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At least 469 records · Page 26

Chemomechanics in alloy phase stability

We describe a first-principles statistical mechanics method to calculate the free energies of crystalline alloys that depend on temperature, composition, and strain. The approach relies on an extension of the alloy cluster expansion to include an explicit dependence on homogeneous strain in addition to site occupation variables that track the degree of chemical ordering. The method is applied to the Si-Ge binary alloy and is used to calculate free energies that describe phase stability under arbitrary epitaxial constraints. We find that while the incoherent phase diagram (in which coexisting phases are not affected by coherency constraints) hosts a miscibility gap, coherent phase equilibrium predicts ordering and negative enthalpies of mixing. Instead of chemical instability, the chemomechanical free energy exhibits instabilities along directions that couple the composition of the alloy with a volumetric strain order parameter. Furthermore, this has fundamental implications for phase field models of spinodal decomposition as it indicates the importance of gradient energy coefficients that couple gradients in composition with gradients in strain.

Materials Science↗

Spectral Analysis of Regular Material Point Method and its Application to Study High Pressure Reverse Osmosis Membrane Compaction and Embossing

Material Point Method (MPM) is gaining widespread interest in applied continuum mechanics. The fact that all the continuum properties are stored on the particles (or material points) and the governing equations are solved on these material points makes MPM extremely suited to problems involving severe material deformations, such as crack propagation, soil movement, and fluid flows. Despite its popularity, only a few studies have focused on the numerical properties of MPM. This presentation introduces a global spectral analysis of the regular material point method. Contrary to previous studies, the analysis focuses on the numerical properties of the method in the spectral space. The amplification factor is derived as a function of the non- dimensional wave numbers. It provides insights into the stability and dissipative properties of the method for various CFL and Fourier numbers. The effect of the grid shape functions, number of particles per cell and their locations inside the grid cell are also analyzed. The EXAGOOP MPM solver (https://github.com/NREL/Exagoop.git) is developed at the National Renewable Energy Laboratory as a part of the NAWI UHPRO project and is based on the AMReX framework. A single-level, uniform cartesian grid is used as the background mesh, while the particle class in AMReX is used to manage the material point operations. Linear hat and B-splines are used as grid shape functions, while the time integration is performed using explicit Euler time integration. EXAGOOP is both CPU and GPU compatible and has been demonstrated to work well on multiple compute architectures. The performance of EXAGOOP on various computing architectures is presented along with its application to study compaction and embossing of high-pressure reverse osmosis membranes. The MPM solution accurately reproduces the membrane deformation. The deformed pore size and structure simulated using MPM also agree well with experimental SEM images.

material point method↗

A first principles study of energetics and electronic structural responses of uranium-based coordination polymers to Np incorporation

Abstract Recently developed coordination polymers (CPs) and metal organic frameworks (MOFs) may find applications in areas such as catalysis, hydrogen storage, and heavy metal immobilization. Research on the potential application of actinide-based CPs (An-CP/MOFs) is not as advanced as transition metal-based MOFs. In order to modify their structures necessary for optimizing thermodynamic and electronic properties, here, we described how a specific topology of a particular actinide-based CP or MOF responds to the incorporation of other actinides considering their diverse coordination chemistry associated with the multiple valence states and charge-balancing mechanisms. In this study, we apply a recently developed DFT-based method to determine the relative stability of transuranium incorporated CPs in comparison to their uranium counterpart considering both solid and aqueous state sources and sinks to understand the mechanism and energetics of charge-balanced Np 5+ incorporation into three uranium-based CPs. The calculated Np 5+ +H + incorporation energies for these CPs range from 0.33 to 0.52 eV, depending on the organic linker, when using the solid oxide Np source Np 2 O 5 and U sink UO 3 . Incorporation energies of these CPs using aqueous sources and sinks increase to 2.85–3.14 eV. The thermodynamic and structural analysis in this study aides in determining, why certain MOF topologies and ligands are selective for some actinides and not for others. This means that once this method is extended across a variety of CPs with their respective linker molecules and different actinides, it can be used to identify certain CPs with certain organic ligands being specific for certain actinides. This information can be used to construct CPs for actinide separation. This is the first determination of the electronic structure (band structure, density of states) of these uranium- and transuranium-based CPs which may eventually lead to design CPs with certain optical or catalytic properties. While the reduction of the DFT-determined-bandgap goes from 3.1 eV to 2.4 eV when going from CP1 to CP3, showing the influence of the linker, Np 6+ incorporation reduces the bandgap for CP1 and CP3, while increasing it for CP2. The coupled substitution of U 6+ →Np 5+ +H + reduces the bandgap significantly, but only for CP3.

Chemistry↗

Learning Constrained Parametric Differentiable Predictive Control Policies With Guarantees

We present differentiable predictive control (DPC), a method for offline learning of constrained neural control policies for nonlinear dynamical systems with performance guarantees. We show that the sensitivities of the parametric optimal control problem can be used to obtain direct policy gradients. Specifically, we employ automatic differentiation (AD) to efficiently compute the sensitivities of the model predictive control (MPC) objective function and constraints penalties. To guarantee safety upon deployment, we derive probabilistic guarantees on closed-loop stability and constraint satisfaction based on indicator functions and Hoeffding’s inequality. We empirically demonstrate that the proposed method can learn neural control policies for various parametric optimal control tasks. In particular, we show that the proposed DPC method can stabilize systems with unstable dynamics, track time-varying references, and satisfy nonlinear state and input constraints. Our DPC method has practical time savings compared to alternative approaches for fast and memory-efficient controller design. Specifically, DPC does not depend on a supervisory controller as opposed to approximate MPC based on imitation learning. We demonstrate that, without losing performance, DPC is scalable with greatly reduced demands on memory and computation compared to implicit and explicit MPC while being more sample efficient than model-free reinforcement learning (RL) algorithms.

97 MATHEMATICS AND COMPUTING↗

Unconventional route to dual-shelled organolead halide perovskite nanocrystals with controlled dimensions, surface chemistry, and stabilities

The past few years have witnessed rapid advances in the synthesis of high-quality perovskite nanocrystals (PNCs). However, despite the impressive developments, the stability of PNCs remains a substantial challenge. The ability to reliably improve stability of PNCs while retaining their individual nanometer size represents a critical step that underpins future advances in optoelectronic applications. Here, we report an unconventional strategy for crafting dual-shelled PNCs (i.e., polymer-ligated perovskite/SiO 2 core/shell NCs) with exquisite control over dimensions, surface chemistry, and stabilities. In stark contrast to conventional methods, our strategy relies on capitalizing on judiciously designed star-like copolymers as nanoreactors to render the growth of core/shell NCs with controlled yet tunable perovskite core diameter, SiO 2 shell thickness, and surface chemistry. Consequently, the resulting polymer-tethered perovskite/SiO 2 core/shell NCs display concurrently a stellar set of substantially improved stabilities (i.e., colloidal stability, chemical composition stability, photostability, water stability), while having appealing solution processability, which are unattainable by conventional methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Structural, Electronic, and Photophysical Insights into a Few Atom Copper-Sulfur Cluster in the Solid and Solution States

Coinage-metal chalcogenide clusters are widely studied for their attractive photoluminescence properties. Copper chalcogenides are especially promising, but are often confined to solid-state investigations due to their limited solution stability and the difficulty of synthesizing stable, well-defined clusters. Here, we investigate copper–sulfur clusters incorporating a small number of Cu atoms to elucidate fundamental atomic interactions, ground- and excited-state characteristics, and photophysical behavior in both solid and solution. We have synthesized the Cu6(4,6-dimethyl-2-mercaptopyrimidine)6 cluster in both neutral and charged states, Cu6 and Cu6-2H2+, respectively, by selective ligand protonation. The molecular structures are determined using single-crystal X-ray diffraction, while Cu K-edge X-ray absorption spectroscopy is used to probe Cu electronic structure differences arising from the ligand modification. Steady-state and pump-probe optical spectroscopy is used to investigate photophysical properties, interpreted using density functional theory methods. Both clusters exhibit good stability in the solid state and in solution and show characteristic near-infrared emission with microsecond lifetimes. Overall, the Cu6S6 clusters display favorable charge–transfer characteristics and show potential for further use in driving photochemical transformations.

Copper-sulfur clusters↗

Deep Learning Based Frequency Stability Assessment in Power Grid with High Renewables

Frequency stability assessment is one critical aspect of power system security assessment. Traditional N-1 screening method is based on the simulations of a few typical daily and seasonal operation scenarios. However, the increasing integration of inverter-based renewables and the retirement of conventional synchronous generators result in decreasing system inertia and growing complexity of system operating conditions. Selecting a few typical operation scenarios cannot cover all operating conditions, and the time-domain simulation of all operation conditions requires tremendous time. This paper proposes a more efficient frequency stability assessment method based on deep learning. The affinity propagation clustering algorithm is used to divide the dataset into different clusters, so the selected dataset for training can cover the diversified operating conditions as much as possible. Also, feature normalization is applied to both the training dataset and testing dataset in order to remove any unnecessary bias. Especially, trained model based on full dataset normalization has bounded error in the prediction. The case study on the reduced 240-bus WECC system demonstrates that the proposed method can predict accurate frequency nadir with limited training dataset. The deep learning model using the revised feature normalization can predict more accurate frequency nadir than that using the traditional feature normalization and has very small maximum prediction error.

affinity propagation↗

Carrier-envelope phase stabilization of an Er:Yb:glass laser via a feed-forward technique

Few-cycle pulsed laser technology highlights the need for control and stabilization of the carrier-envelope phase (CEP) for applications requiring shot-to-shot timing and phase consistency. This general requirement has been achieved successfully in a number of free–space and fiber lasers via feedback and feed-forward (FF) methods. Here, expanding on existing results, we demonstrate CEP stabilization through the FF method applied to a SESAM mode-locked Er:Yb:glass laser at 1.55 μm with a measured ultralow timing jitter of 2.9 as (1–3 MHz) and long-term stabilization over a duration of 8 h. Single-digit attosecond stabilization at telecom wavelengths opens a new direction in applications requiring ultra-stable frequency and time precision such as high-resolution spectroscopy and fiber timing networks.

47 OTHER INSTRUMENTATION↗

One-Step Facile Synthesis of High-Activity Nitrogen-Doped PtNiN Oxygen Reduction Catalyst

PtM alloy electrocatalysts (M = Fe, Co, Ni) have been the subject of many investigations aimed at increasing their attractive properties, in particular oxygen reduction reaction (ORR) activity, while reducing total platinum-group-metal content and improving durability. Despite some success, these catalysts still have relatively high Pt content and lack the necessary durability as M metals leach out from the alloys during potential cycling. Previously, we synthesized nitrogen (N)-doped PtMN/C catalysts consisting of thin Pt shells on M nitride cores by a two-step method, which showed higher ORR activity and stability than their PtM counterparts. In the present work, we developed a facile one-step synthesis method, which comprises a single thermal annealing process of the N-doped PtNiN/C alloy. The ORR performance of the one-step synthesized PtNiN/C catalyst is much higher than that of the two-step synthesized PtNiN/C, as revealed by rotating disk electrode measurements. Membrane electrode assembly fuel cell testing demonstrated superb durability and high activity. Formation of Pt monolayer shells on the nitrided (Pt x Ni 1-x ) 4 N cores was confirmed by in situ X-ray absorption spectroscopy. The origins of the enhanced activity and stability of the one-step synthesized PtNiN/C catalyst are elucidated based on density functional theory calculations together with the experimental results.

30 DIRECT ENERGY CONVERSION↗

A new method to retrieve the diurnal variability of planetary boundary layer height from lidar under different thermodynamic stability conditions

The planetary boundary layer height (PBLH) is an important parameter for understanding the accumulation of pollutants and the dynamics of the lower atmosphere. Lidar has been used for tracking the evolution of PBLH by using aerosol backscatter as a tracer, assuming aerosol is generally well-mixed in the PBL; however, the validity of this assumption actually varies with atmospheric stability. This is demonstrated here for stable boundary layers (SBL), neutral boundary layers (NBL), and convective boundary layers (CBL) using an 8-year dataset of micropulse lidar (MPL) and radiosonde (RS) measurements at the ARM Southern Great Plains, and MPL at the GSFC site. Due to weak thermal convection and complex aerosol stratification, traditional gradient and wavelet methods can have difficulty capturing the diurnal PBLH variations in the morning and forenoon, as well as under stable conditions generally. Here a new method is developed that combines lidar-measured aerosol backscatter with a stability dependent model of PBLH temporal variation (DTDS). The latter helps “recalibrate” the PBLH in the presence of a residual aerosol layer that does not change in harmony with PBL diurnal variation. The hybrid method offers significantly improved PBLH detection, with better correlation and smaller biases, under most thermodynamic conditions, especially for SBL and CBL. Relying on the physical process of PBL diurnal development, different schemes are developed for growing, maintenance, and decaying periods. Comprehensive evaluation of this new method shows much better tracking of diurnal PBLH variation and significantly smaller biases under various pollution levels.

54 ENVIRONMENTAL SCIENCES↗

High-accuracy method for modeling nucleation and growth of particles

State-of-the-art numerical models describing the kinetics of aerosol particle nucleation and growth from a cooling vapor primarily use a nodal method, in which particles that are smaller than the critical size are omitted from consideration because they are thermodynamically unfavorable. This omission is based on the assumption that most newly formed particles are above the critical size, so that subcritical-size particles are not important to take into account. Due to the nature of the nodal method, it suffers from numerical diffusion, which can cause an artificial broadening of the cluster size distribution leading to a significant overestimation of the number of large-size particles. To address these issues, we propose a more accurate numerical method that explicitly models particles of all sizes, and uses a special numerical scheme that substantially reduces the numerical diffusion and provides high solution accuracy and numerical stability. We extensively compare this novel method to the commonly used nodal solver of the general dynamic equation (GDE) for particle growth and demonstrate that it offers GDE solutions with higher accuracy with low numerical diffusion. Incorporating small subcritical clusters into the solution is crucial for: 1) more precise determination of the entire particle size distribution function and 2) wider applicability of the model to experimental studies with non-monotonic temperature variations leading to particle evaporation. The computational code implementing this numerical method in Python is available upon request.

42 ENGINEERING↗

Spatial atomic layer deposition for coating flexible porous Li-ion battery electrodes

Ultrathin atomic layer deposition (ALD) coatings on the electrodes of Li-ion batteries can enhance the capacity stability of the Li-ion batteries. To commercialize ALD for Li-ion battery production, spatial ALD is needed to decrease coating times and provide a coating process compatible with continuous roll-to-roll (R2R) processing. The porous electrodes of Li-ion batteries provide a special challenge because higher reactant exposures are needed for spatial ALD in porous substrates. This work utilized a modular rotating cylinder spatial ALD reactor operating at rotation speeds up to 200 revolutions/min (RPM) and substrate speeds up to 200 m/min. The conditions for spatial ALD were adjusted to coat flexible porous substrates. The reactor was initially used to characterize spatial Al2O3 and ZnO ALD on flat, flexible metalized polyethylene terephthalate foils. These studies showed that slower rotation speeds and spacers between the precursor module and the two adjacent pumping modules could significantly increase the reactant exposure. The modular rotating cylinder reactor was then used to coat flexible, model porous anodic aluminum oxide (AAO) membranes. The uniformity of the ZnO ALD coatings on the porous AAO membranes was dependent on the aspect ratio of the pores and the reactant exposures. Larger reactant exposures led to better uniformity in the pores with higher aspect ratios. The reactant exposures were increased by adding spacers between the precursor module and the two adjacent pumping modules. The modular rotating cylinder reactor was also employed for Al2O3 ALD on porous LiCoO2 (LCO) battery electrodes. Uniform Al coverages were obtained using spacers between the precursor module and the two adjacent pumping modules at rotation speeds of 25 and 50 RPM. The LCO electrodes had a thickness of ~49 um and pores with aspect ratios of ~12-25. Coin cells were then constructed using the ALD-coated LCO electrodes and were tested to determine their battery performance. The capacity of the Al2O3 ALD-coated LCO battery electrodes was measured versus the number of charge-discharge cycles. Both temporal and spatial ALD processing methods led to higher capacity stability compared with uncoated LCO battery electrodes. The results for improved battery performance were comparable for temporal and spatial ALD-coated electrodes. The next steps are also presented for scale-up to R2R spatial ALD using the modular rotating cylinder reactor.

25 ENERGY STORAGE↗

Pressure-Driven Helium Insertion for Structural Stability of CH 3 NH 3 PbBr 3 Hybrid Perovskites

Organic−inorganic metal halide perovskites (MHPs) have garnered significant attention due to their outstanding performance in optoelectronic devices, but they are prone to degradation through a variety of pathways. High-pressure studies are being used to understand the mechanical and structural stability of MHPs and investigate new methods for improving these. In this study, we map the high-pressure, low-temperature structural phase diagram of CH 3 NH 3 PbBr 3 (MAPbBr 3 ) between 15−300 K and up to 1.5 GPa. We first compare the temperature and pressure effects on the global and local structures of MAPbBr 3 using synchrotron X-ray diffraction (XRD) and extended X-ray absorption fine structure (EXAFS), respectively, and find evidence of PbBr 6 octahedral distortion. Our results also suggest that He inserts into the MAPbBr 3 structure. The thermodynamics of He insertion into MAPBHe x are calculated to be plausible at room temperature for x ≤ 1 and P = 1−3 GPa and shown to stabilize higher-symmetry phases. This phenomenon increases the fitted bulk modulus of MAPbBr 3 . Structural stabilization by inert atom insertion is proposed as a method to improve the mechanical robustness of MHPs and other soft hybrid materials.

Diffraction↗

Improving Stability of Triple-Cation Perovskite Solar Cells under High-Temperature Operation

Metal halide perovskite photovoltaic performance required for commercial technology encompasses both efficiency and stability. Advances in both these parameters have recently been reported; however, these strategies are often difficult to directly compare due to differences in perovskite composition, device architecture, fabrication methods, and accelerated stressors applied in stability tests. In particular, it is found that there is a distinct lack of elevated temperature, operational (light and bias) stability data. Furthermore, significant testing is required to understand the interactions when combinations are used (e.g., additives used with posttreatments). Herein, individual and combined additive, posttreatment, and contact layer strategies from recent literature reports under standardized operational stability tests of p-i-n CsMAFA perovskites at 70 degrees C are evaluated. Through analysis of over 1000 devices, it is concluded that the hole-transport layer (HTL) is the most significant component impacting elevated temperature operational stability. This analysis motivates future development of high-performance HTLs.

14 SOLAR ENERGY↗

Orbital-enriched flat-top partition of unity method for the Schrödinger eigenproblem

Quantum mechanical calculations require the repeated solution of a Schrödinger equation for the wavefunctions of the system, from which materials properties follow. Recent work has shown the effectiveness of enriched finite element type Galerkin methods at significantly reducing the degrees of freedom required to obtain accurate solutions. However, time to solution has been adversely affected by the need to solve a generalized rather than standard eigenvalue problem and the ill-conditioning of associated system matrices. In this work, we address both issues by proposing a stable and efficient orbital-enriched partition of unity method to solve the Schrödinger boundary-value problem in a parallelepiped unit cell subject to Bloch-periodic boundary conditions. In the proposed partition of unity method, the three-dimensional domain is covered by overlapping patches, with a compactly-supported weight function associated with each patch. A key ingredient in our approach is the use of non-negative weight functions that possess the flat-top property, i.e., each weight function is identically equal to unity over some finite subset of its support. This flat-top property provides a pathway to devise a stable approximation over the whole domain. On each patch, we use $p$th degree orthogonal (Legendre) polynomials that ensure $p$th order completeness, and in addition include eigenfunctions of the radial Schrödinger equation. Furthermore, we adopt a variational lumping approach to construct a (block-)diagonal overlap matrix that yields a standard eigenvalue problem for which there exist efficient eigensolvers. The accuracy, stability, and efficiency of the proposed method is demonstrated for the Schrödinger equation with a harmonic potential as well as a localized Gaussian potential. In conclusion, we show that the proposed approach delivers optimal rates of convergence in the energy, and the use of orbital enrichment significantly reduces the number of degrees of freedom for a given desired accuracy in the energy eigenvalues while the stability of the enriched approach is fully maintained.

42 ENGINEERING↗

Dynamic Modeling of Sequential Service Restoration in Islanded Single Master Microgrids

This paper presents a methodology for generating restoration sequences in distribution systems and microgrids with emphasis on deriving optimal switching times for remote control switches (RCS). Microgrid architecture considered are assumed to be operating in islanded single master mode. Control methods for handling the unbalance inherent in distribution systems using single-phase controlled PQ inverters were developed and incorporated in the proposed method. The problem of considering simultaneously both energy optimization and dynamic stability of the system, which is lacking in existing methods, was addressed by studying the transient behavior of microgrids based on extended EMTP simulations and then approximate and incorporate these behaviors into the optimization formulation for restoration. The approach is based on multi-objective optimization of final restored load and total restoration time. The methodology was studied on a modified IEEE 123 node test feeder. An EMTP simulation in PSCAD of the formed microgrids was used to validate the accuracy of the dynamic and steady-state characteristics of the resulting systems. By considering the transient behavior of DGs during restoration, a better restoration sequence that does not trigger protection relays could be realized.

42 ENGINEERING↗

Aerosol-Assisted Deposition for TiO 2 Immobilization on Photocatalytic Fibrous Filters for VOC Degradation

Atomization and spraying are well-established methods for the production of submicrometer- and micrometer- sized powders. In addition, they could be of interest to the immobilization of photocatalytic nanoparticles onto supports because they enable the formation of microporous films with photocatalytic activity. Here, we provide a comparison of aerosol-assisted immobilization methods, such as spray-drying (SD), spray atomization (SA), and spray gun (SG), which were used for the deposition of TiO 2 dispersions onto fibrous filter media. The morphology, microstructure, and electronic properties of the structures with deposited TiO 2 were characterized by SEM and TEM, BET and USAXS, and UV-Vis spectrometry, respectively. The photocatalytic performances of the functionalized filters were evaluated and compared to the benchmark dip-coating method. Our results showed that the SG and SA immobilization methods led to the best photocatalytic and operational performance for the degradation of toluene, whereas the SD method showed the lowest degradation efficiency and poor stability of coating. We demonstrated that TiO2 sprays using the SG and SA methods with direct deposition onto filter media involving dispersed colloidal droplets revealed to be promising alternatives to the dip-coating method owing to the ability to uniformly cover the filter fibers. In addition, the SA method allowed for fast and simple control of the coating thickness as the dispersed particles were continuously directed onto the filter media without the need for repetitive coatings, which is common for the SG and dip-coating methods. Our study highlighted the importance of the proper immobilization method for the efficient photocatalytic degradation of VOCs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Workflow for evaluating enzyme immobilization and performance for continuous flow manufacturing

Enzymes have shown promise in various industries due to their functional specificity, catalytic efficiency, and environmental sustainability. These biological catalysts can be a pivotal component of manufacturing pipelines like continuous flow chemistry. For this, there exists a need to robustly immobilize enzymes on solid supports and assess the effects of the solid supports on catalytic performance and stability. Here, we use an industrially relevant model enzyme, C. ensiformis (Jack bean) urease, to demonstrate immobilization and assess performance in the context of continuous flow manufacturing. Various immobilization strategies were screened focusing on immobilization efficiency, protocol simplicity, and urease biocatalyst kinetics. Based on this, CDI-agarose and NHS-agarose resins were identified as the best-performing immobilization strategies for urease. CDI-agarose-urease and NHS-agarose-urease were then scaled up and applied to a large-scale continuous flow reactor to evaluate product yields, operational stability, and long-term stability. These experiments identified differences in stability and performance depending on the immobilization method tested. This highlights the importance of screening immobilization methods and subsequent enzyme performance for each candidate biocatalyst used in manufacturing to promote optimal performance and stability. As such, this work provides a framework for evaluating enzyme biocatalyst immobilization approaches to improve performance and enable transition into industrial processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗