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At least 1,513 records · Page 84

Scaling dynamics in low-salt-rejection reverse osmosis for high-salinity produced water desalination: Mechanistic modeling and membrane autopsy

Membrane scaling remains a critical barrier to the reliable operation of desalination systems, particularly for hypersaline produced water (PW) treatment. This study fills the knowledge gap of autopsy-based model validation for PW desalination by elucidating scaling mechanisms in a Low-Salt-Rejection Reverse Osmosis (LSRRO) system through the integration of pilot-scale experimentation and complementary modeling approaches. A semi-empirical modeling framework was developed and applied to a multistage pilot LSRRO system equipped with nanofiltration and RO membranes treating high-salinity PW from the Permian Basin. Water quality analysis showed that total dissolved solids decreased from ~130,000 mg/L to ~1900 mg/L in the permeate, then further reduced to ~300 mg/L by a second-pass RO. Two different thermodynamic modeling approaches were evaluated: the first extends the LSRRO framework by incorporating system complexity and scaling phenomena, whereas the second method explicitly captures concentration polarization in localized supersaturation. Both methods illustrate the tendency for carbonate and sulfate scaling throughout the stages. Membrane autopsies revealed a silica-dominated deposit matrix, localized CaSO 4 at Stage 2, and minor barite/celestite despite their prominence in model predictions. Quantum-chemical calculations indicated silica scaling can be rationalized by favorable adsorption of H 4 SiO 4 on Fe-oxide surfaces (ΔG ≈ −44 kJ/mol), providing a kinetic pathway for interfacial inorganic polymerization even when bulk equilibrium predictions are conservative. Overall, the thermodynamic scaling modeling and membrane autopsy revealed heterogeneous, localized deposits with limited impact on LSRRO performance, while quantum analysis rationalized the thermodynamically unfavorable precipitation formation under bulk equilibrium, reconciling model–autopsy discrepancies. These insights support targeted pretreatment and silica-specific antiscalants to extend membrane lifetime and increase recovery, providing a transferable framework for hypersaline water desalination systems. The combined experimental–computational approach provides new mechanistic insight into scaling in hypersaline membrane systems and establishes a transferable framework for predicting and mitigating scaling in next-generation desalination technologies.

Low-salt-rejection reverse osmosis↗

Learning model combining convolutional deep neural network with a self-attention mechanism for AC optimal power flow

Alternating current optimal power flow (OPF) analysis is critical for efficient and reliable operation of power systems. For large systems or repetitive computations, the traditional methods such as the direct and gradient methods, or non-traditional methods, such as the genetic algorithm and simulating annealing, are time-consuming and unsuitable for real-time computing. The work in this paper proposes a novel framework to obtain the optimal solution of power flow in real-time using a combination of convolutional neural networks and a self-attention mechanism. All parameters of the power networks are rearranged in an image-like shape of a multi-channel image where each channel is a two-dimensional matrix. The proposed approach is adaptive with every input size of power systems as well as frequent variations of network topologies without intervention to the framework core. The encompassment of all power system contexts in which all parameters of internal elements, generation costs, and topology information are included, contributes to the higher accuracy of inference compared to other current machine-learning-based OPF-solving methods. Besides, the proposed framework established on ubiquitous platforms is effortlessly integrated into current infrastructures of power systems, and the great efficiency along with the computation speed may serve as a critical point for practical implications, such as enabling faster decision-making during real-time operations, predicting system contingencies, and remedial actions based on an offline pre-trained model. Furthermore, this supervised learning process is applied to the dataset of four case studies of meshed power systems: the IEEE 5-bus system (IEEE-5), the IEEE 30-bus system (IEEE-30), the IEEE 39-bus system (IEEE-39), and the IEEE 57-bus system (IEEE-57) to prove the efficacy of the proposed method.

42 ENGINEERING↗

Networked Microgrid Topology Reconfiguration to Promote Fairness in Proactive Load Shedding

Increasing occurrences of natural disasters and grid emergency events consistently challenge the safe and reliable operations of power systems. During such emergency situations, system operators may proactively shed load to mitigate risks. However, uncoordinated implementation of load shedding may disrupt electricity supply and even lead to cascading failures. Meanwhile, it is crucial to address potential biases affecting different customers when executing load shedding. This paper addresses the dynamic topology reconfiguration problem for networked microgrids with distributed energy resources under emergency conditions. Specifically, we propose a novel rolling-horizon optimization model that integrates fairness-aware constraints into the networked microgrid topology reconfiguration. Unlike existing approaches that focus solely on efficiency or apply fairness considerations in static settings, our method explicitly incorporates temporal fairness constraints to restrict repeated or excessive load curtailment for load blocks. Moreover, the fairness-aware constraints are specifically developed for the context of dynamic networked microgrid topology reconfiguration, and are designed to be convex or amenable to linear reformulations, which offers a more tractable alternative to traditional models with non-convex formulations. Numerical studies on a modified IEEE 13-bus system and a larger-sized SMART-DS networked microgrid system demonstrate the performance of the proposed algorithm towards more fairness-aware networked microgrid topology reconfiguration decision-making.

24 POWER TRANSMISSION AND DISTRIBUTION↗

MOOSE-based Tritium Migration Analysis Program, Version 8 (TMAP8) for advanced open-source tritium transport and fuel cycle modeling

Tritium management is critical for the safety, sustainability, and economics of fusion energy systems, and advanced and reliable modeling tools help accelerate the development of tritium technologies. This paper presents the Tritium Migration Analysis Program, Version 8 (TMAP8), an open-source, MOOSE-based application developed to provide state-of-the-art tritium transport and fuel cycle modeling capabilities. TMAP8 aims to expand the capabilities of previous versions (i.e., TMAP4 and TMAP7) by leveraging modern computational techniques, ensuring high software quality assurance standards (key to building trust), and enabling multispecies, multiscale, and multiphysics simulations for integrated tritium transport modeling in complex geometries. This paper outlines TMAP8’s scope and rigorous development practices, emphasizing its transparency, accessibility, modularity, and reliability. We present the current suite of verification and validation cases based on those from TMAP4, demonstrating TMAP8’s accuracy and reliability against analytical solutions and experimental data. Additionally, the paper showcases TMAP8’s integrated fuel cycle modeling capabilities, highlighting its applicability at various scales and levels. The TMAP8 code and documentation are openly available, promoting collaborative development and widespread adoption within the fusion community. Future work will soon expand TMAP8’s verification and validation suite to include those from TMAP7 and other recent experimental studies for validation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Lab-scaled performance evaluation of novel water-lean solvents for post combustion CO 2 capture

Here, this work focuses on demonstrating the energetic performance and operational reliability in a continuous system of RTI's water-lean solvents for post-combustion CO 2 capture applications. RTI's Non-Aqueous Solvent, NAS-1A was subjected to 100 h of continuous, CO 2 capture and regeneration operation using a Lab-scale Gas Absorption System (LsGAS) while the CO 2 capture efficiency, mass balance, and total energy inputs were monitored. Throughout the test period, NAS-1A demonstrated stable operation with 90% CO 2 capture while requiring about 15% lower total energy input for solvent regeneration compared to 30 wt% monoethanolamine (MEA) solution. The use of a slipstream of CO 2 -rich solvent from the absorber sump reduced the regenerated CO 2 temperature before the gas was further cooled by the overhead condenser at the top of the desorber. The rich-split setup combined with a wash section may be an effective approach to remove water and solvent vapor from the regenerated CO 2 as well as to recover heat at the top of the desorber. NAS-1B was later developed and included a modifier component that lowers the heat of CO 2 absorption and reduces the vapor pressure of the amine component. The total energy inputs for 90% CO 2 capture with NAS-1B was found to be 25% less than that of the MEA. A gas chromatograph was used to monitor the amine concentration in the gas leaving the absorber wash section. It was found that under similar operating conditions, the presence of the modifier in NAS-1B reduces the amine in the absorber off-gas from 143 ppm in NAS-1A to 20 ppm.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The HydroBio Dataset: a new data resource for evaluating existing and potential hydropower capacity and freshwater biodiversity in the conterminous United States

Hydropower is a critical source of affordable and reliable electricity and energy system stability services in the United States. Opportunities to expand US hydropower production include retrofitting existing non-powered dams to produce power, retrofitting existing hydropower dams to improve efficiency or increase capacity, or constructing new hydropower infrastructure on currently unregulated river reaches. We created the HydroBio Dataset, which summarizes existing and potential hydropower capacity and freshwater biodiversity at the sub-basin scale in the conterminous US to contextualize existing and potential grid contributions with the freshwater ecosystems in which dams are situated. We demonstrate a use-case of this dataset by rescaling and comparing potential non-powered dam nominal capacity to rarity-threat-weighted freshwater species richness for sub-basins where both types of data exist. On average, normalized freshwater biodiversity exceeded normalized potential non-powered dam nominal capacity in these sub-basins. Potential non-powered dam nominal capacity was concentrated in sub-basins in the Upper Mississippi and Ohio hydrologic regions while freshwater biodiversity was concentrated in the South Atlantic-Gulf, Ohio, and Tennessee hydrologic regions. Additionally, non-powered dams and existing hydropower dams are located in sub-basins with similar indices of freshwater biodiversity. The HydroBio Dataset adds an additional ecological dimension of context to our understanding of current and potential future US hydropower capabilities and is a valuable decision support tool for stakeholders tasked with balancing gains in services to the US power grid with the public and environmental benefits of freshwater ecosystems.

Biodiversity↗

Application of QMU to the design of a nuclear waste storage tank

Defining the reliability of complex physical systems is crucial for system certification and guaranteeing safety, but is often complicated by the presence of many uncertainties and system sub-components. One such example is the certification of the Hanford Waste Treatment Plant, where radioactive and toxic chemical waste that spontaneously generates flammable gases is stored in large tanks. We introduce the QMU methodology to quantify the system safety of waste storage tanks in the event of a loss of tank ventilation, which poses a safety risk to workers. We also show how QMU can be used as a design tool to find operating regimes that maintain a desired confidence level. A simplified physical model is used to analyze the build-up of hydrogen gas in storage tanks and conduct an uncertainty propagation study to quantify the operating margin with respect to the flammability conditions. A demonstration problem is shown in which the radiation loading in a waste tank is iteratively modified until a desired confidence ratio is achieved. The results show that the resulting designs are sensitive to the use of interval or full QMU to achieve a confidence ratio, and it is not always possible to realize a design at a particular confidence ratio.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Additively manufactured multiplexed inertial coalescence filters

Multiphase flows often pose a significant challenge to the efficient and reliable design of thermofluidic systems. This paper describes multiplexed inertial coalescence filters composed of parallel helical pathways, designed to capture fine droplets (<40 µm) through inertial separation while maintaining a low pressure drop (<400 Pa). Filtration efficiencies for 7 µm and 30 µm droplets were characterized for varying flow conditions, with complete capture observed above a threshold flow rate. Models for filtration efficiency and pressure drop were developed and validated against experimental results to allow system design and optimization, enabled by the tunable additive manufacturing approach used to fabricate the filters. Filter quality factor was computed for varying droplet sizes, showcasing exceptional quality factor when compared to state-of-the-art filters documented in the literature. In conclusion, this multiplexed inertial coalescence filtration approach could find use in dehumidification systems, fog harvesting, chemical reactors, and microgravity droplet capture.

3D Printing↗

Overcoming significant challenges in extracting off-stoichiometric thermodynamics using the compound energy formalism through complementary use of experimental and first principles data: A case study of Ba 1-x Sr x FeO 3-δ

The compound energy formalism (CEF) is a powerful framework to describe the thermodynamics of metal oxides as a function of off-stoichiometry, temperature, and composition. The thermodynamic properties are crucial materials design attributes in metal oxide-based oxygen-exchange chemical processes. Despite the richness of information an accurate CEF model provides, a method to determine a unique and accurate fit for oxygen exchange materials remains elusive. This contribution details a method for fitting the CEF model that overcomes the current fitting challenges through three innovations: 1) the combination of density functional theory calculations with experimental data decorrelates excess terms and delineates the enthalpic/entropic contributions to the Gibbs free energy; 2) a systematic determination of the important CEF model terms, removing thermodynamic predetermining human intervention; 3) a self-consistent solution of the starting oxygen offstoichiometry (δ 0 ) of thermogravimetric measurements. Thus, our method enables the reliable extraction of off-stoichiometric metal oxide thermodynamic properties and facilitates rapid materials compositional screening, and reliable process design of systems dependent on off-stoichiometric redox-active metal oxides. We apply this method to a Ba x Sr 1-x FeO 3-δ test case. We find by systematically examining the performance of the CEF model fit with and without each innovation that all three innovations are necessary for an accurate fit. We determined that reduction enthalpy is higher and more sensitive to off-stoichiometry when the Sr fraction is large (139.5 and 185.3 kJ/mol O 2 for SrFeO 3 at δ = 0 and δ = 0.5, respectively vs. nearly constant 83 kJ/mol O 2 for BaFeO 3 ). However, the reduction entropy is mostly insensitive to Sr fraction, but highly dependent on δ suggesting larger contributions in the non-configurational entropy parameters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Ground State Electronic Energy of Benzene

We report here on the findings of a blind challenge devoted to determining the frozen-core, full configuration interaction (FCI) ground-state energy of the benzene molecule in a standard correlation-consistent basis set of double-ζ quality. As a broad international endeavor, our suite of wave function-based correlation methods collectively represents a diverse view of the high-accuracy repertoire offered by modern electronic structure theory. In our assessment, the evaluated high-level methods are all found to qualitatively agree on a final correlation energy, with most methods yielding an estimate of the FCI value around -863 mE H . However, we find the root-mean-square deviation of the energies from the studied methods to be considerable (1.3 mE H ), which in light of the acclaimed performance of each of the methods for smaller molecular systems clearly displays the challenges faced in extending reliable, near-exact correlation methods to larger systems. While the discrepancies exposed by our study thus emphasize the fact that the current state-of-the-art approaches leave room for improvement, we still expect the present assessment to provide a valuable community resource for benchmark and calibration purposes going forward.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Tribochemical Conversion of Methane to Graphene and Other Carbon Nanostructures: Implications for Friction and Wear

Tribochemistry involves chemical reactions occurring at sliding contact interfaces in the presence of gaseous and/or liquid media. It often leads to the formation of a solid reaction film (also termed boundary film) which controls friction and wear and hence the efficiency and reliability of moving mechanical systems (such as engines). Here we demonstrate tribochemical conversion of methane to graphene, nano-onion, and disordered carbons on the sliding surfaces of Ni-, Cu-, and CuNi-containing VN coatings at atmospheric pressure and room temperature, providing 2-3 orders of magnitude reduction in wear and similar to 50% reduction in friction compared to those of the uncoated steels. Transmission electron microscopy confirms that graphene forms preferably on metal rich nanoclusters of the composite coatings, while the carbon nano-onions are scattered throughout the carbon tribofilm. Ab initio molecular dynamics simulations elucidate underlying mechanisms involved in the tribochemical conversion of methane to carbon- based nanostructures in support of microscopic observations. These scientific findings may lead to new materials technologies that can use methane as a source for continuous and in situ lubrication. For example, there is an urgent need to curtail the uses of lubricating oils in natural gas compressors and engines as they contaminate the natural gas being compressed or burnt.

36 MATERIALS SCIENCE↗

Genome-Wide Tuning of Protein Expression Levels to Rapidly Engineer Microbial Traits

The reliable engineering of biological systems requires quantitative mapping of predictable and context-independent expression over a broad range of protein expression levels. However, current techniques for modifying expression levels are cumbersome and are not amenable to high-throughput approaches. Here we present major improvements to current techniques through the design and construction of E. coli genome-wide libraries using synthetic DNA cassettes that can tune expression over a ~10 4 range. The cassettes also contain molecular barcodes that are optimized for next-generation sequencing, enabling rapid and quantitative tracking of alleles that have the highest fitness advantage. We show these libraries can be used to determine which genes and expression levels confer greater fitness to E. coli under different growth conditions.

59 BASIC BIOLOGICAL SCIENCES↗

High-Resolution Meteorology with Climate Change Impacts from Global Climate Model Data Using Generative Machine Learning

As renewable energy generation increases, the impacts of weather and climate on energy generation and demand become critical to the reliability of the energy system. However, these impacts are often overlooked. Global climate models (GCMs) can be used to understand possible changes to our climate, but their coarse resolution makes them difficult to use in energy system modelling. Here we present open-source generative machine learning methods that produce meteorological data at a nominal spatial resolution of 4 km at an hourly frequency based on inputs from 100 km daily-average GCM data. These methods run 40 times faster than traditional downscaling methods and produce data that have high-resolution spatial and temporal attributes similar to historical datasets. We demonstrate that these methods can be used to downscale projected changes in wind, solar and temperature variables across multiple GCMs including projections for more frequent low-wind and high-temperature events in the Eastern United States.

climate change↗

Development of a time-variable nuclear pulser for half life measurements

In this work a time-variable pulser system with an exponentially-decaying pulse frequency is presented, which was developed using the low-cost, open-source Arduino microcontroler plataform. In this system, the microcontroller produces a TTL signal in the selected rate and a pulse shaper board adjusts it to be entered in an amplifier as a conventional pulser signal; both the decay constant and the initial pulse rate can be adjusted using a user-friendly control software, and the pulse amplitude can be adjusted using a potentiometer in the pulse shaper board. The pulser was tested using several combinations of initial pulse rate and decay constant, and the results show that the system is stable and reliable, and is suitable to be used in half-life measurements.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Film-coupled nanoparticles by atomic layer deposition: Comparison with organic spacing layers

Film-coupled nanoparticle systems have proven a reliable platform for exploring the field enhancement associated with sub-nanometer sized gaps between plasmonic nanostructures. In this Letter, we present a side-by-side comparison of the spectral properties of film-coupled plasmon-resonant, gold nanoparticles, with dielectric spacer layers fabricated either using atomic layer deposition or using organic layers (polyelectrolytes or self-assembled monolayers of molecules). In either case, large area, uniform spacer layers with sub-nanometer thicknesses can be accurately deposited, allowing extreme coupling regimes to be probed. The observed spectral shifts of the nanoparticles as a function of spacer layer thickness are similar for the organic and inorganic films and are consistent with numerical calculations taking into account the nonlocal response of the metal.

36 MATERIALS SCIENCE↗

Update on developments at SNIF

The Small Negative Ion Facility (SNIF) at CCFE has been undergoing continuous development and enhancement to both improve operational reliability and increase diagnostic capability. SNIF uses a CW 13.56MHz, 5kW RF driven volume source with a 30kV triode accelerator. Improvement and characterisation work includes: Installation of a new “L” type RF matching unit, used to calculate the load on the RF generator. Use of the electron suppressing biased insert as a Langmuir probe under different beam extraction conditions. Measurement of the hydrogen Fulcher molecular spectrum, used to calculate gas temperature in the source. Beam optimisation through parameter scans, using copper target plate and visible cameras, with results compared with AXCEL-INP to provide beam current estimate. Modelling of the beam power density profile on the target plate using ANSYS to estimate beam power and provide another estimate of beam current. This work is described, and has allowed an estimation of the extracted beam current of approximately 6mA (4mA/cm2) at 3.5kW RF power and a source pressure of 0.6Pa.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Reliability of unstable periodic orbit based control strategies in biological systems

Presence of recurrent and statistically significant unstable periodic orbits (UPOs) in time series obtained from biological systems is now routinely used as evidence for low dimensional chaos. Extracting accurate dynamical information from the detected UPO trajectories is vital for successful control strategies that either aim to stabilize the system near the fixed point or steer the system away from the periodic orbits. A hybrid UPO detection method from return maps that combines topological recurrence criterion, matrix fit algorithm, and stringent criterion for fixed point location gives accurate and statistically significant UPOs even in the presence of significant noise. Geometry of the return map, frequency of UPOs visiting the same trajectory, length of the data set, strength of the noise, and degree of nonstationarity affect the efficacy of the proposed method. Results suggest that establishing determinism from unambiguous UPO detection is often possible in short data sets with significant noise, but derived dynamical properties are rarely accurate and adequate for controlling the dynamics around these UPOs. A repeat chaos control experiment on epileptic hippocampal slices through more stringent control strategy and adaptive UPO tracking is reinterpreted in this context through simulation of similar control experiments on an analogous but stochastic computer model of epileptic brain slices. Reproduction of equivalent results suggests that far more stringent criteria are needed for linking apparent success of control in such experiments with possible determinism in the underlying dynamics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A reliable, compact, and repetitive-rate high power microwave generation system

A compact high power microwave (HPM) generation system is described in this paper. The main parts of the HPM system are a Marx generator with a pulse forming line and a magnetron with diffraction output. The total weight and length of the system are 250 kg and 120 cm, respectively. The output microwave power of the HPM system at 550 kV of applied voltage and 0.33 T of magnetic field reaches 1 GW at 2.32 GHz of central frequency with 38 ns of pulse duration, 23% of power conversion efficiency, and Gaussian radiation pattern. In the bursts operation, both time and amplitude jitters are less than 4 ns and lower than 1.5 dB, respectively.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗