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DOE OSTI2025

Smart culture medium optimization for recombinant protein production: Experimental, modeling, and AI/ML-driven strategies

Recombinant protein production (RPP) is central to biotechnology, where recombinant proteins are used as either end products or catalysts in the synthesis of chemicals, fuels, and materials. Among the major cost drivers, culture medium plays a pivotal role in determining protein yield and quality. This review presents a comprehensive perspective on the critical stages of “smart” culture medium optimization: planning, screening, modeling, optimization, and validation. In the planning stage, we examine the nutritional and energetic roles of medium components, including carbon, nitrogen, amino acids, salts, and trace metals, and their impacts on culture parameters such as pH, oxidative state, and osmolality. We highlight the variability in trace metal content due to water sources, culture vessels, and raw materials, which can substantially influence RPP. The screening stage covers Design of Experiments (DoE) approaches, assessing their theoretical basis, implementation, and limitations. For modeling, we describe methods that integrate experimental data to develop predictive models for smart medium formulation. Model-based optimization strategies can then be employed to select optimal media compositions for a given application. The validation stage aims to evaluate model predictions and provide feedback for model training and refinement. Finally, we survey mechanistic and artificial intelligence/machine learning (AI/ML)-driven models as integrated, transformational tools for predictive modeling of bioprocess conditions, nutrient availability, cellular metabolism, and protein quality, with the goal of optimizing culture media to enhance protein yields while reducing costs and environmental impact. We conclude by addressing the challenges of translating laboratory-scale medium optimization to industrial-scale settings and exploring future AI/ML-driven approaches that may overcome current bottlenecks and accelerate medium design for RPP. Overall, this review provides a unified framework for advancing smart medium design in RPP.

Artificial Intelligence/Machine Learning (AI/ML)↗

NASA NTRS1991

Efficient real gas upwinded Navier-Stokes computations of high speed flows

An efficient method to account for the chemically frozen thermodynamic and transport properties of air in three-dimensional Navier-Stokes calculations has been demonstrated. This approach uses an explicitly specified equation of state (EOS) so that the fluid pressure, temperature, and transport properties are directly related to the flow variables. The method is efficient since no subiterations are required to deduce the pressure and temperature from the flux variables and is modular by allowing different equations of state to be easily supplied to the code. The flexibility of the EOS approach is shown by its implementation into a high-order total variation diminishing upwinding scheme as well as a standard central-differencing scheme. The EOS approach is then demonstrated by computing the hypersonic flow through the corner region of two mutually perpendicular flat plates using both the upwind and central-differencing schemes.

Coirier, William J.↗

DOE OSTI2014

Integrating Variable Renewable Energy in Electric Power Markets: Best Practices from International Experience (Fact Sheet)

Many countries--reflecting very different geographies, markets, and power systems--are successfully managing high levels of variable renewable energy (RE) on the grid. Australia (South Australia), Denmark, Germany, Ireland, Spain, and the United States (Colorado and Texas), for example, have effectively integrated variable RE utilizing diverse approaches. Analysis of the results from these case studies reveals a wide range of mechanisms that can be used to accommodate high penetrations of variable RE (e.g., from new market designs to centralized planning). Nevertheless, the myriad approaches collectively suggest that governments can best enable variable RE grid integration by implementing best practices in five areas of intervention: lead public engagement, particularly for new transmission; coordinate and integrate planning; develop rules for market evolution that enable system flexibility; expand access to diverse resources and geographic footprint of operations; and improve system operations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2013

EMITTING ELECTRONS SPECTRA AND ACCELERATION PROCESSES IN THE JET OF Mrk 421: FROM THE LOW STATE TO THE GIANT FLARE STATE

We investigate the electron energy distributions (EEDs) and the acceleration processes in the jet of Mrk 421 through fitting the spectral energy distributions (SEDs) in different active states in the frame of a one-zone synchrotron self-Compton model. After assuming two possible EEDs formed in different acceleration models: the shock-accelerated power law with exponential cut-off (PLC) EED and the stochastic-turbulence-accelerated log-parabolic (LP) EED, we fit the observed SEDs of Mrk 421 in both low and giant flare states using the Markov Chain Monte Carlo method which constrains the model parameters in a more efficient way. The results from our calculations indicate that (1) the PLC and LP models give comparably good fits for the SED in the low state, but the variations of model parameters from low state to flaring can be reasonably explained only in the case of the PLC in the low state; and (2) the LP model gives better fits compared to the PLC model for the SED in the flare state, and the intra-day/night variability observed at GeV-TeV bands can be accommodated only in the LP model. The giant flare may be attributed to the stochastic turbulence re-acceleration of the shock-accelerated electrons in the low state. Therefore, we may conclude that shock acceleration is dominant in the low state, while stochastic turbulence acceleration is dominant in the flare state. Moreover, our result shows that the extrapolated TeV spectra from the best-fit SEDs from optical through GeV with the two EEDs are different. It should be considered with caution when such extrapolated TeV spectra are used to constrain extragalactic background light models.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

EOSPAC User's Manual: Version 6.5 Second Edition (Rev. 3)

The EOSPAC utility package is a collection of interface routines, which can be used to access the SESAME data library and perform various data adjustments and interpolations on the SESAME data. The SESAME data library contains both thermodynamic (e.g., equation of state) and transport coefficients (e.g., opacity and conductivity). Note, for simplicity, the term EOS (equation of state) used herein includes both thermodynamic variables and transport coefficients. The EOSPAC utility package is designed to be used by physics codes (henceforth ”host codes”) written in multiple languages and on multiple platforms. The remainder of this manual is organized into several sections. Chapter 2 discusses conventions such as data organization and routine names. Chapter 3 provides a general overview of basic theory and models implemented within EOSPAC. Chapter 4 provides a general overview of how to use the EOSPAC interface library. Chapters 5 to 7 describe the public interfaces of EOSPAC in detail. Chapter 8 provides a brief introduction to some related tools, which may be of use to the user. Chapter 9 provides details related to some selected numerical features of EOSPAC. Chapter 10 gives examples for using the interface routines described in chapters 5 to 7. Chapter 11 provides technical support contact information. Chapter 12 contains a brief set of acknowledgments. Chapter 13 contains a list of referenced documents. Finally, chapter 14 lists the “table types: mnemonic conventions”, “table types: grouped by category, sorted by name”, “table types: eospac version 5 cross reference”, “options: setup phase”, “data information parameters”, “meta-data information parameters”, “options: interpolation phase”, and the “error codes”.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2015

Deconstructed transverse mass variables

Traditional searches for R-parity conserving natural supersymmetry (SUSY) require large transverse mass and missing energy cuts to separate the signal from large backgrounds. SUSY models with compressed spectra inherently produce signal events with small amounts of missing energy that are hard to explore. We use this difficulty to motivate the construction of "deconstructed" transverse mass variables which are designed preserve information on both the norm and direction of the missing momentum. Here, we demonstrate the effectiveness of these variables in searches for the pair production of supersymmetric top-quark partners which subsequently decay into a final state with an isolated lepton, jets and missing energy. We show that the use of deconstructed transverse mass variables extends the accessible compressed spectra parameter space beyond the region probed by traditional methods. The parameter space can further be expanded to neutralino masses that are larger than the difference between the stop and top masses. In addition, we also discuss how these variables allow for novel searches of single stop production, in order to directly probe unconstrained stealth stops in the small stop-and neutralino-mass regime. We also demonstrate the utility of these variables for generic gluino and stop searches in all-hadronic final states. Overall, we demonstrate that deconstructed transverse variables are essential to any search wanting to maximize signal separation from the background when the signal has undetected particles in the final state.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2015

Solid-state transformation of Fe-rich intermetallic phases in Al–5.0Cu–0.6Mn squeeze cast alloy with variable Fe contents during solution heat treatment

The Al–5.0 wt.% Cu–0.6 wt.% Mn alloys with a variable Fe content were prepared by squeeze casting. Optical microscopy (OM), Deep etching technique, scanning electron microscopy(SEM), X-ray diffraction (XRD) and transmission electron microscopy (TEM) were used to examine the solid-state transformation of Fe-rich intermetallics during the solution heat treatment. The results showed that the Chinese script-like α-Fe, Al{sub 6}(FeMn) and needle-like Al{sub 3}(FeMn) phases transform to a new Cu-rich β-Fe (Al{sub 7}Cu{sub 2}(FeMn)) phase during solution heat treatment. The possible reaction and overall transformation kinetics of the solid-state phase transformation for the Fe-rich intermetallics were investigated. - Graphical abstract: Display Omitted - Highlights: • The α-Fe, Al{sub 6}(FeMn) and Al{sub 3}(FeMn) phases change to the β-Fe phases. • Possible reactions of Fe phases during solution heat treatment are discussed. • The overall fractional transformation rate follows an Avrami curve.

36 MATERIALS SCIENCE↗

NASA NTRS2003

Orbital-Phase-Resolved Study of OAO 1657-415 in Spin-Up and Spin-Down

We observed the 38-s X-ray pulsar OAO 1657-415 in a series of daily snapshots spanning its 10-day binary orbit, on three different occasions corresponding to different accretion torque states. The goal was to see if the previously observed drastic variability in X-ray spectral properties showed a systematic pattern with respect to orbital phase or torque state. Our study failed to identify any systematic patterns, although considerably stochastic variability was observed. Overall, our results were inconclusive. We chose not to prepare a journal paper on this study, although the data were shared with several other groups interested in monitoring the properties of this source.

Chakrabarty, Deepto↗

NASA NTRS1984

Flight test results for the Digital Integrated Automatic Landing Systems (DIALS): A modern control full-state feedback design

The Digital Integrated Automatic Landing System (DIALS) is discussed. The DIALS is a modern control theory design performing all the maneuver modes associated with current autoland systems: localizer capture and track, glideslope capture and track, decrab, and flare. The DIALS is an integrated full-state feedback system which was designed using direct-digital methods. The DIALS uses standard aircraft sensors and the digital Microwave Landing System (MLS) signals as measurements. It consists of separately designed longitudinal and lateral channels although some cross-coupling variables are fed between channels for improved state estimates and trajectory commands. The DIALS was implemented within the 16-bit fixed-point flight computers of the ATOPS research aircraft, a small twin jet commercial transport outfitted with a second research cockpit and a fly-by-wire system. The DIALS became the first modern control theory design to be successfully flight tested on a commercial-type aircraft. Flight tests were conducted in late 1981 using a wide coverage MLS on Runway 22 at Wallops Flight Center. All the modes were exercised including the capture and track of steep glidescopes up to 5 degrees.

Hueschen, R. M.↗

DOE OSTI2021

Behavioral patterns of bats at a wind turbine confirm seasonality of fatality risk

Abstract Bat fatalities at wind energy facilities in North America are predominantly comprised of migratory, tree‐dependent species, but it is unclear why these bats are at higher risk. Factors influencing bat susceptibility to wind turbines might be revealed by temporal patterns in their behaviors around these dynamic landscape structures. In northern temperate zones, fatalities occur mostly from July through October, but whether this reflects seasonally variable behaviors, passage of migrants, or some combination of factors remains unknown. In this study, we examined video imagery spanning one year in the state of Colorado in the United States, to characterize patterns of seasonal and nightly variability in bat behavior at a wind turbine. We detected bats on 177 of 306 nights representing approximately 3,800 hr of video and > 2,000 discrete bat events. We observed bats approaching the turbine throughout the night across all months during which bats were observed. Two distinct seasonal peaks of bat activity occurred in July and September, representing 30% and 42% increases in discrete bat events from the preceding months June and August, respectively. Bats exhibited behaviors around the turbine that increased in both diversity and duration in July and September. The peaks in bat events were reflected in chasing and turbine approach behaviors. Many of the bat events involved multiple approaches to the turbine, including when bats were displaced through the air by moving blades. The seasonal and nightly patterns we observed were consistent with the possibility that wind turbines invoke investigative behaviors in bats in late summer and autumn coincident with migration and that bats may return and fly close to wind turbines even after experiencing potentially disruptive stimuli like moving blades. Our results point to the need for a deeper understanding of the seasonality, drivers, and characteristics of bat movement across spatial scales.

17 WIND ENERGY↗

DOE OSTI2017

Seasonal southern hemisphere multi-variable reflection of the southern annular mode in atmosphere and ocean reanalyses

Variations of southern hemisphere (SH) climate variables are often linked to the southern annular mode (SAM) variability. We examined such linkage by seasons using state-of-the-art atmosphere and ocean/sea-ice reanalyses. The associated SAM related anomaly (SRA) fields of the climate variables, denoting anomalies corresponding to the same variation in SAM, are overall consistent across the reanalyses. Among the atmospheric products, 20CRV2 differs from ERA-interim and CFSR in the sea-level pressure SRAs over the Amundsen Sea, resulting in less warming over the Antarctic Peninsula. Among the ocean reanalyses, ORAP5 and C-GLORS exhibit the largest consistency. The major difference between them and the lower-resolution CFSR and SODA reanalyses is deeper penetration of anomalous meridional currents. Compared to the other ocean reanalyses, CFSR exhibits stronger and spatially more coherent surface-current SRAs, resulting in greater SRAs of sea-ice motion and ice thickness along the ice edges. The SRAs of sensible and total surface heat fluxes are reduced in CFSR due to ocean–atmosphere coupling. Significant sea-ice concentration SRAs are present on the west side of peninsulas along the east Antarctica coast in spring and winter, most notably in ORAP5 and C-GLORS, implying changes in new-ice production and shelf-water formation. Most atmosphere and ocean variables manifest an annular SRA pattern in summer and a non-annular pattern in the other seasons, with a wavenumber-3 structure strongest in autumn and weakest in summer. The wavenumber-3 structure should be related to the zonal wave three pattern of the SH circulation, the relation of which to SAM needs further exploration.

Meteorology & Atmospheric Sciences↗

DOE OSTI2022

Newton trust-region methods with primary variable switching for simulating high temperature multiphase porous media flow

Coupling multiphase flow with energy transport due to high temperature heat sources introduces significant new challenges since boiling and condensation processes can lead to dry-out conditions with subsequent re-wetting. The transition between two-phase and single-phase behavior can require changes to the primary dependent variables adding discontinuities as well as extending constitutive nonlinear relations to extreme physical conditions. Practical simulations of large-scale engineered domains lead to Jacobian systems with a very large number of unknowns that must be solved efficiently using iterative methods in parallel on high-performance computers. Performance assessment of potential nuclear repositories, carbon sequestration sites and geothermal reservoirs can require numerous Monte-Carlo simulations to explore uncertainty in material properties, boundary conditions, and failure scenarios. Due to the numerical challenges, standard NR iteration may not converge over the range of required simulations and require more sophisticated optimization method like trust-region. In this study, we use the open-source simulator PFLOTRAN for the important practical problem of the safety assessment of future nuclear waste repositories in the U.S. DOE geologic disposal safety assessment Framework. The simulator applies the PETSc parallel framework and a backward Euler, finite volume discretization. We demonstrate failure of the conventional NR method and the success of trust-region modifications to Newton’s method for a series of test problems of increasing complexity. Trust-region methods essentially modify the Newton step size and direction under some circumstances where the standard NR iteration can cause the solution to diverge or oscillate. Furthermore, we show how the Newton Trust-Region method can be adapted for Primary Variable Switching (PVS) when the multiphase state changes due to boiling or condensation. The simulations with high-temperature heat sources which led to extreme nonlinear processes with many state changes in the domain did not converge with NR, but they do complete successfully with the trust-region methods modified for PVS. This implementation effectively decreased weeks of simulation time needing manual adjustments to complete a simulation down to a day. Finally, we show the strong scalability of the methods on a single node and multiple nodes in an HPC cluster.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Growth modeling to evaluate alternative cultivation strategies to enhance national microalgal biomass production

In this paper, we present a model-based assessment of alternative cultivation strategies on algal biomass production within the conterminous United States. Our assessment focuses on two basic cultivation strategies: 1) seasonal rotation of three representative freshwater algal strains that are well suited for warm weather, cold weather, and all-season diverse weather conditions, respectively; and 2) variation between three open pond water depths (15cm, 20cm, and 25cm). The enhanced Biomass Assessment Tool (BAT) is applied on a site-specific, hourly basis at 5,832 North American Land Data Assimilation System Phase 2 1/8° meteorological model grid cells over a 30-year period (1980-2009) to evaluate the operational strategies. Recognizing that resource management decisions may also consider scales beyond the individual site, we also conduct a regional assessment of focused on 7 representative climate zones in the conterminous United States. Results demonstrate that the spatial variability of algal productivity is largely affected by the strain-specific growth response to light and temperature that vary significantly by climate zone and latitude. Therefore, with a limited set of alternative cultivation strategies, the BAT identified the best performing combination of cultivation strategies on a site-specific basis that considerably enhances national annual biomass productivity. Specifically, the appropriate choice of seasonal strain rotation is able to significantly dampen climate-driven seasonal and spatial variability.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2016

A solution of the monoenergetic neutral particle transport equation for adjacent half-spaces with anisotropic scattering

We present highly accurate solutions to the neutral particle transport equation in a half-space. While our initial motivation was in response to a recently published solution based on Chandrasekhar's H-function, the presentation to follow has taken on a more comprehensive tone. The solution by H-functions certainly did achieved high accuracy but was limited to isotropic scattering and emission from spatially uniform and linear sources. Moreover, the overly complicated nature of the H-function approach strongly suggests that its extension to anisotropic scattering and general sources is not at all practical. For this reason, an all encompassing theory for the determination of highly precise benchmarks, including anisotropic scattering for a variety of spatial source distributions, is presented for particle transport in a half-space. We illustrate the approach via a collection of cases including tables of 7-place flux benchmarks to guide transport methods developers. The solution presented can be applied to a considerable number of one and two half-space transport problems with variable sources and represents a state-of-the-art benchmark solution.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2018

Unusual magnetodielectric effects in La2CuMnO6 induced by a dynamic crossover in dielectric relaxation at TC

Highlights: • Ferromagnetic short-range correlations above T{sub C} = 72 K and a sign reversal of magnetoresistance around T{sub C}. • Dielectric relaxation in La{sub 2}CuMnO{sub 6}, with a dynamic (Arrhenius to Arrhenius) crossover at T{sub C}. • An unusual trend in the magnetodielectric coupling around T{sub C}. • A large magnetodielectric coupling of 55% at 68 K for 4 kHz and 61% at 105 K for 285.8 kHz under a magnetic field of 5 kOe. • Both the magnetic ordering and the external magnetic field control the electric dipole relaxation in the material. - Abstract: A series of fixed frequency dielectric measurements shows dielectric relaxation in La{sub 2}CuMnO{sub 6}, with a dynamic (Arrhenius to Arrhenius) crossover at T{sub C}. The external magnetic field alters the relaxation parameters in the vicinity of crossover and induces an unusual trend in the magnetodielectric coupling around T{sub C}. A large magnetodielectric coupling of 55% (at 68 K, 4 kHz) and 61% (at 105 K, 285.8 kHz) under a small magnetic field of 5 kOe is discovered. Presence of ferromagnetic short-range correlations above T{sub C} and a sign reversal of magnetoresistance around T{sub C} are observed. Specific heat analysis revealed the presence of ferromagnetic, variable range hopping active charge localized state. The presence of ferromagnetic short-range correlations and the influence of a core-grain dominated magnetoresistance on the Maxwell-Wagner interfacial polarization are responsible for the observed large magnetodielectric effect. Both the magnetic ordering and external magnetic field control the electric dipole relaxation in the material.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2022

Automated and efficient local adaptive regression for principal component-based reduced-order modeling of turbulent reacting flows

Principal Component Analysis can be used to reduce the cost of Computational Fluid Dynamics simulations of turbulent reacting flows by reducing the dimensionality of the transported variables through projection of the thermochemical state onto a lower-dimensional manifold. However, because of the nonlinearity of the principal component source terms, nonlinear regression techniques must be utilized for the source terms in terms of the principal components. Unfortunately, widely available and utilized nonlinear regression techniques can have prohibitive computational requirements and/or accuracy that is highly dependent on user experience in ad hoc tuning of model architecture and hyperparameters. Here, in this work, a new nonlinear regression approach is proposed that is both computationally efficient and automated so does not require any user input. The approach is evaluated through a priori prediction of principal component source terms using data from a Direct Numerical Simulation of a turbulent nonpremixed n-heptane/air jet flame. In particular, the proposed framework consists of local regressions whose complexity is adapted according to the local nonlinearity of the data: local linear regression when accurate enough and local Artificial Neural Networks when nonlinear regression is required. The number of local clusters for local regression is determined automatically using the Davies-Bouldin index. In addition, Bayesian optimization is utilized for model training (i.e., to select the best architectures and hyperparameters of the nonlinear regressions in an unsupervised fashion), eliminating ad hoc hand-tuning and/or expensive grid searches. Overall, compared to a single, global neural network, the new local adaptive regression approach is shown to have comparable accuracy but 69% less training time due to the utilization of local linear regression and faster training of local neural networks.

42 ENGINEERING↗

DOE OSTI2021

Climate and atmospheric deposition drive the inter-annual variability and long-term trend of dissolved organic carbon flux in the conterminous United States

The lateral flux of dissolved organic carbon (DOC) from soils to inland waters and ultimately to the ocean represents a fundamental component of the global carbon cycle. To estimate the DOC flux, we developed an empirical terrestrial-aquatic DOC fluxes model (TAF-DOC). TAF-DOC incorporates various environmental factors (e.g., meteorology, sulfur, and nitrogen deposition) that to-date have not been comprehensively considered or well-represented in existing modeling frameworks. TAF-DOC was applied to estimate spatial-temporal patterns of DOC flux and potential fates across the conterminous United States during the 1985 to 2018 time period. Our results suggest that TAF-DOC successfully characterized spatial-temporal of DOC flux. As expected, the interannual pattern of DOC flux was strongly regulated by precipitation, but the long-term trend was significantly influenced by the rate of atmospheric wet sulfur deposition. From 1985 to 2018, TAF-DOC estimated DOC loading from terrestrial to aquatic ecosystems in the conterminous United States to be 33.5 ± 2.2 TgC per year, which was roughly 0.39–0.49% of total soil organic carbon stock estimates. The dominant fate of terrestrially-derived DOC was delivery to the coastal ocean in riverine export (41%), with another 21% buried in sediment and the remaining 12.8 ± 0.4 TgC per year (38%) returned to the atmosphere through outgassing from inland waters. Finally, assuming the quantities of DOC sediment burial and export to the ocean as an annual sink of terrestrially-derived carbon, budget inventories and models that do not account for DOC flux in the conterminous United States will underestimate the net annual carbon sink by as much as 5.5–6.4%.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Adsorbate Partition Functions via Phase Space Integration: Quantifying the Effect of Translational Anharmonicity on Thermodynamic Properties

A new method for computing anharmonic thermophysical properties for adsorbates on metal surfaces is presented. Classical Monte Carlo phase space integration is performed to calculate the partition function for the motion of a hydrogen atom on Cu(111). Here, a minima-preserving neural network potential energy surface is used within the integration routine. Two different sampling schema for generating the training data are presented, and two different density functionals are used. The results are benchmarked against direct state counting results by using discrete variable representation. The phase space integration results are in excellent quantitative agreement with the benchmark results. Additionally, both the discrete variable representation and the phase space integration results confirm that the motion of H on Cu(111) is highly anharmonic. The results were applied to calculate the free energy of dissociative adsorption of H 2 and the resulting Langmuir isotherms at 400, 800, and 1200 K in a partial pressure range of 0–1 bar. It shows that the anharmonic effects lead to significantly higher predicted surface site fractions of hydrogen.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗