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At least 1,063 records · Page 59

A reduced-order model of concentration polarization in reverse osmosis systems with feed spacers

Feed spacers in reverse osmosis systems generate complex fluid flows that limit computational fluid dynamics (CFD) simulations to small length and time scales. That limits our ability to simulate mineral scaling and other membrane fouling phenomena, which occur over longer length and time scales. Thus motivated, we develop a reduced model that replaces the CFD simulation of the velocity field with an analytical model that mimics spacers. This focuses the remaining numerical effort on simulating the advection–diffusion equation governing solute transport. We motivate and validate the model with CFD simulations and bench-scale experiments of spacer filaments in three different arrangements, including cases of unsteady vortex shedding. We show that the model produces a roughly 10,000-fold speedup compared to CFD, and accurately reproduces CFD predictions of not only the average and maximum concentrations, but also the local concentration distribution along the membrane. Here, we also demonstrate the model for simulating a feed channel with a length-to-height ratio of 200. The model provides a simple testbed for exploratory studies of multispecies transport, precipitation, and membrane fouling phenomena for which simulating spacers is often prohibitive.

Computational fluid dynamics↗

Studying the effect of the upper internal structure design on thermal stratification in sodium fast reactors

Thermal stratification and mixing in large reactor pools can pose significant issues with regard to operation and safety of nuclear plants. While significant work has been done in this area on light water reactors it is more critical for sodium reactors and there is far less data with regard to low Prandtl number fluids. Here this paper focuses on the effect of the upper internal structure on the formation of thermal stratification in a scaled sodium fast reactor upper plenum. Six different upper internal structure configurations were tested to observe the effect on thermal stratification. The degree of stratification was quantified using the stratification number. Each configuration was tested from low to high flow rates at a temperature difference of 50 and 100 °C. Over this broad array of testing, it was observed that higher flow rates, more porosity in the upper internal structure design, and a smaller temperature difference yielded a lower degree of stratification. This information can be used to aid in the design of the upper internal structure in a sodium fast reactor. Furthermore, this high resolved temperature data can be used to verify models under prototypic low Prandtl numbers.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Indicators of carbon alteration (ICAs) suggest patterns in reservoir methane emissions

Reservoir operations influence emissions via multiple causal pathways. In this paper, we quantify indicators of carbon alteration (ICAs) focused on methane. ICAs were chosen to reflect the potential for methane emission along four causal pathways: 1) water column mixing, 2) wet-dry cycles in sediment, 3) sediment redistribution, and 4) vegetation. We developed algorithms to calculate ICAs for three reservoirs along a longitudinal gradient in the Tennessee River basin of the southeast US. The ICAs revealed interesting longitudinal patterns. Indicators of both methane production and destruction increased downstream. The potential for ebullitive methane emissions driven by sub-daily water level fluctuations and emissions mediated by vegetation were higher in downstream mainstem reservoirs than in the upstream tributary reservoir. Along the remaining two pathways, longitudinal patterns were equivocal (sediment pathway) or suggested decreased emissions downstream (water-column mixing). We also observed seasonal patterns and, by combining ICAs, inferred times when ramping could be achieved with lower risk of emissions. The ICAs demonstrated here are the first step in quantifying mechanistic relationships between reservoir operation and methane emissions. In future, they may lead to improved operations in reservoir cascades and regional-scale estimates of emissions that account for differences among reservoirs.

Greenhouse gases↗

Multi-parametric analysis for mixed integer linear programming: An application to transmission upgrade and congestion management

Upgrading the capacity of existing transmission lines is essential for meeting the growing energy demands, facilitating the integration of renewable energy, and ensuring the security of the transmission system. This study focuses on the selection of lines whose capacities and by how much should be expanded from the perspective of the Independent System Operators (ISOs) to minimize the total system cost. We employ advanced multi-parametric programming and an enhanced branch-and-bound algorithm to address complex mixed-integer linear programming (MILP) problems, considering multi-period time constraints and physical limitations of generators and transmission lines. To characterize the various decisions in transmission expansion, we model the increased capacity of existing lines as parameters within a specified range. This study first relaxes the binary variables to continuous variables and applies the Lagrange method and Karush-Kuhn-Tucker (KKT) conditions to obtain optimal solutions and identify critical regions associated with active and inactive constraints. Moreover, we extend the traditional branch-and-bound (B&B) method by determining the problem’s upper and lower bounds at each node of the B&B decision tree, helping to manage computational challenges in large-scale MILP problems. Here, we compare the difference between the upper and lower bounds to obtain an approximate optimal solution within the decision-makers’ tolerable error range. In addition, the first derivative of the objective function on the parameters of each line is used to inform the selection of lines for easing congestion and maximizing social welfare. Finally, the capacity upgrades are selected by weighing the reductions in system costs against the expense of upgrading line capacities. The findings are supported by numerical simulations and provide transmission-line planners with decision-making guidance.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Influence of Pelletization and Moisture Content of Oil Palm Empty Fruit Bunches (EFBs) on Dynamic Gasification Performance

Wet-ground empty fruit bunches (EFBs), dry-ground EFB, and pelletized EFB were gasified in a laboratory-scale updraft fixed-bed reactor at differing temperatures and equivalent ratios (ERs) between 0.19 and 0.78 to evaluate the performance and quality of the syngas under autothermal operating conditions. In addition, the theoretical estimation of the key performance indicator of the ashes on the performance of the gasification process was obtained. The results show that for ERs > 0.4 the autothermal operating condition was achieved for pretreatments with pelletized and dry-ground EFBs, with reactor operating temperatures T > 700 °C. With wet EFB, this condition is achieved at any ER value. The average composition of the syngas from pelletized EFB presented the best average concentrations of the combustible species CO, H2, and CH4 when the ER values were between 0.25 and 0.40. The highest hot and cold thermal efficiency values were obtained for the gasification of EFB pellets with ER values between 0.25 and 0.40. For ground EFB, increases in the ER value led to improvements in hot thermal efficiency. Finally, during the EFB pellet gasification tests, no agglomeration and sintering problems were evidenced in comparison with wet-ground and dry-ground EFBs that showed slag formation, especially at ER < 0.46.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Dynamic Surface Restructuring in Cu(Au) Alloys Driven by Oxygen-Mediated Au Mobility

Alloying plays a crucial role in tuning the surface properties of metals, but the atomic-level mechanisms by which alloying elements influence surface structure dynamics under reactive conditions remain elusive. Using Cu(Au) in oxidizing environments as a model system, we reveal a dynamic oxygen-induced transformation of the topmost atomic layer into a periodically hill-and-valley morphology with reversible switching between undulated and flattened surface states. These interconversions are driven by the retreat of surface Au to the subsurface during oxygen adsorption and its resegregation to the surface upon oxygen desorption. This cyclical mobility establishes a feedback loop, allowing the surface to dynamically reconfigure in response to changes in the oxygen pressure. The results offer a broadly applicable framework for understanding atomic-scale surface restructuring in alloy systems, where differences in the chemical reactivity of alloying elements drive dynamic redistribution between surface and subsurface regions. As a result, this dynamic coupling has practical implications for designing corrosion-resistant coatings and metastable nanostructures with tunable catalytic properties.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Real-Time Alignment and Reorientation of Polymer Chains in Liquid Crystal Elastomers

Liquid crystal elastomers (LCEs) exhibit soft elasticity due to the alignment and reorientation of mesogens upon mechanical loading, which provides additional mechanisms to absorb and dissipate energy. This enhanced response makes LCEs potentially transformative materials for biomedical devices, tissue replacements, and protective equipment. However, there is a critical knowledge gap in understanding the highly rate-dependent dissipative behaviors of LCEs due to the lack of real-time characterization techniques that probe the microscale network structure and link it to the mechanical deformation of LCEs. In this work, we employ in situ optical measurements to evaluate the alignment and reorientation degree of mesogens in LCEs. The data are correlated to the quantitative physical analysis using polarized Fourier-transform infrared spectroscopy. The time scale of mesogen alignment is determined at different strain levels and loading rates. The mesogen reorientation kinetics is characterized to establish its relationship with the macroscale tensile strain, and compared to theoretical predictions. Overall, this work provides the first detailed study on the time-dependent evolution of mesogen alignment and reorientation in deformed LCEs. It also provides an effective and more accessible approach for other researchers to investigate the structural-property relationships of different types of polymers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Microbial Pathways for Cost-Effective Low-Carbon Renewable Indigoidine

Indigoidine is a bioadvantaged platform molecule with diverse applications, including use as a textile dye, biotransistor, biosolar cell, biosensor, and food coloring. There are multiple microbial hosts and carbon sources that can be used and optimized for its production, yet there is limited guidance for which options have the greatest commercial potential. Here, we consider five different host microbes and combine genome-scale metabolic models with techno-economic and lifecycle assessment models. Pseudomonas putida currently outperforms synthetic indigo production and other indigoidine-producing hosts, using glucose, xylose, and lignin-derived aromatics to produce indigoidine at a minimum selling price of $2.9/kg and a greenhouse gas (GHG) footprint of 3.5 kgCO 2e /kg. Optimizing pathways-achieving 90% of the theoretical indigoidine yield from sugars and aromatics-can reduce costs 6-7-fold and GHG emissions 3-10-fold. From a cost perspective, microbes that co-utilize aromatics are advantageous, while selecting hosts that coproduce other value-added molecules can reduce GHG emissions. System-wide improvements and the use of a low-cost, low-carbon nitrogen source are crucial for commercial viability in all cases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Structural Evolution and Photoluminescence Quenching across the FASnI 3– x Br x ( x = 0–3) Perovskites

One of the primary methods for band gap tuning in metal halide perovskites has been halide (I/Br) mixing. Despite widespread usage of this type of chemical substitution in perovskite photovoltaics, there is still little understanding of the structural impacts of halide alloying, with the assumption being the formation of ideal solid solutions. The FASnI 3–x Br x (x = 0–3) family of compounds provides the first example where the assumption breaks down, as the composition space is broken into two unique regimes (x = 0–2.9; x = 2.9–3) based on their average structure with the former having a 3D and the latter having an extended 3D (pseudo 0D) structure. Pair distribution function (PDF) analyses further suggest a dynamic 5s 2 lone pair expression resulting in increasing levels of off-centering of the central Sn as the Br concentration is increased. These antiferroelectric distortions indicate that even the x = 0–2.9 phase space behaves as a nonideal solid-solution on a more local scale. Solid-state NMR confirms the difference in local structure yielding greater insight into the chemical nature and local distributions of the FA + cation. In contrast to the FAPbI 3–x Br x series, a drastic photoluminescence (PL) quenching is observed with x ≥ 1.9 compounds having no observable PL. In conclusion, our detailed studies attribute this quenching to structural transitions induced by the distortions of the [SnBr 6 ] octahedra in response to stereochemically expressed lone pairs of electrons. This is confirmed through density functional theory, having a direct impact on the electronic structure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

AlphaFold predictions are valuable hypotheses and accelerate but do not replace experimental structure determination

Abstract Artificial intelligence-based protein structure prediction methods such as AlphaFold have revolutionized structural biology. The accuracies of these predictions vary, however, and they do not take into account ligands, covalent modifications or other environmental factors. Here, we evaluate how well AlphaFold predictions can be expected to describe the structure of a protein by comparing predictions directly with experimental crystallographic maps. In many cases, AlphaFold predictions matched experimental maps remarkably closely. In other cases, even very high-confidence predictions differed from experimental maps on a global scale through distortion and domain orientation, and on a local scale in backbone and side-chain conformation. We suggest considering AlphaFold predictions as exceptionally useful hypotheses. We further suggest that it is important to consider the confidence in prediction when interpreting AlphaFold predictions and to carry out experimental structure determination to verify structural details, particularly those that involve interactions not included in the prediction.

59 BASIC BIOLOGICAL SCIENCES↗

Hidden order across online extremist movements can be disrupted by nudging collective chemistry

Disrupting the emergence and evolution of potentially violent online extremist movements is a crucial challenge. Extremism research has analyzed such movements in detail, focusing on individual- and movement-level characteristics. But are there system-level commonalities in the ways these movements emerge and grow? Here we compare the growth of the Boogaloos, a new and increasingly prominent U.S. extremist movement, to the growth of online support for ISIS, a militant, terrorist organization based in the Middle East that follows a radical version of Islam. We show that the early dynamics of these two online movements follow the same mathematical order despite their stark ideological, geographical, and cultural differences. The evolution of both movements, across scales, follows a single shockwave equation that accounts for heterogeneity in online interactions. These scientific properties suggest specific policies to address online extremism and radicalization. We show how actions by social media platforms could disrupt the onset and ‘flatten the curve’ of such online extremism by nudging its collective chemistry. Our results provide a system-level understanding of the emergence of extremist movements that yields fresh insight into their evolution and possible interventions to limit their growth.

99 GENERAL AND MISCELLANEOUS↗

Spontaneous self-propulsion and nonequilibrium shape fluctuations of a droplet enclosing active particles

Active particles, such as swimming bacteria or self-propelled colloids, spontaneously assemble into large-scale dynamic structures. Geometric boundaries often enforce different spatio-temporal patterns compared to unconfined environment and thus provide a platform to control the behavior of active matter. Here, we report collective dynamics of active particles enclosed by soft, deformable boundary, that is responsive to the particles’ activity. We reveal that a quasi two-dimensional fluid droplet enclosing motile colloids powered by the Quincke effect (Quincke rollers) exhibits strong shape fluctuations with a power spectrum consistent with active fluctuations driven by particle-interface collisions. A broken detailed balance confirms the nonequilibrium nature of the shape dynamics. We further find that rollers self-organize into a single drop-spanning vortex, which can undergo a spontaneous symmetry breaking and vortex splitting. The droplet acquires motility while the vortex doublet exists. Our findings provide insights into the complex collective behavior of active colloidal suspensions in soft confinement.

42 ENGINEERING↗

Kelvin probe force microscopy under ambient conditions

Kelvin probe force microscopy (KPFM) is a technique derived from atomic force microscopy that provides maps of surface potential or work function differences across material systems, with nanometre-scale resolution. KPFM is a useful tool for investigating electrical phenomena such as dipole orientation, interfacial charge transfer, charge accumulation, band bending and doping levels. This Primer aims to provide an overview of typical ambient-condition KPFM measurements, covering their underlying principles, experimental implementations and wide-ranging applications. Key KPFM variants, including amplitude and frequency modulation, heterodyne detection schemes and innovative open loop and pulsed force techniques, are discussed, with practical guidance on optimizing signal acquisition and reducing errors. Specialized approaches, such as time-resolved KPFM and multimodal KPFM, are discussed for their ability to capture dynamic charge processes and chemical information, respectively. Here, we highlight recent advances in KPFM applications, spanning metal alloys, soft matter, ferroelectrics, photovoltaics and 2D materials, showcasing its versatility across research domains. By addressing current limitations and identifying future opportunities, this Primer underscores the transformative potential of KPFM in advancing the understanding of nanoscale electrical phenomena.

Zahmatkeshsaredorahi, Amirhossein [Lehigh Univ., B↗

High throughput exploration of the oxidation landscape in high entropy alloys

We report high entropy alloys (HEAs) have gained interest for structural applications in extreme environments. With a potentially vast chemical and phase space, there are significant opportunities to discover superior performing alloys. Crucial for most high-temperature applications is understanding and mitigating the oxidation behavior of these chemically complex alloys. Most experimental and computational HEA studies have focused on a limited set of compositions and only a fraction these compositions have been characterized for oxidation. We present a high-throughput framework that utilizes density-functional theory (DFT) in concert with a combined machine-learning model and grand-canonical linear programming for assessing phase stability, phase-fraction, chemical activity and high-temperature survivability of arbitrary HEAs. This framework considers temperature dependent contributions to the Gibbs energy of the competing phases arising from short-range order and vibrational entropy. We demonstrate the effectiveness of the framework by assessing the thermodynamic stability, oxidation behavior, chemical activity, and phase decomposition of body-centered cubic Mo-W-Ta-Ti-Zr refractory HEAs. A total of 51 compositions were analyzed and ranked in order of their survivability based on the Pareto-front analysis. Oxidation was performed at 1373 K on fours samples in air showing the difference in oxidation behavior determined experimentally through scale thickness and their mass changes. The insights on oxidation behavior presented in this work will enable the fast assessment of technologically useful HEAs needed for future structural application in extreme conditions

36 MATERIALS SCIENCE↗

Modeling diurnal and annual ethylene generation from solar-driven electrochemical CO 2 reduction devices

Integrated solar fuels devices for CO 2 reduction (CO 2 R) are a promising technology class towards reducing carbon emissions. Designing integrated CO 2 R solar fuels devices requires careful co-design of electrochemical and photovoltaic components as well as consideration of the diurnal and seasonal effects of solar irradiance, temperature, and other meteorological factors expected for ‘on-sun’ deployment. Using a photovoltaic-electrochemical (PV-EC) platform, we developed a temperature and potential-dependent diurnal and annual model using experimentally-determined CO 2 R performance of Cu-based electrocatalysts, local meteorological data from the National Solar Radiation Database (NSRD), and modeled performance of commercial c-Si PVs. Here we simulated gaseous diurnal product outputs with and without the effects of ambient temperature. From these outputs, we observed seasonal variation in gaseous product generation, with up to two-fold increases in ethylene productivity between the Winter and Summer, analyzed the consequences of dynamic cloud coverage, and identified periods where device cooling/heating mechanisms could be implemented to maximize ethylene generation. Finally, we modeled the annual ethylene generation for a scaled 1 MW solar farm at three different locations (Beijing, CN; Sydney, AUS; Barstow, CA) to determine the consequences of local meteorological climates on PV-EC CO 2 R product output, recording a maximum ethylene output of 18.5 tonne per year at Barstow. Overall, this model presents a critical tool for streamlining the translation of experimental solar-driven electrochemical research to real-world implementation.

14 SOLAR ENERGY↗

Semi-analytical covariance matrices for two-point correlation function for DESI 2024 data

We present an optimized way of producing the fast semi-analytical covariance matrices for the Legendre moments of the two-point correlation function, taking into account survey geometry and mimicking the non-Gaussian effects. We validate the approach on simulated (mock) catalogs for different galaxy types, representative of the Dark Energy Spectroscopic Instrument (DESI) Data Release 1, used in 2024 analyses. We find only a few percent differences between the mock sample covariance matrix and our results, which can be expected given the approximate nature of the mocks, although we do identify discrepancies between the shot-noise properties of the DESI fiber assignment algorithm and the faster approximation (emulator) used in the mocks. Importantly, we find a close agreement (≤ 8% relative differences) in the projected errorbars for distance scale parameters for the baryon acoustic oscillation measurements. This confirms our method as an attractive alternative to simulation-based covariance matrices, especially for non-standard models or galaxy sample selections, making it particularly relevant to the broad current and future analyses of DESI data.

79 ASTRONOMY AND ASTROPHYSICS↗

Universality of scaled particle spectra in ultrarelativistic heavy-ion collisions

We study the transverse momentum spectra of identified particles in ultrarelativistic collisions of large and small collision systems. In order to isolate information contained in the momentum dependence, we propose to scale the spectra by the total particle number and mean transverse momentum, global quantities which are already well studied. We observe an interesting, nearly universal, centrality-independent shape in the scaled spectra, similar to scalings that have been studied previously. This scaling behavior breaks down at large transverse momentum and for very small systems, such as those produced in p − p collisions. We perform hybrid hydrodynamic simulations and show that, in these simulations, a centrality-independent shape is a consequence of an event-by-event independence. Here, our results motivate further theoretical and experimental investigations of the regime of validity of this scaling phenomenon and their physical interpretation at different collision energies and systems.

Collective flow↗

Precision gyroscope from the helicity of light

We describe a gyroscope that measures rotation based on the effects of the rotation on the polarization of light. Rotation induces a differential phase shift in the propagation of left- and right-circularly polarized light and this phase shift can be measured in suitably designed interferometric setups. The signal in this setup is independent of the frequency of light, unlike various sources of noise such as vibrations, which cause phase shifts that depend on the frequency. Such vibrations are the practical limit on the sensitivity of conventional Sagnac-style optical interferometers that are typically used as gyroscopes. In the proposed setup, one can potentially mitigate this source of noise by simultaneously using two (or more) sources of light that have different frequencies. The signal in this setup scales with the total storage time of the light. Due to its frequency independence, it is thus most optimal to measure the signal using superconducting radio-frequency systems where the high finesse of the available cavities enables considerably longer storage times than is possible in an optical setup.

47 OTHER INSTRUMENTATION↗