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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Cell-Free Systems Biology: Characterizing Central Metabolism of Clostridium thermocellum with a Three-Enzyme Cascade Reaction

Genetic approaches have been traditionally used to understand microbial metabolism, but this process can be slow in nonmodel organisms due to limited genetic tools. An alternative approach is to study metabolism directly in the cell lysate. This avoids the need for genetic tools and is routinely used to study individual enzymatic reactions but is not generally used to study systems-level properties of metabolism. Here we demonstrate a new approach that we call “cell-free systems biology”, where we use well-characterized enzymes and multienzyme cascades to serve as sources or sinks of intermediate metabolites. This allows us to isolate subnetworks within metabolism and study their systems-level properties. To demonstrate this, we worked with a threeenzyme cascade reaction that converts pyruvate to 2,3-butanediol. Although it has been previously used in cell-free systems, its pH dependence was not well characterized, limiting its utility as a sink for pyruvate. We showed that improved proton accounting allowed better prediction of pH changes and that active pH control allowed 2,3-butanediol titers of up to 2.1 M (189 g/L) from acetoin and 1.6 M (144 g/L) from pyruvate. The improved proton accounting provided a crucial insight that preventing the escape of CO 2 from the system largely eliminated the need for active pH control, dramatically simplifying our experimental setup. We then used this cascade reaction to understand limits to product formation in Clostridium thermocellum, an organism with potential applications for cellulosic biofuel production. We showed that the fate of pyruvate is largely controlled by electron availability and that reactions upstream of pyruvate limit overall product formation.

09 BIOMASS FUELS↗
DOE OSTI2023

Laboratory-Scale Coal-Derived Graphene Process (Final Report)

The Energy & Environmental Research Center (EERC) conducted a laboratory-scale coal-derived graphene (CDG) project focused on developing a technological process for making graphene from four U.S. domestic coal or coal wastes, including lignite from North Dakota, subbituminous coal from Wyoming, bituminous coal from Utah, and anthracite from Pennsylvania. The project was divided into two performance or budget periods (BPs), with BP1 comprising the up-front laboratory experiments to make graphene materials from coal beginning on May 1, 2020, to April 30, 2022. BP2 was conducted from May 1, 2022, to April 30, 2023, and was focused on analyzing the CDG process economic feasibility and the technical gaps for technological scale-up and commercialization. During this project, a few different coal-derived high-value products have been demonstrated, including graphite, graphene oxide (GO), reduced graphene oxide (rGO), and graphene quantum dots (GQDs). A new graphite microstructure was discovered and named “croissant graphite” because of the exterior morphological and textural resemblance to croissant food items sold in commercial groceries stores. The new graphite structure and the associated preparation from coal or coal waste feedstocks has been the subject of a U.S. patent application. The systematic experimental processes involving coal cleaning, upgrading, and conversion to high-value carbon products culminated into a developed upgraded coal-to-products (UCP) technology that is being pursued for potential fast-track commercialization, if funding is available. It is envisioned that commercialization of the UCP technology would increase consumption of U.S. domestic coals or coal wastes to make environmentally sustainable high-value products for the electronics industry, high-energy-storage applications, and clean energy technologies such as electric vehicle (EV) lithium-ion batteries (LIBs), for which graphite has become a critical mineral commodity. Croissant graphite microstructures, when observed by field emission scanning electron microscopy (FESEM), display wavy surface morphology and often grow from a base that is made of graphitized particles with honeycomb-like layers, which are believed to be graphene layers. While more studies are needed to fully ascertain the mechanisms of the croissant graphite microstructure formation, it is postulated that their growth may begin from curling of the graphene sheets into ribbon-like structures, and continuous growth and densification of the ribbon-like structures forms croissant microstructures. Additional studies are ongoing to evaluate the electrochemical performance of croissant graphite for LIB applications and to determine the experimental conditions necessary to tune on/off croissant formation so that it can be either optimized or suppressed depending on performance evaluation results. In addition to the discovery of croissant graphite, the graphitization process from the four coal ranks in general was successful. X-ray diffraction (XRD) analysis showed that the degree of graphitization (DoG) ranged from 12% to 80% in an early sample set, and further optimization on lignite coal produces a DoG of about 92%, which was spectacular to see as lignite is the lowest-rank coal. Thus, it is expected that the graphitization performance for higher-rank coals will be similar or better when optimized as well. The coal-derived graphite was used to make GO and rGO. Analytical characterization, e.g., by methods such as Raman spectroscopy, XRD, Fourier transform infrared (FTIR) spectroscopy and FESEM, showed that the sequence of converting the coal to graphite, exfoliating it to GO, and then chemically reducing the GO to rGO was successful. Although coal naturally contains aromatic compounds and some relatively small-sized condensed aromatic units, it does not contain graphene sheets. In the UCP process, the aromatic domains in the coals, particularly low-rank coals, are concentrated and condensed further into graphene sheets, which are ordered into a 3D stack during graphitization. The synthesized graphite is then unpacked by methods such as exfoliation to various graphene products. GQDs were synthesized from all four coal types, and their optical properties were demonstrated to be tunable by the coal precursor preprocessing treatments. In all four coal types, enhanced optical properties were observed for the produced GDQs with incremental improvements made to the coal precursors. GQDs produced from raw coal samples displayed lower ultraviolet–visible (UV–Vis) spectroscopy absorbance intensity compared to those obtained from cleaned and upgraded coal residues. The photoluminescence (PL) intensities also varied with pretreatment conditions and with the concentration of GQDs in aqueous solutions. GQDs obtained from anthracite show longer emission wavelengths and can be excited by visible light as opposed to GQDs derived from the other coal ranks. UV fluorescence 3D maps and spectra revealed that the emission wavelength at which the GQDs solutions display the highest intensity was slightly redshifted based on the coal precursor pretreatments. In low-rank coal (lignite and subbituminous) samples, two clusters were observed in the maps for GQDs, which may suggest that there are potentially two types of fluorophores in solution or two main size populations. The ability to tune the properties of GQDs based on processing methods can be exploited to make GQDs for various optical display or optoelectronics applications. The results also highlight the importance of removing coal-borne impurities to improve the quality of the coal precursor for preparation of graphene products. Coal and/or coal wastes preprocessing methods were developed and applied to clean and upgrade the coal precursors prior to graphitization and subsequent conversion to graphene products. The preprocessing methods involve high specific-gravity separations, mineral acid cleaning (no hydrofluoric acid), and subsequent upgrading by reducing the coal-borne heteroatom (nitrogen, sulfur, and oxygen) content using proprietary chemical agents. Analytical characterization revealed that the preprocessing steps were successful, with ash reductions that range from 38% to 80% and residual ash content that was below the 5 wt% initial target. Based on proximate and ultimate analysis, the heteroatom reduction reactions produced upgraded coal residues with the oxygen content reduced by 8% to 24%, with additional reductions in the nitrogen and sulfur contents. An initial assessment of the waste streams from the UCP process shows very small to negligible environmental impact due to CO 2 , NO x , and SO x because most process steps are performed under inert atmosphere with argon. Consequently, reactive oxygen environments that tend to create these species are avoided. The inorganic and potentially hazardous species are released into aqueous waste streams that are easy to handle for proper disposal. The liquid waste streams were found to contain low-level concentrations of rare-earth elements (REEs), which could be concentrated and recovered as value-added by-products. Additionally, the volatile and gaseous fractions from carbonization and heat treatment contain useful organic compounds that can also be recovered as potential valuable by-products. Thus, the UCP technology is considered an environmentally sustainable and promising emerging technology for making high-value products from coal and coal wastes, with potential additional value-added by-products. Analysis of potential markets for the coal-derived carbon products shows a strong demand in both niche market sectors and across a wide variety of other industrial sectors. Graphite is currently considered a critical mineral commodity that has a large and growing demand in the LIB industry for EV applications. Based on data from Fortune Business Insights (2022) and Marketwatch (2023) reports, the average global graphite market is projected to reach about 33 billion by 2028, growing at a compound annual growth rate (CAGR) of about 7%, with much of this growth expected to be in the LIB industry. GO and rGO have strong market potentials in various application areas, such as coatings for anticorrosion, anti-icing, and antimicrobial protection, thermal barriers, wear resistance, sensors, additive manufacturing such as 3D inks, and others. GQDs are the emerging key player in the bioimaging, photovoltaics, and light-emitting diodes (LEDs) applications, with the potential to replace traditional semiconductor quantum dots (SQDs), which are based on metallic systems that are more toxic and more expensive. Biomedical applications of GQDs are becoming more attractive because of low to no toxicity and extremely low cost compared to SQDs. The major challenges for scale-up and commercialization of coal-derived carbon products such as graphene vary from the inherent attributes of graphene itself to reluctance to accept graphene in new manufacturing processes because of the uncertainty of the unknown. The 2D nature of graphene materials with a thickness of one atom presents significant challenges to proper handling/processing, and process scale-up becomes difficult because it requires high-end, expensive equipment, even for routine handling and analysis for quality assurance and control. Pristine graphene can also be extremely difficult to work into other matrices, thus hindering downstream processibility, especially at large scale. Currently, the cost of graphene and graphene products is still high and presents an economic risk that tends to slow down investment in scaling up emerging technologies. The lack of a standard for graphene materials for quality assurance and quality control poses a great challenge not only for the markets but also for commercialization efforts. A first-look economic feasibility analysis of the UCP technology provided valuable information that suggests the UCP process would be feasible, especially when it is scaled to a pilot scale and could be more competitive at the full scale. Graphitization was found to be the most energy-consuming and most capital-intensive step in the overall process. In small laboratory- and bench-scale experiments, labor is a significant contributor to the total process costs. Although these energy, capital, and labor constraints contribute to a higher selling price for the product, a preliminary economic model suggests that the process would be feasible at large scale when the process is fully integrated, optimized, and automated.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2021

Optical and Magneto-Optical Properties of Donor-Bound Excitons in Vacancy-Engineered Colloidal Nanocrystals

Controlled insertion of electronic states within the band gap of semiconductor nanocrystals (NCs) is a powerful tool for tuning their physical properties. One compelling example is II–VI NCs incorporating heterovalent coinage metals in which hole capture produces acceptor-bound excitons. To date, the opposite donor-bound exciton scheme has not been realized because of the unavailability of suitable donor dopants. Here, we produce a model system for donor-bound excitons in CdSeS NCs engineered with sulfur vacancies (V S ) that introduce a donor state below the conduction band (CB), resulting in long-lived intragap luminescence. V S -localized electrons are almost unaffected by trapping, and suppression of thermal quenching boosts the emission efficiency to 85%. Magneto-optical measurements indicate that the V S are not magnetically coupled to the NC bands and that the polarization properties are determined by the spin of the valence-band photohole, whose spin flip is massively slowed down due to suppressed exchange interaction with the donor-localized electron.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2024

Machine learning without a processor: Emergent learning in a nonlinear analog network

Standard deep learning algorithms require differentiating large nonlinear networks, a process that is slow and power-hungry. Electronic contrastive local learning networks (CLLNs) offer potentially fast, efficient, and fault-tolerant hardware for analog machine learning, but existing implementations are linear, severely limiting their capabilities. These systems differ significantly from artificial neural networks as well as the brain, so the feasibility and utility of incorporating nonlinear elements have not been explored. Here, we introduce a nonlinear CLLN—an analog electronic network made of self-adjusting nonlinear resistive elements based on transistors. We demonstrate that the system learns tasks unachievable in linear systems, including XOR (exclusive or) and nonlinear regression, without a computer. We find our decentralized system reduces modes of training error in order (mean, slope, curvature), similar to spectral bias in artificial neural networks. The circuitry is robust to damage, retrainable in seconds, and performs learned tasks in microseconds while dissipating only picojoules of energy across each transistor. This suggests enormous potential for fast, low-power computing in edge systems like sensors, robotic controllers, and medical devices, as well as manufacturability at scale for performing and studying emergent learning.

Science & Technology - Other Topics↗
DOE OSTI2025

The influence of cooling rates on strain phase diagrams and domain structures of ferroelectric thin films: A case study of PbTiO 3

Strain engineering has been established as an effective approach to control phase equilibria, domain configurations, and functional properties of ferroelectric thin films. Temperature-strain phase diagrams have been used as powerful tools for providing insights into strain engineering. However, almost all existing phase diagrams established using the phase-field approach assume quenching conditions without considering actual cooling rates during the post-deposition annealing process of ferroelectric thin films. Within this work, we systematically investigate the influence of cooling rates on domain structures and the strain-phase diagram of ferroelectric thin films using phase-field simulations, taking PbTiO 3 thin films as a model system. We found that both the position of phase boundaries in the strain phase diagrams and the domain morphology are significantly influenced by the cooling rates. It is revealed that while the paraelectric-ferroelectric phase boundary remains invariant, the phase boundaries between single-phase and multi-phase regions tend to shift toward the corresponding multi-phase region as the cool rate reduces. Slow cooling generally leads to more ordered domain structures with increased domain size. Using the obtained equilibrium domain structures, we calculated effective thermal conductivities and found significant variations that can be tuned by the cooling rates. In conclusion, this work reveals an underexplored yet critical impact of cooling rates on phase equilibria and domain structures in ferroelectric thin films, which may inspire further fine-tuning of domains and domain walls in low-dimensional ferroelectrics for multifunctional applications.

Domain structures↗
DOE OSTI2026

Rational engineering to enhance C8-fatty acid biosynthesis in Picosynechococcus sp. PCC 7002

Medium-chain fatty acids (e.g., C8-C14) are important biofuel precursors that can be produced from CO2 by cyanobacteria and other photoautotrophs. However, cyanobacteria naturally direct a relatively small fraction of fixed carbon to lipid synthesis, primarily producing long-chain membrane-bound fatty acids. We investigated whether mitigating kinetic bottlenecks within the fatty acid biosynthesis (FAB) pathway could enhance flux to free fatty acid (FFA) production in Picosynechococcus sp. PCC 7002. Previous in vitro studies proposed that the FAB initiating enzyme FabH is the primary rate-controlling enzyme in PCC 7002. We hypothesized that enhancing fatty acid initiation could increase in vivo FFA production while shifting the kinetic bottleneck further downstream in the pathway. We enabled C8-FFA accumulation by knocking out the native acyl-acyl carrier protein synthetase gene (aas) and expressing the highly active Cuphea palustris-derived mutant thioesterase CpFatB1.2-M4-287 (CupTE), which selectively catalyzes C8 chain termination. We then expressed the diatom-derived Chaetoceros sp. GSL56 FabH ortholog (chKASIII), to enhance initiation, and a medium-chain selective E. coli ketosynthase ecFabF[I108F] (ecFabF∗), to enhance elongation. When expressed individually or in combination with ecFabF∗, chKASIII slowed growth and decreased net carbon fixation rates relative to the parental Δaas-CupTE strain. However, co-expression of chKASIII, ecFabF∗, and CupTE redirected a larger fraction of fixed carbon toward FFA production, increasing relative carbon flux to C8-FFA and decreasing the projected minimum selling price by four-fold. This work demonstrates how systems metabolic engineering can be applied to enhance C8-FFA production in cyanobacteria while highlighting the unpredictable physiological consequences of host metabolic burden.

09 BIOMASS FUELS↗
DOE OSTI2025

Stormwater Storage and Retention Within an Urban Prairie Wetland Complex

Climate change is expected to increase the frequency and severity of flooding in the Great Lakes region. In many cities, flood-control infrastructure is insufficient to protect against future climate conditions. Consequently, there is increasing focus on stormwater storage provided by urban greenspace, such as wetlands and prairies, but the ecohydrological behavior of these ecosystems is not well understood when they are embedded within cities. To improve understanding of hydrological connectivity between urban areas and natural greenspaces, we deployed a sensor network in Gensburg Markham Prairie (GMP), a large intact prairie-wetland complex in south suburban Chicago. We used the resulting high-frequency time-series data to assess surface-subsurface hydrologic dynamics between upland and low-lying wetland areas, interactions between the prairie and surrounding environment, and stormwater storage provided by the prairie. Rapid infiltration within the prairie during and after storm events provides subsurface flow that stores considerable water, flattens storm hydrographs, and increases the wetland hydroperiod. Much of the stormwater input to GMP derives from the surrounding cityscape. Consequently, storage within the prairie-wetland system reduces and slows stormwater discharge to downstream urban communities. For a typical 5-year 24-hr storm with 10.9 cm of rain, GMP stores 77,100 m 3 , 64% greater than the estimated direct rainfall volume onto the prairie, yielding 30,000 m 3 of offsite stormwater storage. This improved understanding of ecohydrological dynamics in urban prairies and wetlands informs the design and implementation of green infrastructure to meet growing needs for stormwater management.

Rivera, Vivien Anne [Northwestern University, Evan↗
DOE OSTI2020

Investigation of mode activity in NBI-heated experiments of Wendelstein 7-X

The 2018 operation phase (OP 1.2b) of the stellarator Wendelstein 7-X (W7-X) included, for the first time, neutral beam injection (NBI) to heat the plasma. Since the injection geometry at W7-X is not parallel, this generates both passing and trapped fast particles. During longer phases of NBI injection, with the primary purpose to study the heating efficiency of this system, Alfvén eigenmodes (AEs) were observed by a number of diagnostics, including the phase contrast imaging (PCI) system, the magnetic pick-up coils (Mirnov coils), and the soft x-ray multi-camera tomography system (XMCTS). Alfvén eigenmodes are of great interest for future fusion reactors as it has been shown that the resonant interaction of fast ions with self-excited AEs can lead to enhanced transport of fast ions and potentially to energy losses. This is especially true for so-called gap-modes, Alfvén eigenmodes with frequencies in gaps of the continuous spectrum, since they lack continuum damping. These modes are commonly known to be excited by fast ions, but other destabilizing mechanisms, e.g. the electron-pressure gradient are also possible. In this article we present a first analysis of the experimentally observed frequencies from the theoretical side. The calculation of shear Alfvén wave continua for selected cases and the assignment of observed frequencies to the gaps of the continuous spectra are presented. Using the ideal-MHD code CKA (Könies A. 2007 10th IAEA TM on Energetic Particles in Magnetic Confinement System), we find gap modes that match the experimental measurements in terms of the observed frequencies. We emphasize the crucial roles played by the coupling of sound and Alfvén waves as well as of the Doppler shift arising as a consequence of the radial electric field in W7-X. We employ the perturbative gyrokinetic code CKA-EUTERPE (Feh´er 2013 Simulation of the interaction between Alfv´en waves and fast particles), using a slowing-down distribution function for the fast ions as calculated by the Monte-Carlo particle following code ASCOT (Hirvijoki et al 2014 Comput. Phys. Commun. 185 1310–21) to assess the fast-ion drive. Here we find that the fast-ion drive is insufficient to overcome the background-plasma damping. The fact that unstable modes were observed experimentally may point to problems with the modelling or indicate the existence of other destabilizing mechanisms, e.g. associated with the electron-pressure gradient (Windisch et al 2017 Plasma Phys. Control. Fusion 59 105002) that sensitively depend on the profiles of the background plasma.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Direct Measurement of the Selective Microwave-Induced Heating of Agglomerates of Dipolar Molecules: The Origin of and Parameters Controlling a Microwave Specific Superheating Effect

Agglomerates of polar molecules in nonpolar solvents are selectively heated by microwave radiation. The magnitude of the selective heating was directly measured by using the temperature dependence of the intensities of the Stokes and anti-Stokes bands in the Raman spectra of p-nitroanisole (pNA) and mesitylene. Under dynamic heating conditions, a large apparent temperature difference (ΔT) of over 100 °C was observed between the polar pNA solute and the nonpolar mesitylene solvent. This represents the first direct measurement of the selective microwave heating process. The magnitude of the selective microwave heating was affected by the properties of the agglomerated pNA. As the concentration of the pNA increases, the magnitude of the selective heating of the pNA was observed to decrease. This is explained by the tendency of the pNA dipoles to orient in an antiparallel fashion in the aggregates as measured by the Kirkwood g value, which decreased with increasing concentration. This effect reduces the net dipole moment of the agglomerates, which decreases the microwave absorption. After the radiation was terminated, the effective temperature of the dipolar molecules returned slowly to that of the medium. The slow heat transfer was modeled successfully by treating the solutions as a biphasic solvent/solute system. Based on modeling and the fact that the agglomerate can be heated above the boiling temperature of the solvent, an insulating layer of solvent vapor is suggested to form around the heated agglomerate, slowing convective heat transfer out of the agglomerate. Furthermore, this is an effect unique to microwave heating.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

IDAES-PSE 2.6.0 Release

The Institute for the Design of Advanced Energy Systems (IDAES) Integrated Platform is a versatile computational environment offering extensive process systems engineering (PSE) capabilities for optimizing the design and operation of complex, interacting technologies and systems. IDAES enables users to efficiently search vast, complex design spaces to discover the lowest cost solutions while supporting the full process modeling lifecycle, from conceptual design to dynamic optimization and control. The extensible, open platform empowers users to create models of novel processes and rapidly develop custom analyses, workflows, and end-user applications. IDAES-PSE 2.6.0 Release Highlights Upcoming Changes IDAES will be switching to the new Pyomo solver interface in the next release. Whilst this will hopefully be a smooth transition for most users, there are a few important changes to be aware of. The new solver interface uses a different version of the IPOPT writer (“ipopt_v2”) and thus any custom configuration options you might have set for IPOPT will not carry over and will need to be reset. By default, the new Pyomo linear presolver will be activated with ipopt_v2. Whilst are working to identify any bugs in the presolver, it is possible that some edge cases will remain. IDAES will begin deploying a new set of scaling tools and APIs over the next few releases that make use of the new solver writers. The old scaling tools and APIs will remain for backward compatibility but will begin to be deprecated. New Models, Tools and Features New Intersphinx extension automatically linking Jupyter notebook examples to project documentation New end-to-end diagnostics example demonstrated on a real problem New complementarity formulation for VLE with cubic equations of state, backward compatibility for old formulation New solver interface with presolve (ipopt_v2) in support of upcoming changes to the initialization and APIs methods, with default set to ipopt to maintain backwards compatibility; this will deprecate once all examples have been updated New forecaster and parameterized bidder methods within grid integration library Updated surrogates API and examples to support Keras 3, with backwards compatibility for older formats such as TensorFlow SavedModel (TFSM) Updated costing base dictionary to include the 2023 cost year index value Updated ProcessBlock to include information on the constructing block class Updated Flowsheet Visualizer to allow visualize() method to return value and functions Bug Fixes Fixed bug in the Modular Property Framework that would cause errors when trying to use phase-based material balances with phase equilibria. Fixed bug in Modular Properties Framework that caused errors when initializing models with non-vapor-liquid phase equilibria. Fixed typos flagged by June update to crate-ci/typos and removed DMF-related exceptions Minor corrections of units of measurement handling in power plant waste/transport costing expressions, control volume material holdup expressions, and BTX property package parameters Fixed throwing >7500 numpy deprecation warnings by replacing scalar value assignment with element extraction and item iteration calls Testing and Robustness Migrated slow tests (>10s) to integration, impacting test coverage but also yielding a nearly 30% decrease in local test runtime Pinned pint to avoid issues with older supported Python versions Pinned codecov versions to avoid tokenless upload behavior with latest version Bumped extensions to version 3.4.2 to allow pointing to non-standard install location Deprecations and Removals Python 3.8 is no longer supported. The supported Python versions are 3.9 through 3.12 The Data Management Framework (DMF) is no longer supported. Importing idaes.core.dmf will cause a deprecation warning to be displayed until the next release The SOFC Keras surrogates have been removed. The current version of the SOFC surrogate model in the examples repository is a PySMO Kriging model.

AS↗
DOE OSTI2025

Evaluating inkjet dispenser/liquid vortex capture-mass spectrometry for single-cell metabolomics in Hep G2 steatosis caused by tamoxifen

Single-cell mass spectrometry (MS) is advancing our understanding of metabolic pathways in heterogeneous cell populations; however, many techniques are slow or require disruptive sample preparations. This study evaluated coupling a modified HP D100 single-cell inkjet dispenser with liquid vortex capture-mass spectrometry (D100/LVC-MS). The D100 is a single-cell inkjet dispenser capable of titrating solutions and isolating single cells via disposable cassettes equipped with microfluidic channels and an impedance sensor. The LVC-MS enables high-throughput capture, lysis, and ionization of analytes for mass spectrometric analysis. The D100/LVC-MS system was characterized through titration and single-cell experiments. Propranolol titration demonstrated linearity across a broad concentration range using the D100/LVC-MS system. Additionally, Hep G2 hepatocarcinoma cells and Chlamydomonas reinhardtii algae were used to showcase the D100’s high-throughput or low-buffer-volume single-cell dispensing strategies. The D100/LVC-MS system’s performance was validated by evaluating tamoxifen-induced steatosis in Hep G2 cells. Tamoxifen, associated with nonalcoholic fatty liver disease in breast cancer patients following long-term use, was tested in Hep G2 cells at 20 µM for 72 h against DMSO-treated controls. High-throughput analysis of 500 cells per condition, completed in 25 min per run, demonstrated the system’s efficiency. The D100/LVC-MS system simultaneously quantified tamoxifen and measured triglycerides and phosphatidylcholines. Triglycerides were upregulated in the tamoxifen-treated cells and the results indicated two distinct cell populations, differing in tamoxifen and phosphatidylcholines levels, suggesting heterogeneity within the treated population. In conclusion, these findings highlight the D100/LVC-MS system as a cost-effective, high-throughput platform for single-cell metabolomics and lipidomics, with significant potential for evaluating metabolic alterations.

Chromatography↗
DOE OSTI2026

Effect of magneto-mechanical synergism in the process-structure correlation in Fe–C alloys: A phase-field modeling approach

Applied magnetic fields can alter phase equilibria and kinetics in steels; however, quantitatively resolving how magnetic, chemical, and elastic driving forces jointly influence the microstructure remains challenging. We develop a quantitative magneto-mechanically coupled phase-field model for the Fe–C system that couples a CALPHAD-based chemical free energy with demagnetization-field magnetostatics and microelasticity. Here, the model reproduces single- and multi-particle evolution during the α → γ inverse transformation at 1023 K under external fields up to 20 T, including ellipsoidal morphologies observed experimentally at 8 T. Chemically driven growth is isotropic; a magnetic interaction introduces an anisotropic driving force that elongates γ precipitates along the field into ellipsoids, while elastic coherency promotes faceting, yielding elongated cuboidal or “brick-like” particles under combined magneto-elastic coupling. Growth kinetics increase with C content, and decrease with field strength and misfit strain. Multi-particle simulations reveal dipolar interaction-mediated coalescence for field-parallel neighbors and ripening for field-perpendicular neighbors. Incorporating field-dependent diffusivity from experiment slows kinetics as expected; a first-principles-motivated anisotropic diffusivity correction is estimated to be small (<2%). These results establish a process-structure link for magnetically assisted heat treatments of Fe–C alloys and provide guidance for microstructure control via chemo-magneto-mechanical synergism.

Magnetic field↗
DOE OSTI2022

Estimation of the time for steam generator trip due to cyber intrusions

The time required to trip a pressurized water reactor (PWR) by inserting malicious signals into its steam generator (SG) control system has been studied using the Generic PWR (GPWR) Simulator. A semi-analytical model is developed to approximately reproduce the simulator response and understand the dynamics of the control unit. A series of two proportional-integral controllers determines control action according to preset constants, the readings from the feedwater level sensor, and those from feedwater and steam flowrate transmitters. It is observed that the most important factor that determines whether a trip will occur is how much additional water is added to or withheld from the SG over time compared to normal operating conditions. In order to determine the effects of control action on the SG, changes in mass inventory are considered. This approach models the SG water level as a function of mass inventory and has a backward temporal memory. A Python interface is developed for the GPWR framework to automatically simulate different spoofing scenarios and post-process the related data. We observe that the trip times predominantly depend on flow mismatch and/or level errors. Controller parameters, including the integral time and gain constants, either speed up or slow down the rate of progression to a trip setpoint but do not cause a trip by themselves. The reactor can trip on a high-level signal when the reading crosses above 78%, increased from its reference level of 57%, or a low-level reading when it is below 25%. The present results show roughly how long the operators would have to respond to an attack, given a specific set of spoofing signals within the issue space analyzed. Furthermore, we have generated a simple surface by fitting a combination of exponential functions to the data obtained from the GPWR Simulator. In general, trips on a low level have been observed to occur faster than those on a high level.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Structural Heterogeneity and Hydrodynamics of an Intrinsically Disordered Protein Condensate

Biology demonstrates precise control over the free-energy landscape through the selective partitioning of biomacromolecules into membraneless organelles, enabling essential functions such as biochemical transformations, signaling cascades, and mechanical reinforcement. Although the function of these condensates depends on their underlying structure and hydrodynamics, molecular-scale information on these systems remains sparse. Here, in this study, neutron scattering is used to probe the organization and dynamics of the intrinsically disordered N-terminal domain of Galectin-3, an extracellular lectin responsible for facilitating liquid–liquid phase separation on the cellular surface, in both dilute and condensed phases. Dilute solutions contain isolated protein chains in equilibrium with mesoscopic clusters, whereas the condensed phase adopts a bicontinuous, microemulsion-like morphology. The dilute phase behavior is quantitatively described by coarse-grained polymer models from soft-matter physics, demonstrating their predictive power for complex biological proteins. At elevated concentrations, the proteins self-assemble akin to block copolymers, microphase separating through the aggregation of hydrophobic domains along the protein contour. The resulting condensate remains fluid-like despite a 25-fold increase in concentration; its internal hydrodynamics slow by only a factor of 3 relative to dilute protein chains. These results provide a molecular-level framework for how disordered proteins achieve both the structural complexity and dynamic fluidity of biomolecular condensates.

Carrick, Brian R. [Massachusetts Inst. of Technolo↗
DOE OSTI2024

Formation kinetics and thermodynamic stability of the Aurivillius compounds in Bi 4 Ti 3 O 12 –BiFeO 3 system

Abstract The Aurivillius compounds in the Bi 2 O 3 –Fe 2 O 3 –TiO 2 system, combining ferroelectric, semiconducting, and ferromagnetic properties, have attracted particular interest. Formation kinetics and thermodynamic stability are the fundamental knowledge needed for modeling and predicting the temporal microstructure and property evolution during materials processing but have not yet been addressed by quantitative experimental measurement. This article focuses on the Bi n +1 Fe n –3 Ti 3 O 3 n +3 Aurivillius compounds on the Bi 4 Ti 3 O 12 –BiFeO 3 tie‐line to elucidate the mechanisms and thermodynamic controls responsible for phase formation of compounds with various perovskite‐like layers. Five high‐purity Aurivillius compounds Bi 4 Ti 3 O 12 , Bi 5 FeTi 3 O 15 , Bi 6 Fe 2 Ti 3 O 18 , Bi 7 Fe 3 Ti 3 O 21 , and Bi 8 Fe 4 Ti 3 O 24 with integer n = 3–7 values were synthesized and their phase transformation properties and enthalpies of formation were studied by X‐ray diffraction in situ, high temperature differential scanning calorimetry, and high temperature oxide melt solution calorimetry. Thermodynamic stability of the compounds decreases with increasing n , and formation kinetics gradually slow down, demonstrating the inherent difficulty to synthesize pure Aurivillius compounds with n larger than 8. This difficulty was confirmed by an impurity phase coexisting with Bi 9 Fe 5 Ti 3 O 27 .

Gong, Weiping↗
DOE OSTI2023

Understanding the Uncertainty in the Technical Performance Level Assessment for Wave Energy

In recent years, the design and development of wave energy converters (WECs) has been explored with intense interest, with highly varying design concepts emerging globally across both research enterprises and industry. The design space for WECs is vast - many concepts ranging in functionality, control systems, power development systems, materials, and scale have been ideated and prototyped, but WEC technology has yet to converge. One critical element of the technology trajectory that governs the speed of adoption is the performance of a WEC concept. In analogous but more-established industries (such as aerospace, and environmentally sustainable electronics design), performance assessment is a quantitative method, based on historical data, that is used as an iterative tool to improve the design of these systems early on in the design process. Though more nascent than these approaches, in wave energy R&D, WEC performance has been assessed using the Technology Performance Level (TPL) assessment, which provides designers with a quantitative score, situating a grid-scale WEC concept on a scale from 1-9 (1 being the lowest performance, and 9 being the highest, trending with the oft-used Technology Readiness Level, or TRL). The TPL assessment is designed to be used during design iteration, when a WEC concept is fully ideated, to enable designers to consider potential means of improving the downstream performance of the concept. One concern that may be slowing the adoption of TPL among WEC developers is the inherent uncertainty in the assessment, and how uncertainty in the individual questions asked as part of the assessment may contribute to perceived inaccuracies in the final score. In this work, we explore the uncertainty present in the assessment and quantify this uncertainty using both traditional mathematical operations and a Monte Carlo simulation. Results imply areas of improvement of the TPL assessment, where reducing uncertainty will be most helpful to end users, enabling both TPL practitioners and users to understand with more accuracy those design elements that can be improved to impact device performance most substantively.

techno-economic analysis↗
DOE OSTI2026

Rewarding Grid-Friendly Behavior: Estimating the Potential Bill Reduction and Load Shifting Benefits of Dynamic Prices

Shifting electric load from times of peak demand can be a key strategy to slow price growth as reducing peak demand avoids the cost of upgrading generation, transmission and distribution infrastructure. Utilities are releasing time-varying prices, such as time of use rates or dynamic prices, to incentivize grid-friendly load shifting. New dynamic price programs provide insight into the true cost of operating electricity grids and the potential economic benefits of load shifting. Program developers and device manufacturers need to understand the economic opportunities in terms of 1) the variation in prices across hours, days, and seasons; 2) the change in utility bills for customers who don’t shift load; and 3) the potential load shifted and economic value of different technologies if manufacturers or aggregators deploy price-responsive controls. This paper estimates possible impacts of dynamic price adoption and load shifting controls if customers paid the dynamic rate from one pilot program. Statistical analysis of historical prices identified annual and seasonal metrics as well as representative price curves for each circuit in the pilot. Simulations for residential technologies with price-responsive controls including unitary heat pump water heaters, central multifamily heat pump water heaters, heating & cooling + storage systems, and pool pumps estimated the potential impacts of highly dynamic prices both with and without load shifting controls. Results showed the potential to reduce electricity costs on representative days by 42-94% and reduce consumption during times of high electricity prices by 63-100% compared to baseline operation for those flex-friendly devices.

Grant, Peter↗
DOE OSTI2021

Reducing roughness and improving efficiency of MAPbI3 perovskite solar cells made by high-throughput photonic curing

For perovskite solar cells (PSCs) to be commercially viable, the slow and energy-insufficient thermal annealing step must be eliminated. Among the photo-irradiation methods proposed to replace thermal annealing, photonic curing is the fastest conversion method. Photonic curing delivers short (20 μs to 100 ms) but intense light pulses from a broadband (200-1500 nm) xenon flash lamp, making it the only method to convert perovskite under 20 ms. This processing time can be extrapolated to a roll-to-roll web speed of 40 m/min based on laboratory processing conditions. However, most reported PSCs made by photonic curing under 1 second have inferior performance (~10% PCE). Although SEM images show dense and pinhole-free perovskite films, AFM images indicate secondary wavy features of 500 nm-wide ridge and 80 nm-deep trenches on photonically cured perovskite films, the existence of which correlates with poor device performance. We suggest that this morphology feature is produced by volatile solvent evaporation during the fast photonic curing process. Two approaches have been made to remedy this issue: (1) adding CH2I2 as the third solvent in the conventional DMF-DMSO system and (2) applying a controlled air-blowing step before photonic curing to remove excess solvent further. Combining these two approaches produces photonically- cured perovskite films with a comparable film roughness and device performance. Alkyl halide additives have been reported to enhance PSC performance by modulated solvent-solute interactions and C-X (X = Cl, Br, and I) cleavage. Photonic curing can cleave CH2I2, producing disassociated iodide ions to replenish iodine loss induced by photonic curing, which is confirmed by EDX. As a co-solvent, the high boiling point of CH2I2 can also make the solvent less volatile, reducing surface roughness in photonically cured perovskite films. Additionally, photonically-cured perovskite films have longer PL lifetimes and a higher recombination resistance compared to thermally-annealed counterparts. As a result, we demonstrate that photonic curing is a suitable method to replace thermal annealing in high-throughput PSC fabrication.

14 SOLAR ENERGY↗