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At least 775 records · Page 43

Formulation and solution approach for calibrating activity-based travel demand model-system via microsimulation

This study addresses the problem of calibrating utility-maximizing nested logit activity-based travel demand model-systems. After estimation, it is common practice to use aggregate measurements to calibrate the estimated model-system’s parameters prior to their application in transportation planning, policy making, and operations. However, calibration of activity-based model-systems has received much less attention. Existing calibration approaches are myopic heuristics in the sense that they do not consider the fundamental inter-dependencies among choice-models and do not have a systematic way to adjust model parameters. Also, other purely simulation-based approaches do not perform well in large-scale applications. In this study, we focus on utility-maximizing nested logit activity-based model-systems and calibrating aggregate statistics such as activity shares, mode shares, time-dependent & mode-specific OD flows, and time-dependent & mode-specific sensor counts. We formulate the calibration problem as a simulation-based optimization problem and propose a stochastic gradient-based solution procedure to solve it. The solution procedure relies on microsimulation to calculate expectations of the aggregate statistics of interest to the calibration problem. Additionally, we derive approximate analytical expressions for the gradient of the objective function —that are evaluated through microsimulation on mini-batches of the population. The proposed solution procedure is sensitive to the fundamental structure of the activity-based model-system and is non-myopic in considering the dependencies across its model components. The formulated optimization problem is non-convex, highly nonlinear, and potentially has multiple-minima. Lastly, we show —through a real-world application— that the proposed solution procedure outperforms other state-of-the-art purely simulation-based optimization approaches in terms of computational efficiency, stability, and convergence. We also compare various gradient-based solution algorithms to determine the best algorithm to update the parameters. This work has the potential to facilitate wider and easier application of activity-based model-systems.

97 MATHEMATICS AND COMPUTING↗

Solvent Selection for the Separation of Lignin-Derived Monomers Using the Conductor-like Screening Model for Real Solvents

The separation of desired monomers from a liquid-phase mixture of lignin depolymerization products is necessary to facilitate their upscaling and upgrading for industrial applications. One effective method to separate multiple liquid-phase products is countercurrent chromatography (CCC), which is a common liquid chromatography technique that separates target solutes based on differences in their partitioning in a biphasic solvent system. Effective CCC separation requires the selection of solvent compositions to tune solute partition coefficients. Here, to alleviate the experimental burden of selecting optimal solvent systems, we apply the conductor-like screening model for real solvents (COSMO-RS) method to compute partition coefficients of representative lignin monomers from four currently used depolymerization strategies in standard solvent systems. We further design new ternary and quaternary solvent systems that are predicted to further improve separation efficacy. On the basis of these predicted partition coefficients and empirical solvent selection criteria for CCC measurements, we suggest a range of solvent systems that would be suitable for the effective separation of aromatic lignin-derived products via CCC or similar liquid–liquid extraction methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Integration of Online Cross-Section Generation Capability with Depletion and Transient Solvers in Griffin

Griffin is a Multiphysics Object-Oriented Simulation Environment (MOOSE)-based reactor multiphysics analysis application jointly developed by Argonne and Idaho National Laboratories under the DOENE Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. In FY25, an online crosssection generation capability based on the Self-Shielding Application Programming Interface (SSAPI) was demonstrated for TRISO-fueled reactor problems under steady-state conditions. This fiscal year, that capability was extended to support depletion and transient multiphysics calculations, enabling high-fidelity analyses that generate self-shielded cross sections on the fly from the actual evolving composition and temperature states rather than from pre-tabulated libraries. For depletion, a two-way coupling was established in which SSAPI computes compact-averaged self-shielded cross sections that the depletion solver then uses to advance the Bateman equations, with the updated compositions returned to SSAPI at each step; the depletion module was refactored to support both library-based and SSAPI-based cross sections, and additional logic was added to track daughter isotopes and to exclude minor isotopes for efficiency. For transient analysis, the SSAPI multigroup library was extended with the kinetics data required for time-dependent calculations, the Improved Quasi-Static (IQS) scheme was coupled with SSAPI, and several supporting capabilities were implemented, including a self-shielding treatment that lets control rods and drums move within a self-shielded model, which had previously been impossible and had ruled out rod- and drum-movement transients with on-the-fly cross sections altogether, a new mixing scheme for delayed-neutron precursor decay constants, a checkpoint-based restart workflow, and performance improvements such as pointwise cross-section interpolation and the bypassing of unnecessary Dancoff factor calculations. The implemented capabilities were verified against Serpent Monte Carlo solutions. For depletion, a prismatic pin-cell problem based on a Next Generation Nuclear Plant (NGNP) Very High Temperature Reactor benchmark showed excellent agreement, with eigenvalue differences within 200 pcm over the entire burnup range (up to 140 MWD/kgU) and fission-product and actinide inventories agreeing to within 0.8% and 2.5%, respectively; a heat-pipe microreactor assembly problem with a much higher fuel loading confirmed the same behavior and quantified the bias introduced when the multigroup equivalence effect is neglected. For transient analysis, a pin-cell problem with a step reactivity insertion and temperature feedback reproduced the analytically expected asymptotic power and showed close agreement between the direct and IQS solutions, and a two-dimensional microreactor core problem with control-drum rotation exercised the new moving-drum self-shielding treatment and demonstrated successful coupling of the online crosssection generation with both the direct and IQS transient methods. The capability was further exercised on a full-core pebble-bed problem, in which Griffin was coupled with the System Analysis Module (SAM) to simulate load-following operation of the gPBR with the Doppler feedback resolved at the TRISO fuel kernel temperature. These developments in Griffin provide a convenient, high-fidelity approach to cross-section generation for advanced thermal reactors with geometrically complex and highly heterogeneous configurations, including TRISO-fueled prismatic and pebble-bed systems, and support steady-state, depletion, and transient multiphysics calculations. They also enable self-shielded cross sections to be evaluated directly at the actual coupled state of the system, thereby establishing a foundation for high-fidelity, fully coupled multiphysics analysis of advanced reactors

Park, H.↗

Universal Approach to Fabricating Graphene-Supported Single-Atom Catalysts from Doped ZnO Solid Solutions

Single-atom catalysts (SACs) have attracted widespread interest for many catalytic applications because of their distinguishing properties. However, general and scalable synthesis of efficient SACs remains significantly challenging, which limits their applications. Here we report an efficient and universal approach to fabricating a series of high-content metal atoms anchored into hollow nitrogen-doped graphene frameworks (M-N-Grs; M represents Fe, Co, Ni, Cu, etc.) at gram-scale. The highly compatible doped ZnO templates, acting as the dispersants of targeted metal heteroatoms, can react with the incoming gaseous organic ligands to form doped metal-organic framework thin shells, whose composition determines the heteroatom species and contents in M-N-Grs. We achieved over 1.2 atom % (5.85 wt %) metal loading content, superior oxygen reduction activity over commercial Pt/C catalyst, and a very high diffusion-limiting current (6.82 mA cm -2 ). Both experimental analyses and theoretical calculations reveal the oxygen reduction activity sequence of M-N-Grs. Additionally, the superior performance in Fe-N-Gr is mainly attributed to its unique electron structure, rich exposed active sites, and robust hollow framework: This synthesis strategy will stimulate the rapid development of SACs for diverse energy-related fields.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Quantifying the Relevance of Long-Range Forces for Crystal Nucleation in Water

Understanding nucleation from aqueous solutions is of fundamental importance in a multitude of fields, ranging from materials science to biophysics. The complex solvent-mediated interactions in aqueous solutions hamper the development of a simple physical picture, elucidating the roles of different interactions in nucleation processes. In this study, we make use of three complementary techniques to disentangle the role played by short- and long-range interactions in solvent-mediated nucleation. Specifically, the first approach we utilize is the local molecular field (LMF) theory to renormalize long-range Coulomb electrostatics. Second, we use well-tempered metadynamics to speed up rare events governed by short-range interactions. Third, the deep learning-based State Predictive Information Bottleneck approach is employed in analyzing the reaction coordinate of the nucleation processes obtained from the LMF treatment coupled with well-tempered metadynamics. We find that the two-step nucleation mechanism can largely be captured by the short-range interactions, while the long-range interactions further contribute to the stability of the primary crystal state under ambient conditions. Furthermore, by analyzing the reaction coordinate obtained from the combined LMF-metadynamics treatment, we discern the fluctuations on different time scales, highlighting the need for long-range interactions when accounting for metastability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Analyses of circular solutions for advanced plastics waste recycling

A circular plastics economy can leverage the lightweight, strong and durable characteristics of macromolecular materials, while simultaneously reducing the negative environmental impacts associated with polymer waste. Advanced recycling technologies provide an opportunity to valorize plastics waste and extend the lifespan of these materials by converting waste into new monomers, polymers or specialty chemicals. Although many advanced technologies appear promising, assessments of economic and environmental sustainability are often not conducted in a standardized fashion and neglect factors such as plastics waste transportation, sorting and pretreatment. These shortcomings can lead to inaccurate or misleading predictions, reduce opportunities for optimization and limit industrial relevance. In this Review, we highlight select industrial case studies to underscore the notable consequences of underestimating the complexity of real-life consumer plastics waste. In addition, the current challenges associated with the assessment of the industrial viability of laboratory-scale processes are explored. Here, by discussing relevant analysis frameworks and system boundaries, along with potential analytical pitfalls, future research will be guided beyond chemical considerations and toward impactful circular solutions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Determination of Intermolecular Distances in Dilute Solutions of Macroions and Their Direct Correlations with Self-Assembly and Macrophase Transitions

Here, this work demonstrates new attempts to determine the intermolecular distances between charged macroionic solutes in their dilute solutions, which regulate the solute’s microphase (self-assembly) and macrophase transitions. Small-angle X-ray scattering (SAXS) and analytical ultracentrifuge (AUC) techniques were applied to determine the intermolecular distances for the 2.42 nm-sized, spherical uranyl peroxide molecular cluster {U 60 } in their self-assembled states in dilute aqueous solution and concentrated phases, respectively. The counterion-mediated attraction among {U 60 } leads to characteristic, inter-{U 60 } distances in solutions, which increase gradually with decreasing the strength of introduced counterions (e.g., lower valency). The gradual increment of inter-{U 60 } distance demonstrates a nice correlation with the macroscopic phase transitions of {U 60 }, from single crystals to concentrated fluids containing rigid 2-D sheets, then to dilute solutions containing a small amount of standalone, floating 2-D sheets of {U 60 }, and finally to dilute solutions containing a limited amount of self-assembled single-layered, spherical blackberry structures of different sizes from the bending of more flexible 2-D sheets.

36 MATERIALS SCIENCE↗

Diazirine-based photo-crosslinkers for defect free fabrication of solution processed organic light-emitting diodes

The fabrication of solution deposited OLEDs is fraught with difficulties, largely due to the interlayer mixing and surface erosion during sequential deposition of the layers. We demonstrate that these problems can be circumvented by using photopolymerizable diazirine-based cross-linker capable of converting soluble organic materials into highly cross-linked insoluble networks. 3-Trifluoromethyl(aryl)diazirines photolyze readily upon the 10–15 min exposure of 365 nm UV irradiation to generate carbenes, which react with polymers or small molecules via C–H bond insertion producing highly cross-linked materials. This photo-generated cross-linking does not require any catalyst, initiator or short-wavelength UV light and is performed at room temperature, releasing molecular nitrogen as the only byproduct. To show the cross-linked polymer layers do not display inter-layer mixing, we deposited red-emitting regioregular poly(3-hexylthiophene-2,5-diyl) (P3HT) over cross-linked (10% cross-linker) blue emitting dioctyl polyfluorene (PFO) layer. The overlaid layers showed clear and well-defined boundary with no interlayer mixing. The surface morphology of the solution deposited layers was investigated by AFM to show that the cross-linked layers exhibited significant decrease in surface roughness. This is also shown on the example of the hole transporting material 4,4'-bis[N-(1-naphthyl)-N-phenylamino]-biphenyl (NPB) which displayed roughness average to decrease from 6.4 nm to 1.0 nm. The effect of decreased surface roughness on the performance of phosphorescent OLEDs was investigated by fabricating devices with configuration of ITO/PEDOT:PSS/NPB:(0%/5%/10%) cross-linker/MCP:6% Ir(mppy) 3 /TPBI/CsF/Al. Furthermore, following the diazirine-mediated cross-linking, the OLEDs displayed a decrease in turn-on voltage from 3.8 V to 3.0 V along with a six-fold enhancement of external quantum efficiency (EQE max ) from 1.1% to 6.8% and maximum luminous efficiency increase from 3.8 cd A -1 to 22.9 cd A -1 . These results demonstrate that the simple diazirine mediated photo-cross-linking using mild conditions compatible with organic layers is a promising strategy for improving the performance of the solution-processed OLEDs.

36 MATERIALS SCIENCE↗

Mathematical solutions in internal dose assessment: A comparison of Python-based differential equation solvers in biokinetic modeling

Abstract In biokinetic modeling systems employed for radiation protection, biological retention and excretion have been modeled as a series of discretized compartments representing the organs and tissues of the human body. Fractional retention and excretion in these organ and tissue systems have been mathematically governed by a series of coupled first-order ordinary differential equations (ODEs). The coupled ODE systems comprising the biokinetic models are usually stiff due to the severe difference between rapid and slow transfers between compartments. In this study, the capabilities of solving a complex coupled system of ODEs for biokinetic modeling were evaluated by comparing different Python programming language solvers and solving methods with the motivation of establishing a framework that enables multi-level analysis. The stability of the solvers was analyzed to select the best performers for solving the biokinetic problems. A Python-based linear algebraic method was also explored to examine how the numerical methods deviated from an analytical or semi-analytical method. Results demonstrated that customized implicit methods resulted in an enhanced stable solution for the inhaled 60 Co (Type M) and 131 I (Type F) exposure scenarios for the inhalation pathway of the International Commission on Radiological Protection (ICRP) Publication 130 Human Respiratory Tract Model (HRTM). The customized implementation of the Python-based implicit solvers resulted in approximately consistent solutions with the Python-based matrix exponential method ( expm ). The differences generally observed between the implicit solvers and expm are attributable to numerical precision and the order of numerical approximation of the numerical solvers. This study provides the first analysis of a list of Python ODE solvers and methods by comparing their usage for solving biokinetic models using the ICRP Publication 130 HRTM and provides a framework for the selection of the most appropriate ODE solvers and methods in Python language to implement for modeling the distribution of internal radioactivity.

61 RADIATION PROTECTION AND DOSIMETRY↗

Simplified Universal Equations for Ionic Conductivity and Transference Number

Nernst-Einstein equation can provide a reasonable estimate of the ionic conductivity of dilute solutions. For concentrated solutions, alternate methods such as Green–Kubo relations and Einstein relations are more suitable to account for ion-ion interactions. Such computations can be expensive for multicomponent systems. Simplified mathematical expressions like the Nernst-Einstein equation do not exist for concentrated multicomponent mixtures. Newman’s treatment of multicomponent concentrated solutions yields a conductivity relation in terms of species concentration and Onsager phenomenological coefficients. However, the estimation of these phenomenological coefficients is not straightforward. Here, mathematical formulations that relate the phenomenological coefficients with the friction coefficients are developed, leading to simplified, ready-to-use expressions of conductivity and transference numbers that can be used for a wide range of ionic mixtures. This approach involves spectral decomposition of the matrix of Onsager phenomenological coefficients. The general analytical expressions for conductivity and transference number are simplified for binary electrolytes, and numerical solutions are provided for ternary and quaternary mixtures with ion dissociation.

Electrochemistry↗

Low-cost sensors and analytics for a digital factory

ORNL Manufacturing Demonstration Facility and Perisense worked on a low-cost solution for machining process monitoring to enable a digital factory. Enabling machine connectivity for digital factors is expensive for many small to medium manufacturers. The hypothesis for the research project is that a lowcost sensor suite, which can be retrofitted to a legacy machine tool or a new machine tool, can effectively provide real-time, in-situ sensing for manufacturing processes, which can enable improvements in process performance and efficiency. The Perisense sensor node was installed on the Haas TM1 machine with a current sensor and an accelerometer. Cutting tests were performed at different process parameters and sensor data was recorded. Results show a correlation of the current sensor to the spindle load. The accelerometer, mounted on the machine base, showed a correlation to the spindle speed as well as the spindle load. The sensor data can be used to monitor the machining process and provide insights on the machine spindle load utilization.

42 ENGINEERING↗

High salinity seawater boiling point elevation: Experimental verification

Boiling point elevation (BPE) for high salinity solutions is a crucial parameter that significantly affects the overall thermal efficiency of desalination, water treatment, and many other industrial processing systems, especially when minimum or zero liquid discharge is a key requirement. This paper addresses the discrepancies among the empirical correlations reported in the literature that were commonly used to determine BPE for seawater solutions. An evaluation of the experimental data with low solution concentration reveals that the data cannot be extrapolated to determine the BPE at high concentration (X > 140 ppt or g/kg). Besides, disparities are established within different equations used to determine the BPE for high salinity seawater. As a result of the minimal availability of experimental data of BPE for X > 140 ppt and the need to eliminate the discrepancies, an experimental setup was built, which can produce reliable and repeatable BPE data for any solution concentration. Boiling points were obtained experimentally for seawater solutions with a wide range of salinity (X between 20 and 280 ppt) and brine solution temperature (t b between 20 and 80°C). The experimental results of boiling point elevations for seawater are further compared with the experimental data and analytical results reported in the literature. The newly obtained experimental results show that the minimum and maximum BPE values for the brine solutions tested are 0.175°C at t b = 80°C and X = 20 ppt, and 11.6°C at t b = 80°C and X = 280 ppt, respectively. Furthermore, the measured BPE data for seawater concentration over 80 ppt are fitted and presented using an appropriate fitting model. The new correlation can accurately predict the BPE for high salinity seawater brines and thus should be very helpful in the design of high-energy-efficient evaporation systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Data-driven simultaneous process optimization and adsorbent selection for vacuum pressure swing adsorption

Technologies for post-combustion carbon capture are essential for the reduction of greenhouse gas emissions to the atmosphere. However, they are still associated with high costs and energy consumption. Intensified processes for carbon capture have the potential to overcome these challenges due to their higher efficiency, lower capital cost, and increased operational flexibility. Here, this work investigates simultaneous optimization of process conditions and adsorbent selection for a modular Vacuum Pressure-Swing Adsorption system designed for CO 2 capture. Both surrogate-based Nonlinear Programming and Mixed-Integer Nonlinear Programming approaches are applied and compared in terms of computational efficiency and solution accuracy. Moreover, process performance results are examined by applying several data analytics techniques to gain insights into the material-process correlations. Data-driven classifiers and neural networks can accurately predict whether a material is likely to satisfy purity, recovery, and energy constraints when operated at optimal process conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Molecular dynamics and continuum analyses of the electrokinetic zeta potential in nanostructured slit channels

This work presents a theoretical and numerical study of electrokinetic flow and the zeta potential for the case of slit channels with nanoscale surface features of dimensions comparable to the Debye length, by employing molecular dynamics simulations and continuum-level analyses. Additionally, a simple analytical model for considering the average effect of such surface features producing nanoscale roughness is proposed by employing matched asymptotic solutions for the charge density and fluid flow field, and matching conditions that satisfy electroneutrality and the Onsager reciprocal relation between the electroosmotic flow rate and streaming current. The proposed analytical model quantitatively accounts for results from molecular dynamics simulations that consider the presence of ion solvation shells and surface hydration layers. Our analysis indicates that a simultaneous knowledge of the electroosmotic and pressure-driven flow rate or streaming current can be instrumental to unambiguously determine the zeta potential in the presence of nanoscale surface features.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Water and salt transport properties of pentiptycene-containing sulfonated polysulfones for desalination membrane applications

A series of pentiptycene-containing disulfonated polysulfone copolymers (PENT-BP) were synthesized via condensation polymerization. Water and salt transport properties (solubility, diffusivity and permeability) were characterized for acid-form membranes (PENT-BP(H)) and compared with triptycene-based sulfonated polysulfones (TRP-BP(H)) and a non-iptycene-containing 4,4'-biphenol-based series (BPS(H)) of polysulfones to investigate the effect of pentiptycene on membrane performance. At comparable water content, the PENT-BP(H) exhibited increased water and salt permeability due to the additional free volume introduced by the pentiptycene units. Enhanced water/salt permeability selectivity of PENT-BP(H) series was also observed due to a significantly higher diffusivity selectivity. At comparable water permeance (P w D ~ 8 X 10 -6 cm 2 /s), the salt rejection of PENT-BP (H) copolymers obtained from dead-end filtration reached 91–93% at 400 psi, higher than that of a corresponding BPS(H) series. This study suggests that incorporation of iptycene moieties into polymer backbone is an effective strategy to enhance desalination membrane performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Expanding the Cage of 2D Bromide Perovskites by Large A-Site Cations

Two-dimensional (2D) halide perovskites have outstanding optoelectronic properties, and they feature a variety of organic cation spacers and cage A-site cations that can be incorporated into their structures. It has recently been reported that the Goldschmidt tolerance factor can be relaxed and expanded in iodide 2D perovskites. Bromide 2D perovskites, whose multilayer structures and optical properties are much less studied, provide a great platform for studying structure-property relationships for 2D perovskites with large Asite cations. Herein, we report the synthesis and structure of three new 2D bromide perovskites-(BA)(2)(MHy)(2)Pb3Br10 (BA, butylammonium; MHy, methylhydrazinium), (BA)(2)(EA)(2)Pb3Br10 (EA is ethylammonium), and (BA)(2)(DMA)Pb2Br7 (DMA is dimethylammonium). We compared them with other 2D perovskites with different A-site cations but with the same spacer and layer thickness. Single-crystal structures show that the Pb-Br bonds are elongated to accommodate the large A-site cations. Additionally, the octahedra in (BA)(2)(MHy)(2)Pb3Br10 and (BA)(2)(EA)(2)Pb3Br10 are highly distorted, and their different stacking patterns of the inner and outer layers lead to the formation of the n = 3 phases. Density functional theory calculations show that 2D perovskites with larger A-site cations (e.g., DMA, MHy, and EA) have smaller band dispersions and larger effective masses than those with Cs+ and MA. (BA)(2)(MHy)(2)Pb3Br10 also exhibits one of the largest Rashba splittings in the literature. Structures with large cage cations also exhibit high band gaps within the same n number and short photoluminescence (PL) lifetimes. Temperature- and power-dependent PL measurements reveal that the broad shoulder in the PL peak originates from the trap states.

Emission↗