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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Genomic mechanisms of climate adaptation in polyploid bioenergy switchgrass

Long-term climate change and periodic environmental extremes threaten food and fuel security and global crop productivity. Although molecular and adaptive breeding strategies can buffer the effects of climatic stress and improve crop resilience, these approaches require sufficient knowledge of the genes that underlie productivity and adaptation—knowledge that has been limited to a small number of well-studied model systems. Here we present the assembly and annotation of the large and complex genome of the polyploid bioenergy crop switchgrass ( Panicum virgatum ). Analysis of biomass and survival among 732 resequenced genotypes, which were grown across 10 common gardens that span 1,800 km of latitude, jointly revealed extensive genomic evidence of climate adaptation. Climate–gene–biomass associations were abundant but varied considerably among deeply diverged gene pools. Furthermore, we found that gene flow accelerated climate adaptation during the postglacial colonization of northern habitats through introgression of alleles from a pre-adapted northern gene pool. The polyploid nature of switchgrass also enhanced adaptive potential through the fractionation of gene function, as there was an increased level of heritable genetic diversity on the nondominant subgenome. In addition to investigating patterns of climate adaptation, the genome resources and gene–trait associations developed here provide breeders with the necessary tools to increase switchgrass yield for the sustainable production of bioenergy.

09 BIOMASS FUELS↗
DOE OSTI2019

QTL × environment interactions underlie adaptive divergence in switchgrass across a large latitudinal gradient

Local adaptation is the process by which natural selection drives adaptive phenotypic divergence across environmental gradients. Theory suggests that local adaptation results from genetic trade-offs at individual genetic loci, where adaptation to one set of environmental conditions results in a cost to fitness in alternative environments. However, the degree to which there are costs associated with local adaptation is poorly understood because most of these experiments rely on two-site reciprocal transplant experiments. Here, we quantify the benefits and costs of locally adaptive loci across 17° of latitude in a four-grandparent outbred mapping population in outcrossing switchgrass ( Panicum virgatum L.), an emerging biofuel crop and dominant tallgrass species. We conducted quantitative trait locus (QTL) mapping across 10 sites, ranging from Texas to South Dakota. This analysis revealed that beneficial biomass (fitness) QTL generally incur minimal costs when transplanted to other field sites distributed over a large climatic gradient over the 2 y of our study. Therefore, locally advantageous alleles could potentially be combined across multiple loci through breeding to create high-yielding regionally adapted cultivars.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Evaluating cross-sectoral impacts of climate change and adaptations on the energy-water nexus: a framework and California case study

Abstract Electricity and water systems are inextricably linked through water demands for energy generation, and through energy demands for using, moving, and treating water and wastewater. Climate change may stress these interdependencies, together referred to as the energy-water nexus, by reducing water availability for hydropower generation and by increasing irrigation and electricity demand for groundwater pumping, among other feedbacks. Further, many climate adaptation measures to augment water supplies—such as water recycling and desalination—are energy-intensive. However, water and electricity system climate vulnerabilities and adaptations are often studied in isolation, without considering how multiple interactive risks may compound. This paper reviews the fragmented literature and develops a generalized framework for understanding these implications of climate change on the energy-water nexus. We apply this framework in a case study to quantify end-century direct climate impacts on California’s water and electricity resources and estimate the magnitude of the indirect cross-sectoral feedback of electricity demand from various water adaptation strategies. Our results show that increased space cooling demand and decreased hydropower generation are the most significant direct climate change impacts on California’s electricity sector by end-century. In California’s water sector, climate change impacts directly on surface water availability exceed demand changes, but have considerable uncertainty, both in direction and magnitude. Additionally, we find that the energy demands of water sector climate adaptations could significantly affect California’s future electricity system needs. If the worst-case water shortage occurs under climate change, water-conserving adaptation measures can provide large energy savings co-benefits, but other energy-intensive water adaptations may double the direct impacts of climate change on the state’s electricity resource requirement. These results highlight the value of coordinated adaptation planning between the energy and water sectors to achieve mutually beneficial solutions for climate resilience.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

TPR: Traffic Pattern-based Adaptive Routing for Dragonfly Networks

The Cray Cascade architecture uses Dragonfly as its interconnect topology and employs a globally adaptive routing scheme called UGAL. UGAL directs traffic based on link loads but may make inappropriate adaptive routing decisions in various situations, which degrades its performance. Here in this work, we propose traffic pattern-based adaptive routing (TPR) for Dragonfly that improves UGAL by incorporating a traffic pattern-based adaptation mechanism. The idea is to explicitly use the link usage statistics that are collected in performance counters to infer the traffic pattern, and to take the inferred traffic pattern plus link loads into consideration when making adaptive routing decisions. Furthermore, our performance evaluation results on a diverse set of traffic conditions indicate that by incorporating the traffic pattern-based adaptation mechanism, TPR is much more effective in making adaptive routing decisions and achieves significant lower latency under low load and higher throughput under high load than its underlying UGAL.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Rapid adaptation (or not) in restored plant populations

Abstract Mismatches between the traits of a colonizing population and a novel habitat can generate strong selection, potentially resulting in rapid adaptation. However, for most colonization events, it can be difficult to detect rapid adaptation or distinguish it from nonadaptive evolutionary changes. Here, I take advantage of a replicated prairie restoration experiment to compare recently established plant populations in two closely located restored prairies to each other and to their shared source population to test for rapid adaptation. Using a reciprocal transplant experiment six years after the populations were established, I found that one restored plant population showed evidence of adaptation, outperforming the other restored population when grown at its home site. In contrast, I detected no evidence for adaptation at the other site. These findings demonstrate that while rapid adaptation can occur in colonizing plant populations, it may not be the rule. Better understanding of when adaptation may or may not occur in these contexts may help us use evolution to our advantage, potentially improving establishment of desirable species in restored habitats.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Signatures of local nitrogen adaptation in the Brachypodium distachyon root microbiome

Plants associate with diverse microbiomes that impact their fitness, yet the contribution of the microbiome to plant adaptation is uncertain. As plant recruitment of its microbiome can be both highly variable and genetically determined, we hypothesized this recruitment process may be the result of adaptive evolution, and contributing to plant local adaptation. We investigated the evolution and adaptive benefit of plant–microbiome recruitment by characterizing the rhizosphere communities across a genotypic panel of Brachypodium distachyon in a common garden experiment. By linking microbial communities to their host genotype's historic environment, we identified signatures of selection on plant–microbiome recruitment. Plant–microbiome composition was significantly correlated with the host genotype's historic environment, with enrichment of microbial traits aligned to local resource conditions. For example, genotypes from low-nitrogen environments recruited communities enriched in nitrogen acquisition traits. In a complementary experiment evaluating plant nitrogen response, these same genotypes were well-adapted to low-nitrogen environments, contingent on the presence of key nitrogen-cycling microbes. These results suggest that local adaptation in plants may partially be mediated by recruitment of beneficial microbiomes. This perspective suggests that plant adaptation may be an emergent property of host–microbe interactions, where evolutionary responses favor traits that promote recruitment of locally beneficial microbiomes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Are We Adapting to Floods? Evidence from Global Flooding Fatalities

There has been a growing interest in understanding whether and how people adapt to extreme weather events in a changing climate. This article presents one of the first empirical analyses of adaptation to flooding on a global scale. Using a sample of 97 countries between 1985 and 2010, we investigate the extent and pattern of flood adaptation by estimating the effects of a country's climatological risk, recent flood experiences, and socioeconomic characteristics on its flood-related fatalities. Our results provide mixed evidence on adaptation: countries facing greater long-term climatological flooding risks do not necessarily adapt better and suffer fewer fatalities; however, after controlling for the cross-country heterogeneity, we find that more recent flooding shocks have a significant and negative effect on fatalities from subsequent floods. These findings may suggest the short-term learning dynamics of adaptation and potential inefficacy of earlier flood control measures, particularly those that promote increased exposure in floodplains. Our findings provide important implications for climate adaptation policy making and climate modeling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Adaptation to low pH and lignocellulosic inhibitors resulting in ethanolic fermentation and growth of Saccharomyces cerevisiae

Here, lignocellulosic bioethanol from renewable feedstocks using Saccharomyces cerevisiae is a promising alternative to fossil fuels owing to environmental challenges. S. cerevisiae is frequently challenged by bacterial contamination and a combination of lignocellulosic inhibitors formed during the pre-treatment, in terms of growth, ethanol yield and productivity. We investigated the phenotypic robustness of a brewing yeast strain TMB3500 and its ability to adapt to low pH thereby preventing bacterial contamination along with lignocellulosic inhibitors by short-term adaptation and adaptive lab evolution (ALE). The short-term adaptation strategy was used to investigate the inherent ability of strain TMB3500 to activate a robust phenotype involving pre-culturing yeast cells in defined medium with lignocellulosic inhibitors at pH 5.0 until late exponential phase prior to inoculating them in defined media with the same inhibitor cocktail at pH 3.7. Adapted cells were able to grow aerobically, ferment anaerobically (glucose exhaustion by 19 +/- 5 h to yield 0.45 +/- 0.01 g ethanol g glucose -1 ) and portray significant detoxification of inhibitors at pH 3.7, when compared to non-adapted cells. ALE was performed to investigate whether a stable strain could be developed to grow and ferment at low pH with lignocellulosic inhibitors in a continuous suspension culture. Though a robust population was obtained after 3600 h with an ability to grow and ferment at pH 3.7 with inhibitors, inhibitor robustness was not stable as indicated by the characterisation of the evolved culture possibly due to phenotypic plasticity. With further research, this short-term adaptation and low pH strategy could be successfully applied in lignocellulosic ethanol plants to prevent bacterial contamination.

09 BIOMASS FUELS↗
DOE OSTI2024

Adaptive Protection and Validated Models to Enable Deployment of High Penetrations of Solar PV (PV-MOD)

The availability and validation of various PV models in commercial tools differ, with some models not yet thoroughly validated for advanced inverter functionalities and reliable performance under weak system conditions. Many existing models do not fully incorporate new inverter control functions, which can affect system stability. The increasing deployment of solar PV and other inverter-based resources (IBRs), including distributed energy resources (DERs), is influencing the reliable operation of protection schemes in distribution systems and microgrids. Emerging adaptive protection schemes (APS) offer new opportunities for protecting these systems during varying configurations and DER operating conditions, though their demonstration and validation remain limited. Adaptive protection schemes face similar challenges, as they are typically designed for specific configurations. There is a growing need for tools and methodologies to streamline the deployment of adaptive protection for safe and reliable DER integration. The project main objective was to develop and validate high-fidelity generic models of solar PV facilities for stability, protection, EMT, and QSTS analyses. This objective was achieved, and these models can now be integrated into commercial software tools, enabling utilities, vendors, and developers to study high-penetration PV systems more confidently. The project also demonstrated advanced applications of these models, including the design and deployment of adaptive protection schemes in high-penetration field applications and microgrids, supporting grid safety and reliability. Several milestones were reached by the end of the project. A sophisticated inverter test plan was developed, and inverters representative of the North American marketplace were selected. EPRI and NREL tested various inverters, conforming to IEEE standards. Improvements were made to existing generic models of IBR units, IBR plants, and aggregated feeders for various analyses. The first generic electromagnetic transient (EMT) model for a solar PV plant was developed, conforming to IEEE Std 2800™-2022 and validated against laboratory measurements of a 2.2 MVA large-scale battery energy storage system (BESS) inverter. That model was then used to produce reference responses illustrating examples of validated and verified IBR plant models that pass or fail tests for technical minimum capability and performance as specified in the IEEE standard. The developed, tested, and validated generic models can be used for transmission planning, stability assessments, expansion planning, and evaluating potential future IBR interconnection requirements. They can also support interconnection screens and conformity assessments of IBR plants, including solar PV. The project significantly contributed to the ongoing standardization and model-based representation and verification of IBR responses. The project further addressed challenges of common distribution protection schemes with increasing deployment of DER by developing, validating, and demonstrating adaptive protection schemes (APS) that can improve the reliable and safe integration of DER into distribution systems. New APS were designed using improved DER models for three common distribution systems: a radial feeder, a meshed network, and a microgrid. Modeling and hardware-in-the-loop (HIL) testing of the APS were conducted, successfully showing their effectiveness and selectivity. Proof-of-concept field demonstration was achieved for two APS, i.e., one on a radial feeder and another one in a microgrid. Field demonstration could not be achieved for the APS on a meshed network, primarily due apprehension of one utility partner and also due to limited access to the protective algorithms in the network protectors. Guidelines developed from the lessons learned in the project lay out the general process followed in the design, installation, and commissioning of APS for various distribution systems. Distribution utility partners’ apprehension about field demonstration of the new APS were addressed—with varying success—by taking a stepped risk-management approach of modeling of a wide range of sensitivities first, performing in-depth proof-of-concept testing in the laboratory including HIL next, and finally deliberately implementing and commissioning the actual protection equipment and algorithms into parts of—or in parallel operation to—the three real distribution systems. Future work should include pilot projects that further show the acceptable performance of the developed APS before these schemes be rolled out more widely. Inclusion of both utility and original equipment manufacturers (OEMs) in future projects could increase chances of successful field demonstration. Despite challenges in achieving the field demonstration goal of the project for all three APS, the research significantly contributed to the innovation of adaptive protection solutions for scalable and reliable DER integration into distribution systems. This project significantly enhances the understanding of the impact of using appropriate inverter models on distribution and transmission (T&D) systems. By addressing the limitations of existing generic models, the project introduces high-fidelity models for stability, protection, electromagnetic transient (EMT), and quasi-static time series (QSTS) analyses. These models, integrated into commercial software tools, enable utilities, vendors, and developers to confidently study high-penetration PV systems. The project also demonstrates advanced applications, including adaptive protection schemes (APS) for distribution systems and microgrids, ensuring grid safety and reliability. The technical effectiveness and economic feasibility of the methods are evident through the development and validation of sophisticated inverter test plans and the selection of representative inverters. Testing by EPRI and NREL on retail, commercial, and utility-scale inverters, conforming to IEEE standards, underscores the robustness of the models. Improvements to existing generic models for various analyses further enhance their validity and applicability. The project also identifies gaps in common distribution protection schemes and designed new APS using improved DER models, demonstrating their effectiveness through modeling and hardware-in-the-loop (HIL) testing. The project’s benefits to the public are manifold. By advancing the standardization and model-based representation of IBR response, it supports transmission planning, stability assessments, and future IBR interconnection requirements. The generic models can facilitate better communication between transmission planners and developers, supporting expected IBR plant capability and performance. Additionally, the development of APS for radial feeders, meshed networks, and microgrids supports the integration of distributed energy resources (DERs) into distribution systems, enhancing grid reliability and safety. The project’s emphasis on thorough testing and simplicity in design ensures practical and scalable solutions for DER integration.

14 SOLAR ENERGY↗
DOE OSTI2022

An adaptive stochastic sequential quadratic programming with differentiable exact augmented lagrangians

In this study, we consider solving nonlinear optimization problems with a stochastic objective and deterministic equality constraints. We assume for the objective that its evaluation, gradient, and Hessian are inaccessible, while one can compute their stochastic estimates by, for example, subsampling. We propose a stochastic algorithm based on sequential quadratic programming (SQP) that uses a differentiable exact augmented Lagrangian as the merit function. To motivate our algorithm design, we first revisit and simplify an old SQP method Lucidi developed for solving deterministic problems, which serves as the skeleton of our stochastic algorithm. Based on the simplified deterministic algorithm, we then propose a non-adaptive SQP for dealing with stochastic objective, where the gradient and Hessian are replaced by stochastic estimates but the stepsizes are deterministic and prespecified. Finally, we incorporate a recent stochastic line search procedure Paquette and Scheinberg into the non-adaptive stochastic SQP to adaptively select the random stepsizes, which leads to an adaptive stochastic SQP. The global "almost sure" convergence for both non-adaptive and adaptive SQP methods is established. Numerical experiments on nonlinear problems in CUTEst test set demonstrate the superiority of the adaptive algorithm.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Challenging excited states from adaptive quantum eigensolvers: subspace expansions vs. state-averaged strategies

The prediction of electronic structure for strongly correlated molecules represents a promising application for near-term quantum computers. Significant attention has been paid to ground state wavefunctions, but excited states of molecules are relatively unexplored. In this work, we consider the adaptive, problem-tailored (ADAPT)-variational quantum eigensolver (VQE) algorithm, a single-reference approach for obtaining ground states, and its state-averaged generalization for computing multiple states at once. We demonstrate for both rectangular and linear H4, as well as for BeH2, that this approach, which we call multistate-objective, Ritz-eigenspectral (MORE)-ADAPT-VQE, can make better use of small excitation manifolds than an analogous method based on a single-reference ADAPT-VQE calculation, q-sc-EOM. In particular, MORE-ADAPT-VQE is able to accurately describe both avoided crossings and crossings between states of different symmetries. In addition to more accurate excited state energies, MORE-ADAPT-VQE can recover accurate transition dipole moments in situations where traditional ADAPT-VQE and q-sc-EOM struggle. These improvements suggest a promising direction toward the use of quantum computers for difficult excited state problems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

A Model-Reference Adaptive Direct-Power Control Scheme for Grid-Interactive Inverters

This paper develops an adaptive direct power control scheme for grid-interactive inverters while the control parameters are adaptively adjusted as the grid and filter parameters vary under different conditions. To demonstrate the efficacy and robustness of the adaptive operation, the performance of the adaptive controller is compared with a typical direct power controller by estimating the filter and grid impedances using a model reference parameter estimation technique with small signal injection. The simulation results verify that the developed methodology can track the reference power setpoints under output circuit parameter uncertainties while the typical design leads to instability. To improve the performance of the adaptive technique and eliminate the need for filter parameter estimation, a Lyapunov stability criterion-based model-reference adaptive direct power controller is designed to track the filter impedance. The developed method was tested using MATLAB/Simulink software to demonstrate the effectiveness of the proposed method. The results verify that adaptively tuning the control parameter can still maintain stable operation if the control gains are poorly selected while applying the classical method leads to abnormal operation or instability.

Gursoy, Mehmetcan↗
DOE OSTI2015

Dosimetric evaluation of three adaptive strategies for prostate cancer treatment including pelvic lymph nodes irradiation

Purpose: The movements of the prostate relative to the pelvic lymph nodes during intensity-modulated radiation therapy treatment can limit margin reduction and affect the protection of the organs at risk (OAR). In this study, the authors performed an analysis of three adaptive treatment strategies that combine information from both bony and gold marker registrations. The robustness of those treatments against the interfraction prostate movements was evaluated. Methods: A retrospective study was conducted on five prostate cancer patients with 7–13 daily cone-beam CTs (CBCTs). The clinical target volumes (CTVs) consisting of pelvic lymph nodes, prostate, and seminal vesicles as well as the OARs were delineated on each CBCT and the initial CT. Three adaptive strategies were analyzed. Two of these methods relied on a two-step patient positioning at each fraction. First step: a bony registration was used to deliver the nodal CTV prescription. Second step: a gold marker registration was then used either to (1) complete the dose delivered to the prostate (complement); (2) or give almost the entire prescription to the prostate with a weak dose gradient between the targets to compensate for possible motions (gradient). The third method (COR) used a pool of precalculated plans based on images acquired at previous treatment fractions. At each new fraction, a plan is selected from that pool based on the daily position of prostate center-of-mass. The dosimetric comparison was conducted and results are presented with and without the systematic shift in the prostate position on the CT planning. The adaptive strategies were compared to the current clinical standard where all fractions are treated with the initial nonadaptive plan. Results: The minimum daily prostate D{sub 95%} is improved by 2%, 9%, and 6% for the complement, the gradient, and the COR approaches, respectively, compared to the nonadaptive method. The average nodal CTV D{sub 95%} remains constant across the strategies, except for the gradient approach where a reduction of 7% is observed. However, a correction of the systematic shift reduced the problem, and the adaptive strategies remain robust against the prostate movement across the fraction. The bladder V{sub 55Gy} is reduced by 35% on average for the adaptive strategies. Conclusions: Because they offer increased CTV coverage and OAR sparing, adaptive methods may be suitable candidates for simple and efficient adaptive treatment strategies for prostate cancer. Margin reduction and systematic error correction in the prostate position improve the protection of the OAR and the dose coverage. A cumulative dose to simulate a complete treatment would show real effects and allow a better comparison between each method.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-I-10: Spatially Local Statistics for Adaptive Image Filtering

Purpose: To facilitate adaptive image filtering operations, addressing spatial variations in both noise and signal. Such issues are prevalent in cone-beam projections, where physical effects such as X-ray scattering result in spatially variant noise, violating common assumptions of homogeneous noise and challenging conventional filtering approaches to signal extraction and noise suppression. Methods: We present a computational mechanism for probing into and quantifying the spatial variance of noise throughout an image. The mechanism builds a pyramid of local statistics at multiple spatial scales; local statistical information at each scale includes (weighted) mean, median, standard deviation, median absolute deviation, as well as histogram or dynamic range after local mean/median shifting. Based on inter-scale differences of local statistics, the spatial scope of distinguishable noise variation is detected in a semi- or un-supervised manner. Additionally, we propose and demonstrate the incorporation of such information in globally parametrized (i.e., non-adaptive) filters, effectively transforming the latter into spatially adaptive filters. The multi-scale mechanism is materialized by efficient algorithms and implemented in parallel CPU/GPU architectures. Results: We demonstrate the impact of local statistics for adaptive image processing and analysis using cone-beam projections of a Catphan phantom, fitted within an annulus to increase X-ray scattering. The effective spatial scope of local statistics calculations is shown to vary throughout the image domain, necessitating multi-scale noise and signal structure analysis. Filtering results with and without spatial filter adaptation are compared visually, illustrating improvements in imaging signal extraction and noise suppression, and in preserving information in low-contrast regions. Conclusion: Local image statistics can be incorporated in filtering operations to equip them with spatial adaptivity to spatial signal/noise variations. An efficient multi-scale computational mechanism is developed to curtail processing latency. Spatially adaptive filtering may impact subsequent processing tasks such as reconstruction and numerical gradient computations for deformable registration. NIH Grant No. R01-184173.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Transcriptomic Analyses Elucidate Adaptive Differences of Closely Related Strains of Pseudomonas aeruginosa in Fuel

Pseudomonas aeruginosa can utilize hydrocarbons, but different strains have various degrees of adaptation despite their highly conserved genome. P. aeruginosa ATCC 33988 is highly adapted to hydrocarbons, while P. aeruginosa strain PAO1, a human pathogen, is less adapted and degrades jet fuel at a lower rate than does ATCC 33988. We investigated fuel-specific transcriptomic differences between these strains in order to ascertain the underlying mechanisms utilized by the adapted strain to proliferate in fuel. During growth in fuel, the genes related to alkane degradation, heat shock response, membrane proteins, efflux pumps, and several novel genes were upregulated in ATCC 33988. Overexpression of alk genes in PAO1 provided some improvement in growth, but it was not as robust as that of ATCC 33988, suggesting the role of other genes in adaptation. Expression of the function unknown gene PA5359 from ATCC 33988 in PAO1 increased the growth in fuel. Bioinformatic analysis revealed that PA5359 is a predicted lipoprotein with a conserved Yx(FWY)xxD motif, which is shared among bacterial adhesins. Overexpression of the putative resistance-nodulation-division (RND) efflux pump PA3521 to PA3523 increased the growth of the ATCC 33988 strain, suggesting a possible role in fuel tolerance. Interestingly, the PAO1 strain cannot utilize n -C 8 and n -C 10 . The expression of green fluorescent protein (GFP) under the control of alkB promoters confirmed that alk gene promoter polymorphism affects the expression of alk genes. Promoter fusion assays further confirmed that the regulation of alk genes was different in the two strains. Protein sequence analysis showed low amino acid differences for many of the upregulated genes, further supporting transcriptional control as the main mechanism for enhanced adaptation. Lastly, these results support that specific signal transduction, gene regulation, and coordination of multiple biological responses are required to improve the survival, growth, and metabolism of fuel in adapted strains. This study provides new insight into the mechanistic differences between strains and helpful information that may be applied in the improvement of bacterial strains for resistance to biotic and abiotic factors encountered during bioremediation and industrial biotechnological processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

A Molecular View of Plant Local Adaptation: Incorporating Stress-Response Networks

Ecological specialization in plants occurs primarily through local adaptation to different environments. Local adaptation is widely thought to result in costly fitness trade-offs that result in maladaptation to alternative environments. However, recent studies suggest that such trade-offs are not universal. Additionally, there is currently a limited understanding of the molecular mechanisms responsible for fitness trade-offs associated with adaptation. Here, we review the literature on stress responses in plants to identify potential mechanisms underlying local adaptation and ecological specialization. We focus on drought, high and low temperature, flooding, herbivore, and pathogen stresses. We then synthesize our findings with recent advances in the local adaptation and plant molecular biology literature. In the process, we identify mechanisms that could cause fitness trade-offs and outline scenarios where trade-offs are not a necessary consequence of adaptation. Lastly, future studies should aim to explicitly integrate molecular mechanisms into studies of local adaptation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Adaptive language model training for molecular design

Abstract The vast size of chemical space necessitates computational approaches to automate and accelerate the design of molecular sequences to guide experimental efforts for drug discovery. Genetic algorithms provide a useful framework to incrementally generate molecules by applying mutations to known chemical structures. Recently, masked language models have been applied to automate the mutation process by leveraging large compound libraries to learn commonly occurring chemical sequences (i.e., using tokenization) and predict rearrangements (i.e., using mask prediction). Here, we consider how language models can be adapted to improve molecule generation for different optimization tasks. We use two different generation strategies for comparison, fixed and adaptive. The fixed strategy uses a pre-trained model to generate mutations; the adaptive strategy trains the language model on each new generation of molecules selected for target properties during optimization. Our results show that the adaptive strategy allows the language model to more closely fit the distribution of molecules in the population. Therefore, for enhanced fitness optimization, we suggest the use of the fixed strategy during an initial phase followed by the use of the adaptive strategy. We demonstrate the impact of adaptive training by searching for molecules that optimize both heuristic metrics, drug-likeness and synthesizability, as well as predicted protein binding affinity from a surrogate model. Our results show that the adaptive strategy provides a significant improvement in fitness optimization compared to the fixed pre-trained model, empowering the application of language models to molecular design tasks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Adaptive Phenotypic Plasticity Stabilizes Evolution in Fluctuating Environments

Fluctuating environmental conditions are ubiquitous in natural systems, and populations have evolved various strategies to cope with such fluctuations. The particular mechanisms that evolve profoundly influence subsequent evolutionary dynamics. One such mechanism is phenotypic plasticity, which is the ability of a single genotype to produce alternate phenotypes in an environmentally dependent context. Here, we use digital organisms (self-replicating computer programs) to investigate how adaptive phenotypic plasticity alters evolutionary dynamics and influences evolutionary outcomes in cyclically changing environments. Specifically, we examined the evolutionary histories of both plastic populations and non-plastic populations to ask: (1) Does adaptive plasticity promote or constrain evolutionary change? (2) Are plastic populations better able to evolve and then maintain novel traits? And (3), how does adaptive plasticity affect the potential for maladaptive alleles to accumulate in evolving genomes? We find that populations with adaptive phenotypic plasticity undergo less evolutionary change than non-plastic populations, which must rely on genetic variation from de novo mutations to continuously readapt to environmental fluctuations. Indeed, the non-plastic populations undergo more frequent selective sweeps and accumulate many more genetic changes. We find that the repeated selective sweeps in non-plastic populations drive the loss of beneficial traits and accumulation of maladaptive alleles, whereas phenotypic plasticity can stabilize populations against environmental fluctuations. This stabilization allows plastic populations to more easily retain novel adaptive traits than their non-plastic counterparts. In general, the evolution of adaptive phenotypic plasticity shifted evolutionary dynamics to be more similar to that of populations evolving in a static environment than to non-plastic populations evolving in an identical fluctuating environment. All natural environments subject populations to some form of change; our findings suggest that the stabilizing effect of phenotypic plasticity plays an important role in subsequent adaptive evolution.

54 ENVIRONMENTAL SCIENCES↗