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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Unraveling the pathway towards superionic transport in polymer electrolytes

Ionic transport in polymers is critical for Li-ion batteries, fuel cells, flow batteries and many other energy storage and conversion technologies. A significant enhancement of ion conductivity in polymers may be achieved through an increase in the polarity of side chains and their self-organization into specific morphologies, which can potentially act as percolated ionic structures. However, higher polarity increases attractive interactions within a polymer matrix and slows down its segmental dynamics, which conversely hinders ionic transport. To overcome this tradeoff, we designed the functionalization of a Li salt-doped polymer matrix by tailored amounts of zwitterionic (ZI) groups. Our results suggest the emergence of a self-assembled percolation conductivity regime above a specific ZI concentration, in which ion hopping decouples from segmental dynamics by up to ten orders of magnitude. Consequently, in the highly concentrated ZI regime, our polymeric materials exhibit in their glassy state energy barriers for ion hopping similar to, or even smaller than, those reported for superionic ceramics. Our study also reveals that ion dynamics in the poly(zwitterion) with all monomers carrying ZI groups is significantly faster than that of a monomeric ZI compound, although the latter has much faster structural relaxation. Furthermore, this result highlights the crucial role played by the local morphology on the ion transport of polymer electrolytes and opens a new pathway for the design of superionic polymers, significantly expanding the current limited portfolio of solid-state electrolytes for energy applications.

Ion conductivity↗
DOE OSTI2022

Oxidative coupling of methane (OCM) conversion into C 2 products through a CO 2 /O 2 co-transport membrane reactor

Oxidative coupling of methane (OCM), which transforms CH 4 into C 2 products (C 2 H 6 and C 2 H 4 ) with molecular O 2 as the oxidant, is one of the most studied direct methane conversions (DMCs). However, a major technical hurdle to the OCM process is to achieve high CH 4 conversion at high C 2 (C 2 H 6 and C 2 H 4 ) selectivity. One rudimentary cause for this “tradeoff” behavior is the high chemical reactivity of the products (C 2 H 6 or C 2 H 4 ), which can be re-oxidized by O 2 . To overcome this thermodynamic challenge, minimizing the oxidizing power of the oxidant and lowering the local oxygen partial pressure are keys. Here, In this work, we demonstrate a new membrane reactor that capture CO 2 /O 2 from a flue gas and uses it for OCM conversion. The results show that the co-captured CO 2 /O 2 mixture converts CH 4 into C 2 H 6 in the presence of a 2%Mn–5%Na 2 WO 4 /SiO 2 catalyst, followed by thermal cracking of C 2 H 6 into C 2 H 4 and H 2 . The presence of CO 2 decreases the local partial pressure of O 2 , thus reducing the propensity of C 2 -products re-oxidation and leading to a higher C 2 selectivity. We show that a small button-type membrane reactor can achieve 12% C 2 yield with ~57% C 2 -selectivity using a diluted CH 4 -Ar mixture as the feedstock. We expect higher C 2 yield with tubular plug-flow membrane reactors in the future. We also highlight the unique advantage of the membrane reactor in intensifying CO 2 capture from both flue gas and OCM purification process into one single step.

42 ENGINEERING↗
DOE OSTI2025

Ultra-selective CANAL Polymers for Hydrogen-based Membrane Separations after Long-Term Aging

Hydrogen is a critically important molecule in the chemicals and energy industries, driving the need for efficient purification technologies such as membrane-based separations. However, polymer membranes often suffer from physical aging, leading to decreased gas permeability over time. This study leverages the unique aging behavior of contorted microporous polymers, synthesized via catalytic arene-norbornene annulation (CANAL) polymerization, to enhance molecular sieving for H 2 separations. While prior studies demonstrated a 1000% increase in H 2 /CH 4 selectivity with minimal permeability loss over 150 days, we extend this investigation to hyperaged (∼1 year) CANAL polymers and evaluate their performance under various conditions of industrial relevance. We report a remarkable 6100% increase in H 2 /CH 4 selectivity and a 2400% improvement in H 2 /N 2 selectivity, with only a 55% decline in H 2 permeability. These membranes exhibit excellent long-term stability in binary and ternary gas mixtures and at elevated temperatures. Additionally, extended aging enhances H 2 /CO 2 selectivity beyond the 2008 upper bound due to improved size-sieving. High-temperature permeation experiments and grand canonical Monte Carlo simulations reveal that H 2 permeability increases from 570 to 3500 barrer as the temperature rises from 35 °C to 190 °C, while H 2 /CO 2 selectivity declines from 14 to 3 due to the higher diffusion activation energy of CO 2 . Despite this tradeoff, hyperaged CANAL membranes maintain performance beyond the 200 °C upper bound, having selectivity–permeability performance comparable to many state-of-the-art membranes for H 2 /CO 2 separations. As a result, this study highlights the robustness and industrial viability of ultra-selective CANAL polymers for hydrogen purification, contributing to advancements in clean energy and sustainable separation technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Property enhancement of CoCrNi medium-entropy alloy by introducing nano-scale features

CoCrNi -medium-entropy alloy (MEA) has been widely investigated due to its superior mechanical properties that overcome strength-ductility tradeoff. Here we show further property enhancement of CoCrNi MEA by introducing nano-scale features. Both CoCrNi and oxide dispersion strengthened (ODS) CoCrNi are fabricated by mechanical alloying and spark plasma sintering. Microstructural characterization and mechanical testing of these nanostructured MEAs revealed that the nano-scale features significantly improves the strength of the alloys. In ODS-CoCrNi MEA, Y 2 Ti 2 O 7 oxides with an average diameter of 7.3 ± 3.2 nm are incoherent with the matrix, and a specific orientation relationship exists between Y 2 Ti 2 O 7 and the matrix, which is [011] Y 2 Ti 2 O 7 //[011]Matrix, (400) Y 2 Ti 2 O 7 //(200)Matrix and ($22\bar2$) Y 2 Ti 2 O 7 //($11\bar1$)Matrix. The recrystallization and grain growth processes are effectively suppressed by the introduction of Y 2 Ti 2 O 7 nanoparticles. Strengthening mechanism analyses indicate that the strength improvement of ODS-CoCrNi is mainly ascribed to the precipitation strengthening of Y 2 Ti 2 O 7 .

36 MATERIALS SCIENCE↗
DOE OSTI2025

New class of tritium breeders for fusion applications: Metal-reinforced composite breeders

Commercial fusion reactors operating on a D-T fuel cycle will require a steady supply of tritium to maintain the burning plasma required for continuous power generation. Since tritium has a short half-life, there is negligible natural abundance which necessitates fusion reactors to produce their own source of tritium. Tritium is most easily produced by surrounding a fusion reactor core with lithium (Li), which reacts under the intense neutron flux leaving the reactor core to form tritium and helium. Due to the hazards and technical challenges associated with surrounding a fusion reactor core with many tons of molten Li, other Li-bearing tritium breeder materials have been pursued. Unfortunately, most of the liquid breeders historically examined are exceedingly corrosive to reactor structural materials while many solid breeders in the form of ceramics are forced to make tradeoffs between Li content and mechanical integrity. In this work, to break the historic limit between Li-density and mechanical integrity of traditional solid breeders, a new class of solid tritium breeders is developed: metal-reinforced composite (MERC) breeders. Specifically, the high Li-density of lithium oxide (Li 2 O) is exploited through the addition of a metal reinforcing phase, producing a composite breeder material exhibiting high splitting tensile strength and quasi-ductility with a Li-density greater than other leading solid breeder candidates, including lithium orthosilicate (Li 4 SiO 4 ) and lithium metatitanate (Li 2 TiO 3 ). Mechanical testing, microstructural characterization, and neutronic simulation results are presented and discussed in light of fusion reactor design considerations.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Electrical injection and transport in Teflon-diluted hole transport materials

Diluting small molecule organic semiconductor hole transport materials with Teflon AF (TAF) dramatically increases their thermal/morphological stability while counterintuitively also increasing the current density in hole-only diodes. Here, we explore the origin of this current enhancement in co-evaporated blends of TAF and N,N'-Di(1-naphthyl)-N,N'-diphenyl-(1,1'-biphenyl)-4,4'-diamine (NPD) and find that it results from improved hole injection and not from a mobility enhancement due to semiconductor dilution effects. Whereas electroabsorption measurements indicate that an interface dipole shift of up to 0.5 eV (depending on TAF concentration) aides hole injection at the indium-tin-oxide anode, time-of-flight and temperature-dependent current-voltage measurements show that the mobility of 25 vol% TAF:NPD blends decreases by roughly an order of magnitude relative to neat NPD despite having slightly lower energetic disorder. For comparison, diluting with 25 vol% high density polyethylene achieves a similar reduction in energetic disorder but only decreases the mobility by a factor of two. Furthermore, these results highlight the tradeoff between reducing energetic disorder and frustrating percolation in diluted organic semiconductors, and represent a step toward thermally-evaporated polymer-small molecule composites that maintain high mobility while offering improved morphological stability and lower refractive index for organic light emitting diodes.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Immortal rays: Rethinking random ray neutron transport on GPU architectures

The Random Ray Method (TRRM) is a recently developed adaptation of the Method of Characteristics for neutral particle transport simulations. TRRM has demonstrated excellent performance on 3D nuclear reactor benchmark problems using CPU-based compute systems. When porting to GPU-based systems, however, new performance challenges arise that are unique to processors targeting massive fine-grained parallelism. For smaller problems, or for large problems that are domain decomposed across many computational nodes, the problem size per node has insufficient parallelism to saturate GPU node resources, thus greatly limiting speedup. In this study, we report on a newly developed “immortal ray” variant of TRRM. Here, the immortal ray technique exposes significantly more fine-grained parallelism by fundamentally reformulating the numerical details of ray discretization, resulting in performance tradeoffs with significant overall benefit on GPUs. For very small 2D simulation problems we found the new immortal ray variant allowed for up to a 4.4x speedup when run on a single GPU. For larger 3D simulation problems we found the new variant improved strong scaling by 3x when run on the Summit supercomputer.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Genome-scale modelling of the primary-specialized metabolism interface

Environmental challenges and development require plants to reallocate resources between primary and specialized metabolites to survive. Genome-scale metabolic models, which map carbon flux through metabolic pathways, are a valuable tool in the study of tradeoffs that arise at this interface. Due to annotation gaps, models that characterize all the enzymatic steps in individual specialized pathways and their linkages to each other and to central carbon metabolism are difficult to construct. Recent studies have successfully curated subsystems of specialized metabolism and characterized the interfaces where flux is diverted to the precursors of glucosinolates, terpenes, and anthocyanins. Although advances in metabolite profiling can help to constrain models at this interface, quantitative analysis remains challenging because of the different timescales on which specialized metabolites from constitutive and reactive pathways accumulate.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

MOOGLE: A Multi-Objective Optimization tool for three-dimensional nuclear fuel assembly design

MOOGLE is a new genetic algorithm methodology for the three-dimensional design of nuclear fuel assemblies. MOOGLE uses common fuel rod types as the decision variable to develop a suite of three-dimensional fuel assemblies to provide optimized solutions to the design problem. Pressurized Water Reactor (PWR) fuel assemblies were optimized using IFBA and gadolinium (Gd 2 O 3 ) as burnable poisons in order to compare how burnable poison choice affects optimization results. Boiling Water Reactor (BWR) fuel bundles were also optimized using three unique fuel rod palettes to study how the size of the design space affects optimization results. Burnable poison analysis showed that utilizing IFBA and Gd 2 O 3 as burnable poisons produced the best and widest range of optimized solutions. Further, BWR fuel bundle optimization results indicate that the inclusion of additional fuel rod types produced a wider solution space but did not improve optimization results for regions explored using fewer unique fuel rods. These tests demonstrate MOOGLE's ability to analyze the tradeoffs between the inclusion of different fuel elements and their effects on assembly performance.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Decoupling of greenness and gross primary productivity as aridity decreases

Ecosystem primary productivity is a key ecological process influencing many ecosystem services, including carbon storage. Thus, clarifying how primary productivity in terrestrial ecosystems responds to climatic variability can reveal key mechanisms that will drive future changes in the global carbon budget. Satellite products of canopy greenness are widely used as proxies for vegetation productivity to evaluate how ecosystems respond to climate variability. However, to what degree inter-annual variations in productivity are consistent with greenness and how this relationship varies spatially remains unclear. Here we investigated the strength of the coupling between inter-annual variations in leaf area index (LAI, a measure of greenness) and ecosystem gross primary productivity (GPP) derived from eddy covariance towers, i.e., the r2 of the LAI-GPP relationship. Overall, inter-annual GPP and LAI were highly coupled (i.e., high r2) in arid grasslands, but were fully decoupled in mesic evergreen broadleaf forests, indicating that this relationship varies strongly along aridity gradients. A possible mechanism of the spatial variation in the LAI-GPP relationship is that the tradeoff between ecosystem structure (LAI) and physiology (photosynthesis per unit leaf area) becomes stronger in more humid climates. Land models overestimated the r2 of LAI-GPP correlation for most ecosystem types and failed to capture the spatial pattern along aridity gradients. We conclude that relying on greenness products for evaluating inter-annual changes in vegetation productivity may bias assessments, especially in tropical rainforest ecosystems. Our findings may also reconcile observed disparities between responses in greenness and GPP during drought in Amazon forests.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

How structural differences influence cross-model consistency: An electric sector case study

Multiple models are often employed to describe a range of possible outcomes for one or more scenarios, yielding insights into causal relationships and their uncertainties. Electric sector capacity expansion scenarios are a common topic of such efforts due to the economic influence of the electric sector, but model results typically span a broad solution space despite efforts to harmonize input assumptions, making decision implications difficult to discern. This study investigates the relationship between input harmonization and cross-model scenario consistency under disparate electric sector scenarios. We compare cross-model consistency between two state-of-the-art electric sector capacity expansion models (GCAM-USA and ReEDS) for six electric sector scenarios comprising alternate assumptions about fossil fuel resource availability, technology innovation, and long-term economy-wide transitions under four harmonization configurations varying model representations of electricity demand, fuel prices, renewable resources, and capacity retirements. These comparisons reveal that cross-model consistency can vary across scenarios under a given harmonization configuration, suggesting that harmonization efforts must often be scenario-specific if comparable cross-model consistency is desired. Model structural differences can hinder consistency, and the impact of these differences can depend on the scenario. Ultimately, thorough harmonization can reveal insights into cross-model consistency, which can be used to tighten uncertainty bounds and improve the decision-making implications of multi-model activities.

Cohen, Stuart↗
DOE OSTI2022

Multifunctional landscapes for dedicated bioenergy crops lead to low-carbon market-competitive biofuels

Switchgrass is a promising feedstock for cellulosic biorefineries, due to its ability to maintain comparatively high biomass yields across a wide range of soil and climatic conditions. However, there is an incomplete understanding of the economic and environmental tradeoffs associated with cultivating switchgrass on low-productivity land for conversion to biofuels. This study surveys prior literature and demonstrates a new integrated assessment framework, including agroecosystem, ecosystem services valuation, technoeconomic, and life-cycle assessment models, to quantify and contextualize the economic and environmental impacts of switchgrass cultivation on marginal land with downstream conversion to biofuels. Monetizing and incorporating the value of ecosystem services, such as improved water quality benefits from nitrate and sediment reductions, climate change mitigation benefits from CO 2 emission reduction, and recreational and pollination benefits from increased biodiversity, the modeled multifunctional landscape reduces the ethanol production cost by 33.3–58.9 cents/$\scriptsize{L}$-gasoline-equivalent ($\$$1.3–2.2/gge). Planting switchgrass in low productivity land improves soil health, resulting in the carbon footprint reduction credit of 12.8–20.2 gCO 2e /MJ. For an improved switchgrass-to-ethanol conversion pathway with the maximum benefits from ecosystem services, the minimum ethanol selling price and carbon footprint of ethanol, respectively, could reach to 31 cents/$\scriptsize{L}$-gasoline-equivalent (47% reduction relative to average gasoline price) and 3 gCO 2e /MJ (97% reduction relative to gasoline). In conclusion, this low carbon renewable ethanol leads to substantial State and/or Federal policy incentives (~$\$$1/$\scriptsize{L}$-gasoline-equivalent) providing a large benefit to biorefinery operators, farmers, and the public as a whole.

09 BIOMASS FUELS↗
DOE OSTI2026

A comparative study of multimodal data fusion strategies for planetary spectroscopy

Integrating heterogeneous data sources can improve scientific inference when different modalities capture complementary information, but doing so is challenging in high-dimensional, small-sample settings. In spectroscopy for planetary exploration, Laser-Induced Breakdown Spectroscopy (LIBS), Raman Spectroscopy (Raman), Visible Infrared Spectroscopy (VISIR), and Mid-Infrared Spectroscopy (MIR) each examine different aspects of composition and mineralogy, raising fundamental questions about when and how data fusion improves predictive performance. Using a Mars-relevant set of geologic standards with measurements from all four modalities, we present a rigorous systematic evaluation of four data fusion strategies: low-level (data) fusion, mid-level (feature) fusion, high-level (decision) fusion, and residual-boosting (sequential) fusion. We assess performance in predicting oxide composition via nested cross-validation and corrected significance testing to evaluate whether data fusion improves upon single-modality baselines. We show that data fusion does not uniformly improve accuracy, and that observed gains are modest, oxide-dependent, and sensitive to modality and model structure. To move beyond aggregate accuracy metrics, we use model coefficients, permutation importance, and residual gain analysis to examine how the fusion models weight individual modalities and to identify patterns of apparent complementarity or redundancy. Though focused on spectroscopy for planetary exploration, our framework for data fusion evaluation and interpretation extends to other scientific domains with heterogeneous and scarce data and provides a principled approach evaluating data fusion strategies, interpreting modality contributions, and understanding tradeoffs among data fusion strategies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

A mathematical design framework for membrane pre-concentration in energy-efficient recovery of fermentation products

Due to the dilute nature of products manufactured via fermentation and cell-free bioprocessing, dewatering is a common unit operation in downstream processing (DSP) for bioproduct recovery, but it is typically energy intensive. To improve DSP energy efficiency for bio-based small molecules, integrating high-pressure membrane pre-concentration is a promising process option. However, this approach is typically constrained by a tradeoff between concentration factor (CF) and product recovery (PR), namely increasing the CF typically results in greater product loss, and vice versa. Here we developed a model that enables process design guidelines to: (i) identify scenarios in which the additional energy consumption and product loss from membrane pre-concentration are justified for use in DSP, and (ii) determine the optimal CF that minimizes process specific energy consumption. We compared the energy consumption of high-pressure membrane-integrated processes to evaporation-only processes and applied the model to an experimental case study for the separation and purification of butyric acid from Clostridium tyrobutyricum fermentation using an in situ product recovery (ISPR) process. The model estimated that integrating a tangential-flow reverse osmosis (RO) pre-concentration unit could reduce process energy consumption up to 45%. The use of advanced membrane pre-concentration technologies, such as negative rejection membranes and organic solvent reverse osmosis (OSRO), have the potential to further reduce the overall process specific energy consumption up to 96%, projected based on modeling. Overall, membrane pre-concentration, especially when strategically integrated prior to an evaporation step with optimized process conditions, holds significant potential for improving DSP energy efficiency, particularly in applications requiring substantial solvent removal for product recovery from dilute mixtures.

09 BIOMASS FUELS↗
DOE OSTI2025

Generation of a fluorescent short-lifetime oxygen nanosensor by coupling of an exciplex forming dye pair

Typical oxygen-sensitive dyes have lifetimes in the μs-ms regime for sensitive oxygen detection based on molecular quenching. Due to the long triplet-state lifetimes and poor quenching efficiency of these probes, it has been difficult to develop short lifetime probes. We have developed oxygen sensors using a short-lifetime dye (∼30–60 ns) that forms an anthracene-aniline exciplex, which is quenched by molecular oxygen through an excited-state charge transfer mechanism. To achieve measurements in aqueous systems, we have tethered the dyes together via a C3 alkyl linker to facilitate greater exciplex formation at low dye concentration (20 μg mL −1 ) and encapsulated the resulting compound into polymeric nanoparticles to form an aqueous-dispersible short-lifetime oxygen nanosensor. The sensors emit at 420 nm (unfolded dye) and 500 nm (exciplex), and the ratiometric Stern-Volmer Constant is 1.52 ± 0.02 L mol −1 , showing good sensitivity from 0 % to 40 % dissolved oxygen without the tradeoff of a long lifetime needed for direct molecular quenching. In this paper, we characterize this sensor for both lifetime-based measurements using time-correlated single-photon counting and ratiometric intensity-based measurements using the unfolded dye emission as an internal reference peak.

Biological and medical sciences↗
DOE OSTI2020

Impacts of directed evolution and soil management legacy on the maize rhizobiome

Domestication and agricultural intensification dramatically altered maize and its cultivation environment. Changes in maize genetics (G) and environmental (E) conditions increased productivity under high-synthetic-input conditions. However, novel selective pressures on the rhizobiome may have incurred undesirable tradeoffs in organic agroecosystems, where plants obtain nutrients via microbially mediated processes including mineralization of organic matter. Using twelve maize genotypes representing an evolutionary transect (teosintes, landraces, inbred parents of modern elite germplasm, and modern hybrids) and two agricultural soils with contrasting long-term management, here we integrated analyses of rhizobiome community structure, potential microbe-microbe interactions, and N-cycling functional genes to better understand the impacts of maize evolution and soil management legacy on rhizobiome recruitment. We show complex shifts in rhizobiome communities during directed evolution of maize (defined as the transition from teosinte to modern hybrids), with a larger effect of domestication (teosinte to landraces) than modern breeding (inbreds to hybrids) on rhizobiome structure and greater impacts of modern breeding on potential microbe-microbe interactions. Rhizobiome structure was significantly correlated with plant nutrient composition. Furthermore, plant biomass and nutrient content were affected by G x E interactions in which teosinte and landrace genotypes had better relative performance in the organic legacy soil than inbred and modern genotypes. The abundance of six N-cycling genes of relevance for plant nutrition and N loss pathways did not significantly differ between teosinte and modern rhizospheres in either soil management legacy. These results provide insight into the potential for improving maize adaptation to organic systems and contribute to interdisciplinary efforts toward developing resource-efficient, biologically based agroecosystems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Revising the dynamic energy budget theory with a new reserve mobilization rule and three example applications to bacterial growth

Dynamic energy budget (DEB) theory has been applied to model a wide range of organisms, including microbes. In the standard DEB model, biomass is partitioned into reserve and structural compartments, where reserve biomass is mobilized in a pseudolinear manner (while the reserve biomass density, defined as the ratio between reserve and structural biomass, decays linearly) to drive maintenance and the growth of structural biomass (and extracellular enzyme production if it is considered). However, the linear dynamics of the reserve biomass density makes the standard DEB model incapable of explaining the slowdown of microbial growth at high reserve density that is caused by macromolecular crowding effect which reduces biochemical reaction rates (a typical situation occurs when microbes are experiencing severe moisture stress) and is inconsistent with the observation that intracellular enzymatic reactions generally follow non-linear kinetics. By partitioning biomass into reserve, kinetic, and structural compartments, we show here that the Equilibrium Chemistry Approximation (ECA) kinetics can be used to represent enzymatically catalyzed reserve biomass mobilization that can then drive the kinetic and structural biomass synthesis. This revised DEB model better represents the tradeoff in ribosome allocation for structural growth and internal enzyme production, is structurally compatible with metabolic models of cell individuals, and includes the standard DEB model and the popular compromise model as special cases for representing population growth. We then applied the revised DEB model to interpret components of bacterial respiration, their dependence on substrate availability, and emergent microbial carbon use efficiency dynamics for an exponentially growing population. We found that the revised DEB model enables a better understanding of bacterial substrates use (carbon in our examples) than that can be derived from a few other models in the literature. In particular, the revised DEB model explains why carbon use efficiency may first increase, then plateau, and finally decrease with growth rate (and substrate uptake rate), as a function of proteomics. Additionally, the revised DEB model explains why the kinetic biomass compartment needs to be divided to reasonably incorporate proteomic control of microbial growth.

59 BASIC BIOLOGICAL SCIENCES↗