroscopy (MPS), after internalization and systematic consideration of applicable factors that aect SPION signal generation, including microstructure, environment, and interparticle interactions. There is no observed change to SPION microstructure after internalization, and the surrounding environment plays little to no role in magnetic response for the SPIONs studied here. Interparticle interactions described by dipole-dipole coupling of SPIONs held close to one another after internalization are shown to be the dominant cause of decreased magnetic performance in cells. These conclusions were drawn from transmission electron microscopy (TEM) image analysis at relevant length scales, experimentally prepared and characterized SPIONs in varied environmental conditions, and theoretical modeling with Monte Carlo simulations.

Teeman, Eric M.↗
DOE OSTI2019

Influences of nitrogen fertilization and climate regime on the above-ground biomass yields of miscanthus and switchgrass: A meta-analysis

Perennial grasses are touted as sustainable feedstocks for energy production. Such benefits, however, may be offset if excessive nitrogen (N) fertilization leads to economic and environmental issues. Moreover, as yields respond to changes in climate, nutrient requirements will change, and thus guidance on minimal N inputs is necessary to ensure sustainable bioenergy production. Here, a pairwise meta-analysis was conducted to investigate the effects of N fertilization (amount and duration) and climate on the above-ground biomass yields of miscanthus ( Miscanthus x giganteus ) and switchgrass ( Panicum virgatum L. ). Both regression models and meta-analyses showed that switchgrass was more responsive to N than miscanthus, although both showed significant and positive N effects. Meta-analysis further showed that the positive growth response of miscanthus to N application increased with N addition rates of 60–300 kg N ha -1 year -1 , but the magnitude of the response decreased with the number of years of fertilization (duration). N effects on switchgrass biomass increased and peaked at rates of 120–160 kg N ha -1 year -1 and 5–6 years of N inputs, but diminished for rates >300 kg N ha -1 year -1 and >7 years. Meta-analysis further revealed that the influences of N on switchgrass increased with both mean annual temperature and precipitation. Miscanthus yields were less responsive to climate than switchgrass yields. This meta-analysis helps fill a gap in estimation of biofeedstock yields based on N fertilization and could help better estimate minimum N requirements and soil management strategies for miscanthus and switchgrass cultivation across climatic conditions, thereby improving the efficiency and sustainability of bioenergy cropping systems.

09 BIOMASS FUELS↗
NASA NTRS1992

Prediction of space sickness in astronauts from preflight fluid, electrolyte, and cardiovascular variables and Weightless Environmental Training Facility (WETF) training

Nine preflight variables related to fluid, electrolyte, and cardiovascular status from 64 first-time Shuttle crewmembers were differentially weighted by discrimination analysis to predict the incidence and severity of each crewmember's space sickness as rated by NASA flight surgeons. The nine variables are serum uric acid, red cell count, environmental temperature at the launch site, serum phosphate, urine osmolality, serum thyroxine, sitting systolic blood pressure, calculated blood volume, and serum chloride. Using two methods of cross-validation on the original samples (jackknife and a stratefied random subsample), these variables enable the prediction of space sickness incidence (NONE or SICK) with 80 percent sickness and space severity (NONE, MILD, MODERATE, of SEVERE) with 59 percent success by one method of cross-validation and 67 percent by another method. Addition of a tenth variable, hours spent in the Weightlessness Environment Training Facility (WETF) did not improve the prediction of space sickness incidences but did improve the prediction of space sickness severity to 66 percent success by the first method of cross-validation of original samples and to 71 percent by the second method. Results to date suggest the presence of predisposing physiologic factors to space sickness that implicate fluid shift etiology. The data also suggest that prior exposure to fluid shift during WETF training may produce some circulatory pre-adaption to fluid shifts in weightlessness that results in a reduction of space sickness severity.

Simanonok, K.↗
DOE OSTI2019

The Shifting Role of mRUE for Regulating Ecosystem Production

To design a comprehensive view of ecosystem resource use, in this work we integrated parallel resource use efficiency observations into a multiple-resource use efficiency (mRUE) framework using a dynamic factor analysis model. Results from 56 site-years of eddy covariance data and mRUE factors for a site in the US Midwest show temporal dynamics and coherence (using Pearson’s R) among resources are associated with interannual variation in precipitation. Loading factors are derived from mRUE observations and quantify how strongly data are connected to the underlying ecosystem state. Water and light resource use loading factors are coherent at annual timescales (Pearson’s R of 0.86), whereas declining patterns of carbon use efficiency loading factors highlight the ecosystem’s trade-off between carbon uptake and respiration during the growing season. At annual and monthly timescales, influence decreases from ~85 to ~65% for loading factors for carbon use, while influence of light use loading factors peaks to ~60% at growing season timescales. Quantifying variation in ecosystem function provides novel insights into the temporal dynamics of changing significance of multiple resources to ecosystem function.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Public electric vehicle charging station utilization in the United States

The utilization of electric vehicle (EV) charging equipment is a key driver of charging station economics, but current trends and factors related to the utilization of public charging infrastructure in the United States are not well understood. This study analyzes EV charging data from 3,705 nationwide public Level 2 (L2) and direct current fast charging (DCFC) stations over 2.5 years (2019-2022), observing utilization patterns over time. Regression analysis is used to assess the relationships between station utilization and several contextual and environmental factors. We conclude that local EV adoption is a strong indicator of utilization; L2 station utilization decreases with the size of the local charging network, while DCFC stations are less affected; and increased charging power has a greater effect on utilization for DCFC stations than L2. This study fills a critical research gap by reporting updated public charging station utilization statistics and analysis for the U.S. market.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1988

Commercial objectives, technology transfer, and systems analysis for fusion power development

Fusion is an inexhaustible source of energy that has the potential for economic commercial applications with excellent safety and environmental characteristics. The primary focus for the fusion energy development program is the generation of central station electricity. Fusion has the potential, however, for many other applications. The fact that a large fraction of the energy released in a DT fusion reaction is carried by high energy neutrons suggests potentially unique applications. In addition, fusion R and D will lead to new products and new markets. Each fusion application must meet certain standards of economic and safety and environmental attractiveness. For this reason, economics on the one hand, and safety and environment and licensing on the other, are the two primary criteria for setting long range commercial fusion objectives. A major function of systems analysis is to evaluate the potential of fusion against these objectives and to help guide the fusion R and D program toward practical applications. The transfer of fusion technology and skills from the national labs and universities to industry is the key to achieving the long range objective of commercial fusion applications.

Dean, Stephen O.↗
DOE OSTI2021

An evolutionary algorithm for designing microbial communities via environmental modification

Despite a growing understanding of how environmental composition affects microbial communities, it remains difficult to apply this knowledge to the rational design of synthetic multispecies consortia. This is because natural microbial communities can harbour thousands of different organisms and environmental substrates, making up a vast combinatorial space that precludes exhaustive experimental testing and computational prediction. Here, we present a method based on the combination of machine learning and metabolic modelling that selects optimal environmental compositions to produce target community phenotypes. In this framework, dynamic flux balance analysis is used to model the growth of a community in candidate environments. A genetic algorithm is then used to evaluate the behaviour of the community relative to a target phenotype, and subsequently adjust the environment to allow the organisms to approach this target. We apply this iterative process to thousands of in silico communities of varying sizes, showing how it can rapidly identify environments that yield desired taxonomic compositions and patterns of metabolic exchange. Moreover, this combination of approaches produces testable predictions for the assembly of experimental microbial communities with specific properties and can facilitate rational environmental design processes for complex microbiomes.

59 BASIC BIOLOGICAL SCIENCES↗