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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 OSTI2021

Symbolic pregression: Discovering physical laws from distorted video

In this work, we present a method for unsupervised learning of equations of motion for objects in raw and optionally distorted unlabeled synthetic video (or, more generally, for discovering and modeling predictable features in time-series data). We first train an autoencoder that maps each video frame into a low-dimensional latent space where the laws of motion are as simple as possible, by minimizing a combination of nonlinearity, acceleration, and prediction error. Differential equations describing the motion are then discovered using Pareto-optimal symbolic regression. We find that our pre-regression (“pregression”) step is able to rediscover Cartesian coordinates of unlabeled moving objects even when the video is distorted by a generalized lens. Using intuition from multidimensional knot theory, we find that the pregression step is facilitated by first adding extra latent space dimensions to avoid topological problems during training and then removing these extra dimensions via principal component analysis. An inertial frame is autodiscovered by minimizing the combined equation complexity for multiple experiments.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

A first principles framework to predict the transient performance of latent heat thermal energy storage

Thermal energy storage (TES) is increasingly recognized as an essential component of efficient Combined Heat and Power (CHP), Concentrated Solar Power (CSP), Heating Ventilation and Air Conditioning (HVAC), and refrigeration as it reduces peak demand while helping to manage intermittent availability of energy (e.g., from solar or wind). Latent Heat Thermal Energy Storage (LHTES) is a viable option because of its high energy storage density. Parametric analysis of LHTES in terms of dimensionless numbers is highly desired as a tool to model LHTES systems. One approach is to develop a model equation so as to minimize the error between the model and data obtained from experiments or simulations. While this approach can produce an accurate correlation applicable within the range of data used for its creation, it does not provide physical understanding of the rate-limiting process controlling the transient behavior of the device. In this paper we present an alternative approach whereby the potential rate-limiting processes are identified from first principles and then the key process is determined as a function of time as a LHTES device is charged. For example, in a simple geometry, the melt-fraction can be expected to vary linearly in time if the heat transfer rate is limited by natural convection of the phase changing material and we show it scales with the PCM Grashof number as $Gr^1_p$ and PCM Prandtl number as $Pr_p^{(1/3)}$. On the other hand, if surface area of solid PCM limits the heat transfer rate, the melt fraction increases asymptotically to reach full melting. The existence of these linear and asymptotic regions and the $Gr^1_pP r^{1/3}_p$ shape of the melt fraction curve is verified using our database of 64 simulations. Of practical importance in designing LHTES devices is the melt fraction at which the heat transfer rate ceases to be limited by convection, after which the heat storage rate deteriorates. For our geometry, this is found to be about 90%. This test case of our methodology shows the value of our approach, that predicting heat storage rate based on the rate-limiting physical phenomenon as a function of time is an effective approach to modeling LHTES devices.

25 ENERGY STORAGE↗
DOE OSTI2019

Structural and electronic properties of the spin-filter material CrVTiAl with disorder

The effects of chemical disorder on the electronic properties of the spin-filter material CrVTiAl are investigated experimentally and theoretically. Synchrotron X-ray diffraction experiments on bulk CrVTiAl and the associated Rietveld analysis indicate that the crystal structure consists primarily of a mixture of a partially ordered B2 phase, a fully disordered A2 phase, and a small component of an ordered L2 1 or Y phase. High temperature resistivity measurements confirm the existence of a bandgap. First-principles, all-electron, self-consistent electronic structure computations show that the chemically disordered A2 and B2 phases are metallic, while the spin-filter properties of the ideal Y-type phase are preserved in the presence of L2 1 disorder (Cr and V mixing). The Hall coefficient is found to decrease with increasing temperature, similar to the measured increase in the conductivity, indicating the presence of thermally activated semiconductor-like carriers.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Evaluating Water Assets Using Water Efficiency Framework for Infrastructure Intensive Agency

Water infrastructure-intensive organizations should incorporate sustainability principles when making decisions on infrastructure investments to ensure the long-term resilience of mission-critical equipment and components. A water efficiency evaluation framework to inform infrastructure investments is discussed and applied to three federal campuses. The methodology considered emphasizes the iterative process between data analysis and decision-making; evaluates cost-sharing solution alternatives when making final recommendations; considers both internal and external stakeholder perceptions of project outcomes and future planning; and makes explicit government and community preferences when evaluating projects. Case study findings underscore condition evaluations for infrastructure that are critical to setting a baseline for system performance and determining desired potential upgrades and sustainment strategies. Such a holistic approach has demonstrated effectiveness for understanding, classifying, and recommending innovative water asset solutions that are necessary for the public sector to consider in today’s complex, modern planning environment.

Asset Management, Alternative Water, evaluation, P↗
DOE OSTI2019

Particle Flow Solarthermal Redox Process to Split Water

The aim of this project is to develop novel solarthermal water splitting (STWS) materials and a STWS reactor capable of producing hydrogen gas in an economic (<2/gge H 2 ) and efficient manner (>26% solar to hydrogen efficiency) at commercial scales (>50,000 kg of H 2 /day). To meet these targets, new materials must be developed with high intrinsic STWS efficiencies and then fabricated into a robust, long-lived “reactor ready” form. Additionally, scalable novel reactors are necessary to efficiently deliver the solar heat to the reacting materials while minimizing parasitic efficiency losses such as unnecessary heating and cooling, electrical work and heat losses from the reactor (such as radiation, or conduction). In this project we will: 1) develop new materials capable of meeting the targets outlined above; 2) develop particle formulation capable of producing attrition resistant, long lived, “reactor ready” particles; 3) evaluate and refine the individual reactor components of our Particle Flow Solarthermal Reactor design; 4) develop an overall system model to be used for reactor design improvement and economic analysis; and 5) produce at least three liters of H 2 on-sun in an eight hour day using our developed materials and reactor design principles. Overall, we will move our STWS process from Technology Readiness Level (TRL) 2 to TRL3.

08 HYDROGEN↗
DOE OSTI2017

A parts list for fungal cellulosomes revealed by comparative genomics

Here, cellulosomes are large, multiprotein complexes that tether plant biomass-degrading enzymes together for improved hydrolysis. These complexes were first described in anaerobic bacteria, where species-specific dockerin domains mediate the assembly of enzymes onto cohesin motifs interspersed within protein scaffolds. The versatile protein assembly mechanism conferred by the bacterial cohesin–dockerin interaction is now a standard design principle for synthetic biology. For decades, analogous structures have been reported in anaerobic fungi, which are known to assemble by sequence-divergent non-catalytic dockerin domains (NCDDs). However, the components, modular assembly mechanism and functional role of fungal cellulosomes remain unknown. Here, we describe a comprehensive set of proteins critical to fungal cellulosome assembly, including conserved scaffolding proteins unique to the Neocallimastigomycota. High-quality genomes of the anaerobic fungi Anaeromyces robustus , Neocallimastix californiae and Piromyces finnis were assembled with long-read, single-molecule technology. Genomic analysis coupled with proteomic validation revealed an average of 312 NCDD-containing proteins per fungal strain, which were overwhelmingly carbohydrate active enzymes (CAZymes), with 95 large fungal scaffoldins identified across four genera that bind to NCDDs. Fungal dockerin and scaffoldin domains have no similarity to their bacterial counterparts, yet several catalytic domains originated via horizontal gene transfer with gut bacteria. However, the biocatalytic activity of anaerobic fungal cellulosomes is expanded by the inclusion of GH3, GH6 and GH45 enzymes. These findings suggest that the fungal cellulosome is an evolutionarily chimaeric structure—an independently evolved fungal complex that co-opted useful activities from bacterial neighbours within the gut microbiome.

09 BIOMASS FUELS↗
DOE OSTI2015

Design of smart 3D-digital X-ray microtomographic scanners for non-destructive testing of materials and components of electronic devices with a multilayered structure

The article studies the operating procedures of an X-ray microtomographic scanner and the module of reconstruction and analysis 3D-image of a test sample in particular. An algorithm for 3D-image reconstruction based on image shadow projections and mathematical methods of the processing are described. Chapter 1 describes the basic principles of X-ray tomography and general procedures of the device developed. Chapters 2 and 3 are devoted to the problem of resources saving by the system during the X-ray tomography procedure, which is achieved by preprocessing of the initial shadow projections. Preprocessing includes background noise removing from the images, which reduces the amount of shadow projections in general and increases the efficiency of the group shadow projections compression. Chapter 4 covers general procedures of defect search, which is based on vector analysis principles. In conclusion, the main applications of X-ray tomography are presented.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

New method for fitting coefficients in standard model effective theory

We present an alternative method for carrying out a principal-component analysis of Wilson coefficients in standard model effective field theory (SMEFT). The method is based on singular-value decomposition (SVD). The SVD method provides information about the sensitivity of experimental observables to physics beyond the standard model that is not accessible in the Fisher-information method. In principle, the SVD method can also have computational advantages over diagonalization of the Fisher information matrix. We demonstrate the SVD method by applying it to the dimension-6 coefficients for the process of top-quark decay to a b quark and a W boson and use this example to illustrate some pitfalls in widely used fitting procedures. We also outline an iterative procedure for applying the SVD method to dimension-8 SMEFT coefficients.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Phylogenetic diversity of 200+ isolates of the ectomycorrhizal fungus Cenococcum geophilum associated with Populus trichocarpa soils in the Pacific Northwest, USA and comparison to globally distributed representatives

The ectomycorrhizal fungal symbiont Cenococcum geophilum is of high interest as it is globally distributed, associates with many plant species, and has resistance to multiple environmental stressors. C . geophilum is only known from asexual states but is often considered a cryptic species complex, since extreme phylogenetic divergence is often observed within nearly morphologically identical strains. Alternatively, C . geophilum may represent a highly diverse single species, which would suggest cryptic but frequent recombination. Here we describe a new isolate collection of 229 C . geophilum isolates from soils under Populus trichocarpa at 123 collection sites spanning a ~283 mile north-south transect in Western Washington and Oregon, USA (PNW). To further understanding of the phylogenetic relationships within C . geophilum , we performed maximum likelihood and Bayesian phylogenetic analyses to assess divergence within the PNW isolate collection, as well as a global phylogenetic analysis of 789 isolates with publicly available data from the United States, Japan, and European countries. Phylogenetic analyses of the PNW isolates revealed three distinct phylogenetic groups, with 15 clades that strongly resolved at >80% bootstrap support based on a GAPDH phylogeny and one clade segregating strongly in two principle component analyses. The abundance and representation of PNW isolate clades varied greatly across the North-South range, including a monophyletic group of isolates that spanned nearly the entire gradient at ~250 miles. A direct comparison between the GAPDH and ITS rRNA gene region phylogenies, combined with additional analyses revealed stark incongruence between the ITS and GAPDH gene regions, consistent with intra-species recombination between PNW isolates. In the global isolate collection phylogeny, 34 clades were strongly resolved using Maximum Likelihood and Bayesian approaches (at >80% MLBS and >0.90 BPP respectively), with some clades having intra- and intercontinental distributions. Together these data are highly suggestive of divergence within multiple cryptic species, however additional analyses such as higher resolution genotype-by-sequencing approaches are needed to distinguish potential species boundaries and the mode and tempo of recombination patterns.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

First-Cycle Simulation for Li-Rich Layered Oxide Cathode Material x Li 2 MnO 3 • (1- x )Li M O 2 ( x = 0.4)

Here, lithium-rich layered oxides (LRLO) x Li 2 MnO 3 • (1- x )Li M O 2 continue to attract attention owing to their promise of high capacity and energy density as lithium-ion battery cathodes, despite the degradation of atomic structure and energy density (voltage fade) with cycling. First-principles DFT calculations for the model systems M = Co and M = Mn 0.5 Ni 0.5 provide insights into the atomic-scale transformations in the bulk during the first charge and discharge of LRLO. The simulations were performed with the VASP code at the GGA+ U level. Molecular dynamics simulations were conducted at T = 1000 K (charge) and 2000 K (discharge) to accelerate the dynamics. Considerable Co migration to the Li layer occurs during the first charge for the system with M = Co, but the Li M O 2 component remains substantially intact for the system with M = Mn 0.5 Ni 0.5 . First-charge oxygen dimerization in the M = Co system occurs in both the Li M O 2 and the Li 2 MnO 3 components of the material, and exceeds than for M = Mn 0.5 Ni 0.5 , where dimerization is essentially confined to the Li 2 MnO 3 component. About half of the oxygen dimers created during the voltage plateau dissociate during the first discharge. Analysis of the redox suggests that some Mn 3+ is generated during the first charge for the system M = Co.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

A review on recent machine learning applications for imaging mass spectrometry studies

Imaging mass spectrometry (IMS) is a powerful analytical technique widely used in biology, chemistry, and materials science fields that continue to expand. IMS provides a qualitative compositional analysis and spatial mapping with high chemical specificity. The spatial mapping information can be 2D or 3D depending on the analysis technique employed. Due to the combination of complex mass spectra coupled with spatial information, large high-dimensional datasets (hyperspectral) are often produced. Therefore, the use of automated computational methods for an exploratory analysis is highly beneficial. The fast-paced development of artificial intelligence (AI) and machine learning (ML) tools has received significant attention in recent years. These tools, in principle, can enable the unification of data collection and analysis into a single pipeline to make sampling and analysis decisions on the go. There are various ML approaches that have been applied to IMS data over the last decade. Here, in this review, we discuss recent examples of the common unsupervised (principal component analysis, non-negative matrix factorization, k-means clustering, uniform manifold approximation and projection), supervised (random forest, logistic regression, XGboost, support vector machine), and other methods applied to various IMS datasets in the past five years. The information from this review will be useful for specialists from both IMS and ML fields since it summarizes current and representative studies of computational ML-based exploratory methods for IMS.

47 OTHER INSTRUMENTATION↗
DOE OSTI2018

A Hyperthermophilic Phage Decoration Protein Suggests Common Evolutionary Origin with Herpesvirus Triplex Proteins and an Anti-CRISPR Protein

Virus capsids are protein shells that protect the viral genome from environmental assaults, while maintaining the high internal pressure of the tightly packaged genome. To elucidate how capsids maintain stability under harsh conditions, we investigated the capsid components of the hyperthermophilic phage P74-26. We determined the structure of capsid protein gp87 and show that it has the same fold as decoration proteins in many other phages, despite lacking significant sequence homology. Interestingly, we also find that gp87 is significantly more stable than mesophilic homologs. Our analysis of the gp87 structure reveals that the core “β tulip” domain is conserved in trimeric capsid components across numerous double-stranded DNA viruses, including Herpesviruses. Moreover, this β barrel domain is found in anti-CRISPR protein AcrIIC1, suggesting a mechanism for the evolution of this Cas9 inhibitor. Our work illustrates the principles for increased stability of gp87, and extends the evolutionary reach of the β tulip domain.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Inhomogeneity of Cellulose Microfibril Assembly in Plant Cell Walls Revealed with Sum Frequency Generation Microscopy

Sum frequency generation (SFG) vibrational spectroscopy can selectively detect and analyze noncentrosymmetric components interspersed in amorphous matrices; this principle has been used for studies of nanoscale structure and mesoscale assembly of cellulose in plant cell walls. However, the spectral information averaged over a large area or volume cannot provide regiospecific or tissue-specific information of different cells in plants. Here, we demonstrate spatially resolved SFG analysis and imaging by combining a broad-band SFG spectroscopy system with an optical microscope. The system was designed to irradiate both narrow-band 800 nm and broad-band tunable IR beams through a single reflective objective lens, but from opposite sides of the surface normal direction of the sample. The developed technique was used to reveal inhomogeneous distributions of cellulose microfibrils within single cell walls, such as cotton fibers and onion epidermis as well as among different tissues in Arabidopsis inflorescence stems and bamboo culms. SFG microscopy can be used for vibrational spectroscopic imaging of other biological systems in complement to conventional Fourier transform infrared spectroscopy and confocal Raman microscopy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Dynamic heterogeneity of DNA methylation and hydroxymethylation in embryonic stem cell populations captured by single-cell 3D high-content analysis

Cell-surface markers and transcription factors are being used in the assessment of stem cell fate and therapeutic safety, but display significant variability in stem cell cultures. We assessed nuclear patterns of 5-hydroxymethylcytosine (5hmC, associated with pluripotency), a second important epigenetic mark, and its combination with 5-methylcytosine (5mC, associated with differentiation), also in comparison to more established markers of pluripotency (Oct-4) and endodermal differentiation (FoxA2, Sox17) in mouse embryonic stem cells (mESC) over a 10-day differentiation course in vitro: by means of confocal and super-resolution imaging together with 3D high-content analysis, an essential tool in single-cell screening. In summary: 1) We did not measure any significant correlation of putative markers with global 5mC or 5hmC. 2) While average Oct-4 levels stagnated on a cell-population base (0.015 lnIU/day), Sox17 and FoxA2 increased 22-fold and 3-fold faster, respectively (Sox17: 0.343 lnIU/day; FoxA2: 0.046 lnIU/day). In comparison, global DNA methylation levels increased 4-fold faster (0.068 lnIU/day), and global hydroxymethylation declined at 0.046 lnIU/day, both with a better explanation of the temporal profile. 3) This progression was concomitant with the occurrence of distinct nuclear codistribution patterns that represented a heterogeneous spectrum of states in differentiation; converging to three major coexisting 5mC/5hmC phenotypes by day 10: 5hmC{sup +}/5mC{sup −}, 5hmC{sup +}/5mC{sup +}, and 5hmC{sup −}/5mC{sup +} cells. 4) Using optical nanoscopy we could delineate the respective topologies of 5mC/5hmC colocalization in subregions of nuclear DNA: in the majority of 5hmC{sup +}/5mC{sup +} cells 5hmC and 5mC predominantly occupied mutually exclusive territories resembling euchromatic and heterochromatic regions, respectively. Simultaneously, in a smaller subset of cells we observed a tighter colocalization of the two cytosine variants, presumably delineating chromatin domains in remodeling. We conclude that 1) 5mC emerges as the most differential marker in our model system. 2) However, the combined enrollment of the two DNA modifications provided higher-definition screening and lead to the identification of cell subpopulations based on differential 5hmC/5mC phenotypes corresponding to different 5hmC/5mC ratios. The results encourage: a) assessing the regenerative potential of early-endodermal cells enriched for the three DNA methylation/hydroxymethylation categories, and b) exploring the universality of this type of epigenetic phenotyping across other lineage-specific differentiations. - Highlights: • First reported single-molecule super-resolution 3D-visualization of 5mC/5hmC sites in cells. • Identification of cells with differential 5mC/5hmC nuclear codistribution phenotypes. • Application of principle component and robust regression analyses for evaluation of 3D high-content-screening data. • Global 5mC constitutes a highly differential spatiotemporal in situ marker in early endodermal cell differentiation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

X-Ray photoelectron Spectroscopy Applications

With capability for obtaining quantitative elemental composition, chemical and electronic state, and overlayer thickness information from the top ~10 nm of a sample surface, X-ray Photoelectron Spectroscopy (XPS) or Electron Spectroscopy for Chemical Analysis (ESCA) is a versatile and widely used technique for analyzing surfaces. The technique is applied to a host of materials, from insulators to conductors in virtually every scientific field and sub-discipline. More recently, XPS has been extended under in-situ and operando conditions. Following a brief introduction to XPS principles and instrument components, this article exemplifies widely ranging XPS applications in material and life sciences.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2019

Scaling Input Distributions for Probabilistic Models - 19472

It is important to address scaling issues when building models to support risk-based decisions for radioactive waste disposal sites. Currently, probabilistic risk assessment and probabilistic performance assessment models are run for multiple realizations where each realization uses one value from each input distribution over the entire modeled time. The input distributions represent the current state of knowledge in the mean of the input variable over the spatial region of interest and over the time period of the model run. This paper focuses on the time factor in input distribution scaling because it presents more serious conceptual and distributional challenges than the spatial factor. One of the challenges in temporal scaling is the effect of non-linearity on propagation of distribution uncertainty through to uncertainty in results. Radioactive waste disposal models tend to have both linear and non-linear components in their models. Dose assessment calculations are typically represented by linear models, while contaminant transport models have linear and non-linear components. In principle, temporal scaling of input parameter distributions for a linear model is straightforward, but scaling of input distributions for non-linear models is not. This paper uses examples to investigate the effects of input distribution temporal scaling on simple linear and non-linear models. Different scaling scenarios were investigated by comparing three analysis tools: analytical mathematical representations, statistical software programming, and GoldSim Monte Carlo simulation software. R statistical software is an open source statistical programming language often used for statistical analyses and graphical representation of data. GoldSim is a robust probabilistic dynamic modeling platform used in performance assessment modeling of radioactive waste sites. A simple linear model, a quadratic model and a multiplicative model were the cases explored for each of these tools. For the three analysis tools considered and with each of the scaling cases, 1,000 realizations were implemented from distributions of the random variables of interest. This is a sufficient number of realizations for simple models to capture the model space. An annual temporal resolution of a 100-year simulation period was chosen for all models and analysis tools. The effects of temporal scaling were demonstrated by investigating two different options for time scaling. Option 1 was set up so that the input distributions represented the expected value on an annual time scale, and a new value from that distribution was chosen every year (at every time step which equaled a year) for 100 years. In Option 2, the input distributions were scaled to represent the expected mean value of the input variable over the 100 years of simulation, and one value from that distribution was chosen for the entire elapsed time. Results show agreement across the three analysis tools. As expected, the linear models have identical results for the two different scaling Options, and the non-linear models diverge in the results for different time scale implementation. The implications of this work point to the need for careful consideration of input distribution temporal scaling. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Progress and prospects of thermo-mechanical energy storage – A critical review

The share of electricity generated by intermittent renewable energy sources is increasing (now at 26% of global electricity generation) and the requirements of affordable, reliable and secure energy supply designate grid-scale storage as an imperative component of most energy transition pathways. The most widely deployed bulk energy storage solution is pumped-hydro energy storage (PHES), however, this technology is geographically constrained. Alternatively, flow batteries are location independent and have higher energy densities than PHES, but remain associated with high costs and low lifetimes, which highlights the importance of developing and utilizing additional larger-scale, longer-duration and long-lifetime energy storage alternatives. Here, we review a class of promising bulk energy storage technologies based on thermo-mechanical principles, which includes: compressed-air energy storage (CAES), liquid-air energy storage (LAES) and pumped-thermal electricity storage (PTES). The thermodynamic principles upon which these thermo-mechanical energy storage (TMES) technologies are based are discussed and a synopsis of recent progress in their development is presented, assessing their ability to provide reliable and cost-effective solutions. The current performance and future prospects of TMES systems are examined within a unified framework and a thermoeconomic analysis is conducted to explore their competitiveness relative to each other as well as when compared to PHES and flow battery systems. This includes carefully selected thermodynamic and economic methodologies for estimating the component costs of each configuration in order to provide a detailed and fair comparison at various system sizes. The analysis reveals that the technical and economic characteristics of TMES systems are such that, especially at higher discharge power ratings and longer discharge durations, they can offer promising performance (round-trip efficiencies higher than 60%) along with high lifetimes (> 30 years), low specific costs (often below 100 $/kWh), low ecological footprints and unique sector-coupling features compared to other storage options. TMES systems have significant potential for further progress and the thermoeconomic comparisons in this paper can be used as a benchmark for their future evolution.

25 ENERGY STORAGE↗
DOE OSTI2023

Integrative teaching of metabolic modeling and flux analysis with interactive python modules

Abstract The modeling of rates of biochemical reactions—fluxes—in metabolic networks is widely used for both basic biological research and biotechnological applications. A number of different modeling methods have been developed to estimate and predict fluxes, including kinetic and constraint‐based (Metabolic Flux Analysis and flux balance analysis) approaches. Although different resources exist for teaching these methods individually, to‐date no resources have been developed to teach these approaches in an integrative way that equips learners with an understanding of each modeling paradigm, how they relate to one another, and the information that can be gleaned from each. We have developed a series of modeling simulations in Python to teach kinetic modeling, metabolic control analysis, 13C‐metabolic flux analysis, and flux balance analysis. These simulations are presented in a series of interactive notebooks with guided lesson plans and associated lecture notes. Learners assimilate key principles using models of simple metabolic networks by running simulations, generating and using data, and making and validating predictions about the effects of modifying model parameters. We used these simulations as the hands‐on computer laboratory component of a four‐day metabolic modeling workshop and participant survey results showed improvements in learners' self‐assessed competence and confidence in understanding and applying metabolic modeling techniques after having attended the workshop. The resources provided can be incorporated in their entirety or individually into courses and workshops on bioengineering and metabolic modeling at the undergraduate, graduate, or postgraduate level.

Kaste, Joshua A. M.↗