Precursor design for additive manufacturing of ceramics through hydrogel infusion
Studies to understand how organic (resin formulations) and inorganic (salts and cation identities) precursors influence the quality of ceramics using HIAM.
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Studies to understand how organic (resin formulations) and inorganic (salts and cation identities) precursors influence the quality of ceramics using HIAM.
The stable levitation of an analyte sample in an acoustic levitator is a primary requirement for accurate x-ray characterization of its scientific structure. A rigid particle oscillates in an under-damped manner when introduced into the node of established standing acoustic waves. This investigation has employed the lattice Boltzmann method (LBM), a computational fluid dynamics technique, for the analysis of such rigid particle dynamics in acoustic levitation. The simulation uses the two dimensional and nine velocity (D2Q9) Bhatnagar-Gross-Krook formulation to levitate a rigid 1.6 mm diameter nylon ($\rho$ = 1150 kg/m 3 ) particle in the air at standard pressure and temperature conditions. The presented work is the first reported simulation of realistic acoustic levitator boundary conditions using the LBM. The simulation can capture the particle-fluid interactions that produce dynamic levitation at less than one-period timescale in the ultrasonic frequency regime. An experiment was conducted by levitating a 1.6mm-diameter nylon sphere to estimate the oscillations, and the oscillating frequency was found to be 50 Hz. The dynamic simulation results are consistent with experimental results for particle oscillations within the same order of magnitude, indicating that LBM formulation can be successfully used to study acoustic levitation to understand and mitigate particle jitter. The distortion of the acoustic field due to a levitating particle's presence was also analyzed to demonstrate how the presence of the particle can disrupt adjacent levitating nodes.
The O(2) model in Euclidean space-time is the zero-gauge-coupling limit of the compact scalar quantum electrodynamics. In this work, we obtain a dual representation of it called the charge representation. We study the quantum phase transition in the charge representation with a truncation to “spin $\textit{S}$," where the quantum numbers have an absolute value less than or equal to $\textit{S}$. The charge representation preserves the gapless-to-gapped phase transition even for the smallest spin truncation $\textit{S}$ = 1. The phase transition for $\textit{S}$ = 1 is an infinite-order Gaussian transition with the same critical exponents $\textit{δ}$ and $\textit{η}$ as the Berezinskii-Kosterlitz-Thouless (BKT) transition, while there are true BKT transitions for $\textit{S}$ ≥ 2 . The essential singularity in the correlation length for $\textit{S}$ = 1 is different from that for $\textit{S}$ ≥ 2 . The exponential convergence of the phase-transition point is studied in both Lagrangian and Hamiltonian formulations. We discuss the effects of replacing the truncated $\hat{U}^±$ = exp ($± i\hat{θ}$) operators by the spin ladder operators $\hat{S}^±$ in the Hamiltonian. The marginal operators vanish at the Gaussian transition point for $\textit{S}$ = 1, which allows us to extract the $\textit{η}$ exponent with high accuracy.
Tracking the dynamics of physical systems in real time is a prime application of quantum computers. Using a trapped-ion system with up to six qubits, we simulate the real-time dynamics of a lattice gauge theory in 1+1 dimensions, i.e., the lattice Schwinger model, and demonstrate nonperturbative effects such as pair creation for times much longer than previously accessible. We study the gate requirement of two formulations of the model using the Suzuki-Trotter product formula, as well as the trade-off between errors from the ordering of the Hamiltonian terms, the Trotter step size, and experimental imperfections. To mitigate experimental errors, a recent symmetry-protection protocol for suppressing coherent errors and a symmetry-inspired postselection scheme are applied. This work demonstrates the integrated theoretical, algorithmic, and experimental approach that is essential for efficient simulation of lattice gauge theories and other complex physical systems.
Marine renewable energy (MRE) resources are highly predictable and persistent sources of energy, when compared to other renewable sources like wind and solar. These lend them favorably for potential grid applications, particularly for coastal/island power systems where their generation potential is high. Island power systems, on the other hand, are either supported by onsite generation or by transported energy from the mainland grid. Therefore, robustness of grid operations depend heavily on the diversity of onsite generation resources and the reliability of the power transportation medium. Issues relating to either of these two factors may lead to impediments in smooth and reliable operation of the power system. Analyzing and quantifying operational risks for such island power systems with diverse non-conventional generation portfolios through conventional techniques can also prove to be cumbersome, often requiring multiple different inputs. Therefore, in this paper, we firstly present a novel, purely data-driven formulation which quantifies the operational reliability of such island power systems through minimal input data. Specifically, our proposed methodology only relies on historical knowledge of typical hourly load and generation profiles to quantify associated operational risks. Subsequently, we use our proposed formulation to evaluate the effectiveness of MRE resources (over other renewable resources like wind and solar) in providing resilience benefits to island power systems. The proposed formulation is demonstrated with a case study for an island power system in Nantucket, MA.
Rare-earth barium copper oxide (REBCO) high-temperature superconducting (HTS) magnets can generate very high magnetic fields with superior engineering current density and robust mechanical integrity. The no-insulation (NI) winding technique, including its metal-insulation (MI) variant, enables “self-protection” against localized overheating through inter-turn current sharing, improving defect tolerance and allowing temporary current overloads. In REBCO pancake coils, the current-sharing path is predominantly confined to the edges of the REBCO tapes due to insulating buffer layers. Applying a surface shunt using solder can effectively enhance current sharing in NI/MI coils via the REBCO tape edges. Here, in this paper, we present both experimental and numerical research on the current distribution in surface-shunt metal-insulation (SSMI) REBCO pancake coils. We tested a stainless steel co-wound MI REBCO double-pancake coil, before and after applying a soldered surface shunt, in a saturated liquid nitrogen bath. The SSMI coil was modeled using the H-formulation and rotated anisotropic resistivity to study its dynamic behavior, including inter-turn current sharing and intra-turn screening currents. Benchmarked by experimental data, the numerical model is able to study the defect tolerance of the SSMI coil during energization.
Abstract Susceptibility of wood to UV degradation decreases the service life of wood products outdoors. Organic UV absorbers (UVAs) and hindered amine light stabilizers (HALSs), as well as inorganic UVAs, are added to coatings to improve the UV stability of coated-wood products. Although about 85% of UV radiation is absorbed by lignin in the wood, it is unclear which UV stabilizers can minimize lignin degradation. In this study, the photodegradation of softwood organosolv lignin was monitored over 35 days of UV exposure. Changes in lignin properties were assessed using Fourier transform infrared spectroscopy (FTIR), differential scanning calorimetry (DSC), gel permeation chromatography (GPC), and phosphorus-31 nuclear magnetic resonance spectroscopy ( 31 P NMR). It was found that the aromatic rings of lignin underwent significant degradation, resulting in increased glass transition temperature and molecular weight of lignin. Subsequently, 18 different additives were mixed with lignin and exposed to UV irradiation. The analysis of samples before and after UV exposure with FTIR revealed that inorganic UVAs (cerium oxide and zinc oxide) and a mixture of organic UVAs and HALSs (T-479/T-292, T-5248, and T-5333) were the most effective additives in reducing lignin degradation. This study can help coating scientists to formulate more durable transparent exterior wood coatings.
An all-frequency stable formulation has been proposed and applied to solve low-frequency and multiscale electromagnetic problems to avoid the low-frequency breakdown catastrophe of the traditional vector wave equation. Based on the potential representation of the fields, this formulation involves vector and scalar potentials, as well as an auxiliary potential to enforce the gauge condition. In this paper, such a formulation is first simplified to involve vector potential only. Their iterative solutions are then sought by using an incomplete LU preconditioner and an iterative solver. The iterative performance of both formulations are investigated in a comparative study.
Harnessing aluminum oxidation energy requires navigating the particle's passivation shell composed of alumina. The shell is a barrier to aluminum oxidation but can also exothermically react with halogenated species and therefore contribute to the overall energy generated during aluminum particle combustion. Fluorination reactions with alumina have been studied because fluorine is abundant in binder formulations that commonly surround aluminum particles in an energetic mixture. However, iodine has emerged as an alternative halogenated-based binder or oxidizer because iodine gas provides ancillary benefits such as chemical neutralization of biological agents or sterilization of contaminated environments. Furthermore, this study used density functional theory (DFT) calculations to evaluate potential reaction pathways for aluminum–iodine combustion. Relative to fluorinated fragments such as HF and F – , the adsorption energies associated with HI and I– are nearly triple the exchange reaction energy available from fluorination reactions with alumina (–189 and –278 kJ mol –1 for HI and I – , respectively). However, exchange reactions between iodinated species and the alumina surface are energetically unfavorable. These results explain that through adsorption, alumina surface exothermic reactions with iodine are more energetic than with fluorine fragments. Experiments performed with differential scanning calorimetry (DSC) confirm the higher magnitude of energy generated for iodination compared with fluorination reactions with alumina. Additionally, strong adsorption energies can promote synthesis of new shell chemistries. Adsorption in solution will promote alumina dissolution and iodine precipitation reactions to produce hydroxyl complexes and iodinated species synthesized on the surface of the particle, thereby replacing alumina with alternative passivation shell chemistry.
Several power take-off (PTO) architectures for wave-powered reverse osmosis (RO) desalination of seawater are introduced and compared based on the annual average freshwater production and the size of the components, which strongly relate to the costs of the system. The set of architectures compared includes a novel series-type PTO architecture not previously considered. These seawater hydraulic PTO architectures are composed of a WEC-driven pump, an RO module, an intake charge pump driven by an electric motor, and a hydraulic motor driving an electric generator for electric power production. This study is performed using an efficient two-way coupled steady-state model for the average performance of the system in a given sea state, including freshwater permeate production, electric power production, and electric power consumption. A multi-objective design problem is formulated for the purposes of this comparative study, with the objectives of maximizing annual freshwater production, minimizing the displacement of the WEC-driven pump, and minimizing the installed RO membrane area. This establishes a framework for comparison in the absence of a mature techno-economic model. The requirement that the system produces enough electric power to meet its consumption is applied as a constraint on the operation of the system. The oscillating wave surge converter Oyster 1 is assumed as the WEC. Weights on performance of the system in a given sea state are based on historical data from Humboldt Bay, CA. This study finds that (1) architectures in a series configuration allow for a reduction in the WEC-driven pump size of 59–92% compared to prior work, (2) varying the displacement of the WEC-driven pump between sea conditions does not provide any significant advantage in performance, and (3) varying the active RO membrane area between sea condition offers improvements between 7% and 41% in each design objective.
Stochastic parameterizations are used in numerical weather prediction and climate modeling to help capture the uncertainty in the simulations and improve their statistical properties. Convergence issues can arise when time integration methods originally developed for deterministic differential equations are applied naively to stochastic problems. In previous studies, it has been demonstrated that a correction term, known in stochastic analysis as the Itô correction, can help improve solution accuracy for various deterministic numerical schemes and ensure convergence to the physically relevant solution without substantial computational overhead. The usual formulation of the Itô correction is valid only when the stochasticity is represented by white noise. In this study, a generalized formulation of the Itô correction is derived for noises of any color. The formulation is applied to a test problem described by an advection–diffusion equation forced with a spectrum of fast processes. We present numerical results for cases with both constant and spatially varying advection velocities to show that, for the same time step sizes, the introduction of the generalized Itô correction helps to substantially reduce time integration error and significantly improve the convergence rate of the numerical solutions when the forcing term in the governing equation is rough (fast varying); alternatively, for the same target accuracy, the generalized Itô correction allows for the use of significantly longer time steps and, hence, helps to reduce the computational cost of the numerical simulation.
This study demonstrates the sensitivity of wind turbine wake steering performance to blade design. An actuator line model was implemented within an unsteady adjoint solver that enables efficient execution of gradient-based optimization and sensitivity studies. After first confirming the feasibility of wake steering by controlling actuator line chord profiles and formulating a suitable objective function for wake position, a sensitivity study was conducted to determine the relative importance of chord length as a function of spanwise position on the resulting turbine wake deflection. The results presented here support the idea that blade design choices play a role in wake control. In a larger context, this study demonstrates a computational framework in which turbine and blade designs can be studied at the individual and farm-wide level to enhance wind plant controllability and manage power output.
The Unruh effect can be formulated as the statement that the Minkowski vacuum in a Rindler wedge has a boost as its modular flow. In recent years, other examples of states with geometrically local modular flow have played important roles in understanding energy and entropy in quantum field theory and quantum gravity. Here I initiate a general study of the settings in which geometric modular flow can arise, showing (i) that any geometric modular flow must be a conformal symmetry of the background spacetime, and (ii) that in a well behaved class of “weakly analytic” states, geometric modular flow must be future-directed. I further argue that if a geometric transformation is conformal but not isometric, then it can only be realized as modular flow in a conformal field theory. Finally, I discuss a few settings in which converse results can be shown — i.e., settings in which a state can be constructed whose modular flow reproduces a given vector field.
We demonstrate a first-principles screening methodology as an effective tool to explore electrolyte formulations for the new generation of high energy density rechargeable batteries. We study the liquid structure and electronic properties in dilute electrolytes, high concentration electrolytes (HCE), and localized high concentration electrolytes (LHCE), with focus on electrolyte formulations based on lithium bis(fluorosulfonyl)imide (LiFSI), dimethyl carbonate (DMC), and bis(2,2,2-trifluoroethyl) ether (BTFE) as a diluent. We describe the solvation complexes in the dilute electrolyte and explore structural changes triggered by the increase in lithium salt concentration for HCEs and the diluent effects in LHCEs. In HCE formulations, there is a 4-fold coordination environment of lithium-ions as in the dilute electrolyte, but the number of lithium-ion interactions with O atoms from FSI- anions dominates. In these solutions, the ability of the FSI- anions to interact with multiple lithium-ions allows complex 3D network formation and influences the reductive/oxidative behavior of the electrolyte. Interestingly, in LHCEs, the BTFE diluent molecules do not change the 3D solution structure when diluting the HCE formulation from 5.49 to 3.83 M. However, there is a composition threshold where the structural and electronic behavior may change. We show that diluting the HCE electrolyte with BTFE down to 1.77 M breaks the three-dimensional solution structure into an island-like solvation complex. We relate these structural changes to the electronic properties of the electrolytes finding a causal relationship between the reductive/oxidative behavior and the lithium-oxygen interaction mechanisms in the solvated complexes. The coordination with lithium-ions lowers the electrolyte LUMO and HOMO levels: the higher is the number of interactions with lithium-ions, the more likely the solvent molecule, FSI- anion, or diluent molecule is to be reduced and the less likely it is to become oxidized. The evolution of the solvated ion structure in HCE and LHCE suggests a close connection to a corresponding change in the lithium-ion transport mechanisms for these electrolytes.
Accurate prediction of α-phase nucleation and growth in β-stabilized titanium alloys is crucial for designing heat treatments to optimize mechanical properties in additively manufactured lightweight components. Ideally, predictions of nucleation and growth would incorporate both top-down observations of past experimental heat treatments and bottom-up modeling of phase transformations; however, the appropriate method of combining these information sources is not self-evident. Combining top-down and bottom-up information requires a unified form of model that can connect between spatiotemporal scales, as well as sets of fitting parameters that can be identified by each data source. The selection of which parameters to fit to which data source can be made based on expert opinion, or by performing a sensitivity analysis. In solid-solid nucleation, direct observation of the nucleation and growth process is challenging. Most data on the heat treatment-controlled phase transformations are not in-situ. To predict the process and outcome of the nucleation, growth and coarsening of precipitates, theoretical models of the nucleation pathway are used to bridge the gap. Many sources of uncertainty affect the modeling of this nucleation process. It can be influenced by small variations in the thermomechanical processing history, chemical composition, and initial microstructure. If molecular dynamics (MD) simulations are used to determine thermodynamic quantities and inform CALPHAD modeling, additional uncertainty can be introduced and accounted for using Bayesian methods. Top-down uncertainties require additional steps to quantify. The influence of nucleation model form on the sensitivity of predictions to input parameters and physical conditions is the focus of this study. Classical nucleation theory (CNT) allows modeling to formulate the nucleation as homogeneous or, more commonly, heterogeneous. Non-classical nucleation models are also increasingly explored as a means of reconciling top-down and bottom-up data. In this study, the sensitivity of the intragranular nucleation of α in a β-annealed, slow-cooled aging (BASCA) heat treatment of β-stabilized Ti5553 alloy is explored using CNT and both heterogeneous and homogeneous assumptions. The Kampmann-Wagner Numerical model of precipitate nucleation and growth is employed. Using open-source tools (pyCalphad and thermodynamic modeling of TiMo as a surrogate system, a sensitivity analysis is performed to measure variations in key parameters, including chemical driving force, interfacial energy, and diffusivity, as they relate to predictions of precipitate number density. The inclusion of top-down and bottom-up data in selection of nucleation model form is discussed.
During dry and windy seasons, environmental conditions significantly increase the risk of wildfires, exposing power grids to disruptions caused by transmission line failures. Wildfire propagation exacerbates grid vulnerability, potentially leading to prolonged power outages. To address this challenge, we propose a multistage optimization model that dynamically adjusts transmission grid topology in response to wildfire propagation, aiming to develop an optimal response policy. By accounting for decision-dependent uncertainty, where line survival probabilities depend on usage, we employ distributionally robust optimization to model uncertainty in line survival distributions. We adapt the stochastic nested decomposition algorithm and derive a deterministic upper bound for its finite convergence. To enhance computational efficiency, we exploit the Lagrangian dual problem structure for a faster generation of Lagrangian cuts. Using realistic data from the California transmission grid, we demonstrate the superior performance of dynamic response policies against two-stage alternatives through a comprehensive case study. In addition, after solving the multistage formulation, we construct easy-to-implement policies that significantly reduce computational burden while maintaining good performance in real-time deployment. History: Accepted by Russell Bent, Area Editor for Network Optimization: Algorithms and Applications. Funding: This work was supported by the U.S. Department of Energy, Office of Electricity [Grant DE-AC02-05CH11231]. The work of R. Jiang was supported in part by the U.S. National Science Foundation, Division of Electrical, Communications and Cyber Systems [Grant ECCS-1845980] and the U.S. Air Force Office of Scientific Research [Grant FA9550-23-1-0323]. Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplemental Information ( https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2025.1210 ) as well as from the IJOC GitHub software repository ( https://github.com/INFORMSJoC/2025.1210 ). The complete IJOC Software and Data Repository is available at https://informsjoc.github.io/ .
Rotating detonation engines (RDEs) provide a promising route to substantially increasing cycle efficiency in stationary gas turbines. Much of this increase relies on the ability to achieve consistent pressure gain within the combustor. In particular, the design of injectors that feed fuel and air into the detonation channel plays a crucial role. Such injectors have to ensure proper mixing of fuel and oxidizer, while minimizing backflow of detonation products into the feed plenums, and reduce susceptibility to the complex wave structures that exist within the combustor. From a practical perspective, such RDEs also need to operate with variable fuel composition. When fuel mixtures with components that possess vastly different oxidation pathways and time-scales are used, there could be additional losses through deflagrative burning instead of detonation-driven heat release. Such sensitivity to the complete flow path is akin to the physics of thermoacoustic instabilities in conventional gas turbines. In this sense, RDEs pose a unique research challenge: the performance of the device relies on the small-scale heat release process, which is highly dependent on the flow interactions within the full-scale system. As a result, canonical flow configurations, instrumented with detailed diagnostics or modeled using high-fidelity tools, but only focus on the small-scale processes will not contain the key system-level interactions. At the same time, macroscopic measurements and models that only capture system-level performance will not provide insight into the key sources of pressure losses. These couplings and sensitivities provide a formidable challenge to both experimental and simulation studies of the effects Thus, a joint experimental/computational program designed specifically to address these challenges was undertaken in this program. The focus of this program was on two key topics: a) the interaction between injector flow and the overall wave dynamics within the combustor, and b) the deflagration/detonation structure in multi-component fuels that are of practical interest. Both topics involve interaction of small-scale heat release processes with the geometry-dependent wave structure. Studies focused on the study of full-scale RDE systems, based on a 6-inch conventional annular geometry. Experimentally RDEs were studied using a combination of diagnostics. A combination of optical diagnostics and aero-thermo-acoustic analysis based on a combination of spectral and mode decomposition analysis was used to identify the dynamics of the detonation wave and other secondary waves that exist in the system. These studies have helped the identification and investigation of injector and detonation dynamics arising from coupling, and how they affect RDE mixing, detonation structure, operability and performance. Performance of RDEs was investigated through thrust stand measurements, which was used to evaluate the effective pressure gain generated by the system through the concept of equivalent available pressure. Optical diagnostics were developed and implemented to investigate the distribution of heat release, across the detonation wave. Novel optical diagnostics of NIR imaging was also developed and applied to investigate the high temperature / high pressure distribution across the detonation wave. In order to complement the experiments, the computational tools were geared to simulate the full experimental setup. GPU-based acceleration of the models and computations were developed to enable rapid simulation of the full system. In addition, the use of adaptive mesh refinement, and unstructured grid formulation, enabled the investigation of realistic geometries studied in the laboratory. The simulations produced a wealth of detail on the structure of the detonation wave under different operating conditions. Emphasis was placed on quantifying mixture pre-burning and the impact on wave propagation and structure.
Aluminosilicate hydrogels are often considered to be precursors for the crystallisation of zeolites carried out under hydrothermal conditions. The preparation of mechanically homogeneous aluminosilicate gels enables the study of these materials through bulk rheology and observation of the aging dynamics until the precipitation of crystalline zeolites. The first part of this study deals with the establishment of ternary state diagrams, in order to identify the range of chemical formulations that enable preparation of single-phase homogeneous gels. Then, by studying the viscoelastic moduli during the gelation reaction, and by yielding the gel under large deformation, we propose an empirical law considering the partial order of reaction on each chemical element, to predict the gelation time according to the chemical formulation. The scaling behavior of the elastic properties of this colloidal gel shows a transition from a strong link behavior to a weak link regime. Long term aging results in the shrinkage of the gel, accompanied by syneresis of interstitial liquid at the surface. Zeolites precipitate through crystallisation by a particle attachment mechanism, when thermodynamic equilibrium is reached. The stoichiometry of the precipitated zeolites is not only consistent with the concentration of the remaining species in the supernatant but, surprisingly, it is also very close to the partial order of the reaction of the chemical elements involved in the determination of the critical gel point. This indicates a strong correlation between the morphology of the soft amorphous gel network that is formed at an early age and those of the final solid precipitated crystals.