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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Alternate routes to acetate tolerance lead to varied isoprenol production from mixed carbon sources in Pseudomonas putida

ABSTRACT Lignocellulose is a renewable resource for the production of a diverse array of platform chemicals, including the biofuel isoprenol. Although this carbon stream provides a rich source of sugars, other organic compounds, such as acetate, can be used by microbial hosts. Here, we examined the growth and isoprenol production in a Pseudomonas putida strain pre-tolerized (“PT”) background where its native isoprenol catabolism pathway is deleted, using glucose and acetate as carbon sources. We found that PT displays impaired growth in minimal medium containing acetate and often fails to grow in glucose-acetate medium. Using a mutant recovery-based approach, we generated tolerized strains that overcame these limitations, achieving fast growth and isoprenol production in the mixed carbon feed. Changes in the glucose and acetate assimilation routes, including an upregulation in PP_0154 (SpcC, succinyl-CoA:acetate CoA-transferase) and differential expression of the gluconate assimilation pathways, were key for higher isoprenol titers in the tolerized strains, whereas a different set of mechanisms were likely enabling tolerance phenotypes in media containing acetate. Among these, a coproporphyrinogen-III oxidase (HemN) was upregulated across all tolerized strains and in one isolate required for acetate tolerance. Utilizing a defined glucose and acetate mixture ratio reflective of lignocellulosic feedstocks for isoprenol production in P. putida allowed us to obtain insights into the dynamics and challenges unique to dual carbon source utilization that are obscured when studied separately. Together, this enabled the development of a P. putida bioconversion chassis able to use a more complex carbon stream to produce isoprenol. IMPORTANCE Acetate is a relatively abundant component of many lignocellulosic carbon streams and has the potential to be used together with sugars, especially in microbes with versatile catabolism such as P. putida . However, the use of mixed carbon streams necessitates additional optimization. Furthermore, the use of P. putida for the production of the biofuel target, isoprenol, requires the use of engineered strains that have additional growth and production constraints when cultivated in acetate and glucose mixtures. In this study, we generate acetate-tolerant P. putida strains that overcome these challenges and examine their ability to produce isoprenol. We show that acetate tolerance and isoprenol production, although independent phenotypes, can both be optimized in a given P. putida strain. Using proteomics and whole genome sequencing, we examine the molecular basis of both phenotypes and show that tolerance to acetate can occur via alternate routes and result in different impacts on isoprenol production.

de Siqueira, Guilherme M. V. (ORCID:00000002364563↗
DOE OSTI2026

Improved 140 Nd Production for the 140 Nd/ 140 Pr In Vivo Generator through Target Recycling and Radiochemical Optimization

Theranostic strategies that utilize f-block therapeutic radionuclides, including 161 Tb, 177 Lu, 225 Ac, and 227 Th, suffer from a shortage of positron emission tomography (PET) imaging counterparts in the same chemical space and often rely on 68 Ga as a surrogate. The 140 Nd/ 140 Pr in vivo PET generator, which belongs to the f-block, may address this issue and can be produced via the 141 Pr(p,2n) 140 Nd production route by using medium-energy cyclotrons. However, impurities in the target material, including stable Nd, and the inherent difficulty of adjacent lanthanide separations limit the achievable radionuclidic and chemical purity of 140 Nd. In this work, we address these challenges through the purification and recycling of praseodymium target material and optimization of Nd/Pr separation. The resulting purified 140Nd was evaluated using DOTA and Macropa chelators via radiolabeling and in vitro stability studies. A target material purification and recycling method was developed for the monoisotopic 141 Pr starting material to remove stable Nd impurities, yielding 90.3 ± 4.7% (n = 3) recovery. The purified 141 Pr was isolated as Pr 6 O 11 and irradiated with 24 MeV protons (20.07 MeV at the target surface) at 20 μA for 4 h, which produced 1417.0 ± 83.4 MBq (38.3 ± 2.2 mCi) of 140 Nd at the end of bombardment (EOB). The produced 140 Nd was purified through an optimized DGA normal method to recover 71.6 ± 6.3% pure 140 Nd. The amount of stable Nd reduced progressively in each target purification cycle from >340 ppm without purification to <250 ppb after three cycles, while other measured metallic impurities were below 30 ppb. This improvement in target purity was reflected in the direct increase of apparent molar activity (AMA), when purified 140 Nd was evaluated with DOTA and Macropa chelators. AMA of [ 140 Nd]Nd-DOTA and [ 140 Nd]Nd-Macropa increased from 70.3 MBq/μmol (1.9 mCi/μmol) and 74 MBq/μmol (2.0 mCi/μmol) to 8025.3 MBq/μmol (216.9 mCi/μmol) and 8473.0 MBq/μmol (229.0 mCi/μmol), respectively, after the third target purification cycle. Further evaluation of chelator-labeled 140 Nd showed that [ 140 Nd]Nd-DOTA was stable in phosphate-buffered saline (PBS), saline, human serum, and mouse serum, whereas [140Nd]Nd-Macropa was stable in all except human serum. This work established a practical methodological advance for the production of 140 Nd/ 140 Pr in vivo PET generators, combining optimized target recycling and radiochemical separation to enable scaled-up and high-molar activity 140 Nd suitable for preclinical imaging. These advances support broader development of 140 Nd/ 140 Pr as a robust PET analogue, especially for f-block therapeutics.

Irradiation↗
NASA NTRS1990

Optimized testing of meshes

Efficient testing techniques for two-dimensional mesh interconnection networks are presented. The tests cover faults in the arbitration logic of the switches; this includes an examination of fault detection in the data paths, routing, and control circuitry, including the conflict resolution capabilities of mesh interconnection networks using topological test methods. The proposed methods are not implementation specific and can be applied to any design with a mesh topology. The topology and behavior of the network are described and definitions are presented. The fault model is defined and parallel testing methods for the entire network are given.

Malek, Miroslaw↗
NASA NTRS2016

A Mathematical Model and Algorithm for Routing Air Traffic Under Weather Uncertainty

A central challenge in managing today's commercial en route air traffic is the task of routing the aircraft in the presence of adverse weather. Such weather can make regions of the airspace unusable, so all affected flights must be re-routed. Today this task is carried out by conference and negotiation between human air traffic controllers (ATC) responsible for the involved sectors of the airspace. One can argue that, in so doing, ATC try to solve an optimization problem without giving it a precise quantitative formulation. Such a formulation gives the mathematical machinery for constructing and verifying algorithms that are aimed at solving the problem. This paper contributes one such formulation and a corresponding algorithm. The algorithm addresses weather uncertainty and has closed form, which allows transparent analysis of correctness, realism, and computational costs.

uncertainty↗
DOE OSTI2026

From Powder to Power: Tailored Pre-Milling Strategy that Optimizes Microstructure for Efficient Hydrogen Evolution

The hydrogen evolution reaction (HER) plays a critical role in enabling large-scale electrolytic hydrogen production and advancing future technologies and fuel production. Among non-precious metals, NiMo-based catalysts are particularly attractive due to their capability to promote both water dissociation and hydrogen adsorption in alkaline media. However, conventional NiMo catalysts often suffer from incomplete alloying, particle aggregation, weak metal–support interactions, and surface oxidation, which significantly limit active site utilization, electronic conductivity, and long-term stability. Herein, we report a scalable, solid-state, two-step ball milling strategy for constructing an efficient NiMo/C catalyst for the HER. Pre-milling the metal precursors prior to carbon incorporation promotes efficient solid-state activation, leading to the formation of uniformly alloyed, ultrafine, and defect-rich Ni–Mo nanoparticles with robust metal–carbon interfacial anchoring. Benefiting from this integrated structural design, the optimized NiMo/C catalyst exhibits low overpotentials and Tafel slopes, reduced charge-transfer resistance, and excellent durability under alkaline conditions. Comprehensive structural and surface analysis reveal that the enhanced HER performance can be attributed to the synergistic interplay of homogeneous Ni–Mo alloying, uniform nanoparticle dispersion on a defect-rich carbon scaffold, enhanced accessibility of catalytically active sites, and optimized electronic coupling that stabilizes the catalyst surface. This work highlights the two-step solid-state ball milling strategy as a simple, robust, and scalable route for the preparation of effective and durable non-precious metal HER electrocatalysts, offering practical insights toward large-scale and inexpensive hydrogen production.

Yang, Xiaoxuan [Oak Ridge National Laboratory (ORN↗
NASA NTRSDate not supplied

Rolling Horizon with K-Position Search Method for Strategic Deconfliction of Package Delivery UAS

In this research, the strategic deconfliction of unmanned aircraft systems for an urban package delivery environment with two depots and multiple drop-off locations is studied. This research aims to formulate a mathematical model to compute both the departure sequence and scheduled time of departure for each unmanned aircraft system at a depot, considering temporal constraints at en-route crossing waypoints and depots for strategic deconfliction. However, the problem formulation results in an NP-hard mixed-integer nonlinear programming problem for the global optimal solution, so instead, a "rolling horizon with𝑘-position search"heuristic method is developed. The simulation studies show that an increase in the value of𝑘(the parameter used to determine the size of the local neighborhood) reduces the average ground delay at the cost of an increase in the computation time for a given problem size. The study also shows an order of magnitude increase in the maximum number of flights scheduled with the integration of rolling horizon (time decomposition) compared to those without the integration of rolling horizon in the heuristic algorithm for a given computation time cut off.

UTM↗
DOE OSTI2025

Future marine biofuels in the port of Seattle region

Marine transportation, a vital global sector, emits 3% of global annual greenhouse gas emissions, which are predicted to increase in the future. Marine biofuels derived from biomass or waste sources like wood residue, waste oil and municipal solid waste can be used for decarbonization. However, limited studies have explored if sufficient marine biofuels could be produced and supplied to major regional ports given feedstock, supply chain and technological constraints. We fill this gap by evaluating the feasibility of supplying marine biofuels to the Port of Seattle. The Regional Bio-Economy Model (RBEM) and the Freight and Fuel Transportation Optimization Tool (FTOT) are used to build scenarios for simulating marine biofuel production in the Port region. We harmonized technoeconomic assumptions for RBEM and FTOT, input FTOT feedstock utilization and routing outputs into RBEM, and modelled conversion, feedstock, and policy scenario variations in RBEM. In RBEM, overall biofuel production was constrained primarily by the biofuel cost, and then by feedstock availability. Providing policy incentives and reducing permitting time frames alleviated these constraints and spurred the buildout of a robust industry through industrial learning dynamics in the initial years. With these measures in place, the RBEM results show that 100% of fuel demand at the Port can be supplied by biofuels with policy incentives and suitable technoeconomic conditions, but the addition of transportation cost considerations using FTOT led to 27.8% of demand being able to be met by biofuels at reasonable fuel delivery cost.

09 BIOMASS FUELS↗
DOE OSTI2025

Physiological roles of an Acinetobacter -specific σ factor

ABSTRACT The Gram-negative pathogen Acinetobacter baumannii is considered an “urgent threat” to human health due to its propensity to become antibiotic resistant. Understanding the distinct regulatory paradigms used by A. baumannii to mitigate cellular stresses may uncover new therapeutic targets. Many γ-proteobacteria use the extracytoplasmic function (ECF) σ factor, RpoE, to invoke envelope homeostasis networks in response to stress. Acinetobacter species contain the poorly characterized ECF “SigAb”; however, it is unclear if SigAb has the same physiological role as RpoE. Here, we show that SigAb is a metal stress-responsive ECF that appears unique to Acinetobacter species and distinct from RpoE-like ECFs. We combine promoter mutagenesis, motif scanning, and chromatin immunoprecipitation-sequencing (ChIP-seq) to define the direct SigAb regulon, which consists of genes encoding SigAb itself, the stringent response mediator, RelA, and the uncharacterized small RNA, “SabS.” However, RNA-seq of strains overexpressing SigAb revealed a large, indirect regulon containing hundreds of genes. Metal resistance genes are key elements of the indirect regulon, as CRISPRi knockdown of sigAb or sabS resulted in increased copper sensitivity and excess copper-induced SigAb-dependent transcription. Furthermore, we found that two uncharacterized genes in the sigAb operon, “ aabA ” and “ aabB ,” have anti-SigAb activity. Finally, employing a targeted Tn-seq approach that uses CRISPR-associated transposons, we show that sigAb , aabA , and aabB are important for fitness even during optimal growth conditions. Our work reveals new physiological roles for SigAb and SabS, provides a novel approach for assessing gene fitness, and highlights the distinct regulatory architecture of A. baumannii . IMPORTANCE Acinetobacter baumannii is a hospital-acquired pathogen, and many strains are resistant to multiple antibiotics. Understanding how A. baumannii senses and responds to stress may uncover novel routes to treat infections. Here, we examine how the Acinetobacter -specific transcription factor, SigAb, mitigates stress. We find that SigAb directly regulates only a small number of genes, but indirectly controls hundreds of genes that have substantial impacts on cell physiology. We show that SigAb is required for maximal growth, even during optimal conditions, and is acutely required during growth in the presence of elevated copper. Given that copper toxicity plays roles in pathogenesis and on copper-containing surfaces in hospitals, we speculate that SigAb function may be important in clinically relevant contexts.

Bacon, Emily E. (ORCID:0000000180907689)↗
NASA NTRS2025

Gaussian Process for Flight Delay Prediction: Learning a Stochastic Process

This paper presents a machine-learning approach to predict flight delays. Whereas neural networks are extensively studied for predictive capabilities, they involve non-intuitive design and extensive analysis, particularly in training and optimization processes. Instead, the proposed framework employs Gaussian Processes as a supervised learning technique for flight delay prediction. This data-driven approach trains the model using prior information, specifically the mean and covariance tied to existing data. The proposed Gaussian Process Regression (GPR) model employs the day of flight as a pivotal feature for delay forecasting. We analyze flights from various routes and gauge the accuracy of the presented learning technique by comparing the predicted delays with the actual ones. Given the inherent challenges in precisely forecasting delays, we predict the delays with a 95 % confidence interval. Also, an error propagation analysis in the prediction horizon is carried out to determine the optimal time frame for prediction. The proposed method for flight delay prediction is important as airlines can strategize flight operations and issue timely advisories.

stochastic↗
DOE OSTI2025

Impacts and emerging research opportunities in Vehicle-Grid Integration for transportation: A review

This review provides a comprehensive examination of Vehicle-Grid Integration (VGI) technologies and their impacts on transportation systems, with a particular emphasis on the transportation-energy nexus. It systematically explores how VGI affects key transportation applications such as charging infrastructure planning, electric vehicle (EV) routing, smart charging coordination, shared mobility, and dynamic pricing. By synthesizing recent literature from both transportation and energy systems perspectives, this study highlights how advanced methodologies, such as reinforcement learning, game theory, and optimization techniques, are used to model the complex interactions between EVs, mobility patterns, and distributed energy systems. Furthermore, the review also identifies critical challenges, including behavioral factors, data limitations, and system scalability. Drawing on these insights, the paper outlines emerging research opportunities to support the design of integrated, resilient, and user-centric VGI solutions that advance sustainable mobility and energy system efficiency.

Charging coordination↗
DOE OSTI2025

Parametric Optimization of Nanostructured Alumina Forming Austenitic Alloys

Alumina-forming austenitic (AFA) alloys provide excellent oxidation resistance through the formation of a stable alumina scale, but their relatively high Ni content might limit application in core structural components because of helium generation and swelling under irradiation. Increasing the density of nanoscale features in the microstructure is a promising route to improve sink strength and mitigate these effects. Conventional oxide dispersion–strengthened (ODS) steels achieve this through mechanical alloying (MA), but the approach is costly and difficult to scale. In this milestone, additive manufacturing was applied as an alternative pathway to fabricate nanostructured AFA (NAFA) alloys with dual precipitation of oxides and nitrides enabled by reactive atmosphere processing. In FY25, two compositions, NAFA-1 (AFA-05) and NAFA-2, were produced and compared. Both alloys achieved densities above 99% of theoretical values, but NAFA-2 exhibited microcracking associated with Nb-rich intermetallic formation, indicating the need for further chemistry optimization. Nitrogen and oxygen uptake was confirmed on selected builds, demonstrating the intended dual-precipitate dispersion. Mechanical testing showed that AM-processed NAFA alloys exceed conventionally produced ODS steels in high-temperature tensile strength and fracture toughness. Preliminary Cu ion irradiation results further suggest improved resistance compared to wrought austenitic alloys. While the current alloys are promising for their compatibility in high-temperature air or liquid Pb environments, modifications to composition will be required for long-term operation in high-temperature impure sodium systems. Future work will focus on refining alloy chemistry to suppress laser powder bed fusion–induced cracking and scaling production to reactor-relevant dimensions using directed energy deposition as a pathway toward net-shape cladding fabrication.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Genomic insights into local adaptation and migration success in reintroduced Coho Salmon of the Wenatchee River basin

ABSTRACT Objective Reintroduction of salmonids into regions where they have been extirpated is a common conservation strategy that is often implemented through natural recolonization, translocation of natural populations, or hatchery-based programs. Locally adapting to specific environmental conditions is critical for long-term population viability, particularly for species like Coho Salmon Oncorhynchus kisutch, which face diverse selective pressures during their migration. This study focused on the mid-Columbia River Coho Salmon reintroduction program managed by Yakama Nation Fisheries, which has successfully reintroduced Coho Salmon into the Wenatchee and Methow River basins, Washington. Notably, these populations have adapted to the longer migration route than those in the founding stock, with selection favoring individuals with an earlier arrival time and that can navigate a 15-km, high-gradient canyon to reach optimal spawning grounds. The objectives of this study were to investigate whether specific genomic regions are under selection for traits associated with return location and timing in Coho Salmon. Methods Low-coverage whole-genome resequencing data were used to screen for genomic regions associated with the phenotypes of interest. Results A weak polygenic signal in female Coho Salmon was found to be associated with return group, with a subset of candidate adaptive regions occurring across eight chromosomes. Conclusions These findings provide insights into the genomic mechanisms underlying local adaptation in reintroduced salmon populations and inform broodstock selection strategies aimed at promoting natural production and long-term population sustainability.

Horn, Rebekah L.↗
NASA NTRS1995

A Mars Rover Mission Simulation on Kilauea Volcano

A field experiment to simulate a rover mission on Mars was performed using the Russian Marsokhod rover deployed on Kilauea Volcano HI in February, 1995. A Russian Marsokhod rover chassis was equipped with American avionics equipment, stereo cameras on a pan and tilt platform, a digital high resolution body-mounted camera, and a manipulator arm on which was mounted a camera with a close-up lens. The six wheeled rover is 2 meters long and has a mass of 120 kg. The imaging system was designed to simulate that used on the planned "Mars Together" mission. The rover was deployed on Kilauea Volcano HI and operated from NASA Ames by a team of planetary geologists and exobiologists. Two modes of mission operations were simulated for three days each: (1) long time delay, low data bandwidth (simulating a Mars mission), and (2) live video, wide-bandwidth data (allowing active control simulating a Lunar rover mission or a Mars rover mission controlled from on or near the Martian surface). Simulated descent images (aerial photographs) were used to plan traverses to address a detailed set of science questions. The actual route taken was determined by the science team and the traverse path was frequently changed in response to the data acquired and to unforeseen operational issues. Traverses were thereby optimized to efficiently answer scientific questions. During the Mars simulation, the rover traversed a distance of 800 m. Based on the time delay between Earth and Mars, we estimate that the same operation would have taken 30 days to perform on Mars. This paper will describe the mission simulation and make recommendations about incorporating rovers into the Mars surveyor program.

Stoker, Carol↗
NASA NTRS1993

Optimization of microscopic and macroscopic second order optical nonlinearities

Nonlinear optical materials (NLO) can be used to extend the useful frequency range of lasers. Frequency generation is important for laser-based remote sensing and optical data storage. Another NLO effect, the electro-optic effect, can be used to modulate the amplitude, phase, or polarization state of an optical beam. Applications of this effect in telecommunications and in integrated optics include the impression of information on an optical carrier signal or routing of optical signals between fiber optic channels. In order to utilize these effects most effectively, it is necessary to synthesize materials which respond to applied fields very efficiently. In this talk, it will be shown how the development of a fundamental understanding of the science of nonlinear optics can lead to a rational approach to organic molecules and materials with optimized properties. In some cases, figures of merit for newly developed materials are more than an order of magnitude higher than those of currently employed materials. Some of these materials are being examined for phased-array radar and other electro-optic switching applications.

Marder, Seth R.↗
NASA NTRS2000

Wind Prediction Accuracy for Air Traffic Management Decision Support Tools

The performance of Air Traffic Management and flight deck decision support tools depends in large part on the accuracy of the supporting 4D trajectory predictions. This is particularly relevant to conflict prediction and active advisories for the resolution of conflicts and the conformance with of traffic-flow management flow-rate constraints (e.g., arrival metering / required time of arrival). Flight test results have indicated that wind prediction errors may represent the largest source of trajectory prediction error. The tests also discovered relatively large errors (e.g., greater than 20 knots), existing in pockets of space and time critical to ATM DST performance (one or more sectors, greater than 20 minutes), are inadequately represented by the classic RMS aggregate prediction-accuracy studies of the past. To facilitate the identification and reduction of DST-critical wind-prediction errors, NASA has lead a collaborative research and development activity with MIT Lincoln Laboratories and the Forecast Systems Lab of the National Oceanographic and Atmospheric Administration (NOAA). This activity, begun in 1996, has focussed on the development of key metrics for ATM DST performance, assessment of wind-prediction skill for state of the art systems, and development/validation of system enhancements to improve skill. A 13 month study was conducted for the Denver Center airspace in 1997. Two complementary wind-prediction systems were analyzed and compared to the forecast performance of the then standard 60 km Rapid Update Cycle - version 1 (RUC-1). One system, developed by NOAA, was the prototype 40-km RUC-2 that became operational at NCEP in 1999. RUC-2 introduced a faster cycle (1 hr vs. 3 hr) and improved mesoscale physics. The second system, Augmented Winds (AW), is a prototype en route wind application developed by MITLL based on the Integrated Terminal Wind System (ITWS). AW is run at a local facility (Center) level, and updates RUC predictions based on an optimal interpolation of the latest ACARS reports since the RUC run. This paper presents an overview of the study's results including the identification and use of new large mor wind-prediction accuracy metrics that are key to ATM DST performance.

Cole, Rod↗
NASA NTRS2022

Scheduling For Urban Air Mobility Using Safe Learning

This work considers the scheduling problem for Urban Air Mobility (UAM) vehicles travelling between origin-destination pairs with both hard and soft trip deadlines. Each route is described by a discrete probability distribution over trip completion times (or delay) and over interarrival times of requests (or demand) for the route along with a fixed hard or soft deadline. Soft deadlines carry a cost that is incurred when the deadline is missed. An online, safe scheduler is developed that ensures that hard deadlines are never missed and that average cost of missing soft deadlines is minimized. The system is modelled as a Markov Decision Process (MDP) and safe model based learning is used to find the probabilistic distributions over route delays and demand. Monte Carlo Tree Search (MCTS) Earliest Deadline First (EDF) is used to safely explore the learned models in an online fashion and develop a near-optimal non-preemptive scheduling policy. These results are compared with Value Iteration (VI) and MCTS (Random) scheduling solutions.

Urban Air Mobility↗
NASA NTRSDate not supplied

Scheduling for Urban Air Mobility using Safe Learning

This work considers the scheduling problem for Urban Air Mobility (UAM) vehicles travelling between origin-destination pairs with both hard and soft trip deadlines. Each route is described by a discrete probability distribution over trip completion times (or delay) and over interarrival times of requests (or demand) for the route along with a fixed hard or soft deadline. Soft deadlines carry a cost that is incurred when the deadline is missed. An online, safe scheduler is developed that ensures that hard deadlines are never missed and that average cost of missing soft deadlines is minimized. The system is modelled as a Markov Decision Process (MDP) and safe model based learning is used to find the probabilistic distributions over route delays and demand. Monte Carlo Tree Search (MCTS) Earliest Deadline First (EDF) is used to safely explore the learned models in an online fashion and develop a near-optimal non-preemptive scheduling policy. These results are compared with Value Iteration (VI) and MCTS (Random) scheduling solutions.

Urban Air Mobility↗
DOE OSTI2026

Designing the Protocols for Programmable Ammonia Catalysis

Programmable catalysis can provide a more energy-efficient and cost-effective route to enhancing commercial ammonia production, a key process in the advancement of renewable energy technologies and the manufacture of fertilizers and basic chemicals. This work explores the computational discovery of optimal forcing protocols to drive such dynamic catalysis models. By employing matrix-free time-stepper methods, coupled with an optimization approach, that integrates Bayesian optimization with a Bayesian continuation strategy to efficiently discover the periodic steady states of such periodically forced systems, we enable the discovery of complex optimal catalyst strain waveforms, while ensuring robust solver convergence. We demonstrate the flexibility of our approach to discover optimized forcing protocols under varying physical constraints on strain modulation or other catalyst operating parameters. We show that these can have a temporal structure more complex than simple step functions. In order to detect undesirable catalytic loops that may correlate with overall reduced performance, we perform a study using graph-theoretical analysis to investigate the dynamics of catalytic kinetic networks formed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗