Stabilization of Colloidal Crystals Engineered with DNA
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Oh, Taegon↗
SEARCH · Engineering Papers
Results for “stabilization method”
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Non-hydrolytic metal oxide films for perovskite halide overcoating and stabilization
A method of protecting a perovskite halide film from moisture and temperature includes positioning the perovskite halide film in a chamber. The chamber is maintained at a temperature of less than 200 degrees Celsius. An organo-metal compound is inserted into the chamber. A non-hydrolytic oxygen source is subsequently inserted into the chamber. The inserting of the organo-metal compound and subsequent inserting of the non-hydrolytic oxygen source into the chamber is repeated for a predetermined number of cycles. The non-hydrolytic oxygen source and the organo-metal compound interact in the chamber to deposit a non-hydrolytic metal oxide film on perovskite halide film. The non-hydrolytic metal oxide film protects the perovskite halide film from relative humidity of greater than 35% and a temperature of greater than 150 degrees Celsius, respectively.
36 MATERIALS SCIENCE↗
Electrolyte additives for transition metal cyanometallate electrode stabilization
A method is provided for the self-repair of a transition metal cyanometallate (TMCM) battery electrode. The battery is made from a TMCM cathode, an anode, and an electrolyte including solution formed from a solvent and an alkali or alkaline earth salt. The electrolyte includes an additive represented as G-R-g: where G and g are independently include materials with nitrogen (N) sulfur (S), oxygen (O), or combinations of the above-recited elements; and where R is an alkene or alkane group. In response to charging and discharging the battery in a plurality of cycles, the method creates vacancies in a surface of the TMCM cathode. Then, the method fills the vacancies in the surface of the TMCM cathode with the electrolyte additive. An electrolyte and TMCM battery using the above-mentioned additives are also provided.
25 ENERGY STORAGE↗
Stabilized lithium metal oxide electrode material and method of preparation
A stabilized lithium metal oxide cathode material comprises microparticles of lithium metal oxide in which individual particles thereof a core of lithium metal oxide and a coating of a different lithium metal oxide surrounding the core. There is an interface layer between the cores and the coatings in which there are gradients of metal ions in the direction of coating to core. The materials are made by a three stage process involving coprecipitating precursor metal hydroxide core particles at a controlled pH; coprecipitating a different metal hydroxide coating on the particles without controlling the pH; and then calcining the resulting coated precursor particles with lithium hydroxide to form the stabilized lithium metal oxide material.
Lipson, Albert L.↗
Stabilized lithium metal oxide electrode material and method of preparation
A stabilized lithium metal oxide cathode material comprises microparticles of lithium metal oxide in which individual particles thereof a core of lithium metal oxide and a coating of a different lithium metal oxide surrounding the core. There is an interface layer between the cores and the coatings in which there are gradients of metal ions in the direction of coating to core. The materials are made by a three stage process involving coprecipitating precursor metal hydroxide core particles at a controlled pH; coprecipitating a different metal hydroxide coating on the particles without controlling the pH; and then calcining the resulting coated precursor particles with lithium hydroxide to form the stabilized lithium metal oxide material.
Lipson, Albert L.↗
Optimization of Preparation Method, Nucleating Agent, and Stabilizers for Synthesizing Calcium Chloride Hexahydrate (CaCl2.6H2O) Phase Change Material
This study investigates improvements in low-cost latent heat storage material calcium chloride hexahydrate (CaCl2.6H2O). Its melting point is between 25 and 28 °C, with relatively high enthalpy (170–190 J/g); however, this phase change material (PCM) shows supercooling and phase separation. In CaCl2.6H2O incongruent melting causes lower hydrates of CaCl2 to form, which affects the overall energy storage capacity and long-term durability. In this work, PCM performance enhancement was achieved by adding SrCl2.6H2O as a nucleating agent and NaCl/KCl as a stabilizer to prevent supercooling and phase separation, respectively. We investigated the PCM preparation method and optimized the proportions of SrCl2.6H2O and NaCl/KCl. Thermal testing for 25 cycles combined with DSC and T-history testing was performed to observe changes in enthalpy, phase transitions and supercooling over the extended period of usage. X-ray diffraction was used to verify crystalline structure in the compounds. It was found that the addition of 2 wt.% of SrCl2.6H2O reduced supercooling from 12 °C to 0 °C compared to unmodified CaCl2.6H2O. The addition of 5 wt.% NaCl or KCl proved to effectively suppress separation and the melting enthalpy achieved was 169 J/g–178 J/g with congruent melting over 25 cycles, with no supercooling and almost no reduction in the latent heat.
42 ENGINEERING↗
Multistage Stabilized Continuation for Indirect Optimal Control of Three-Dimensional Hypersonic Trajectories
This work presents the development of a multistaged stabilized continuation for the three-dimensional unpowered hypersonic trajectory planning problem using indirect optimal control methods. The stabilized continuation method is noniterative and guaranteed to terminate within a finite number of floating point operations, thereby making it well suited for onboard autonomous implementations. Here, we present a multistage formulation of the stabilized continuation scheme that involves starting with a “loose” integration tolerance during the first stage and ramping up toward a “strict” integration tolerance through subsequent stages. An important benefit of this approach is that even when the solution to the underlying optimal control problem is numerically unstable, such as with the hypersonic vehicle footprint generation problem, the stabilized continuation algorithm is shown to be successful in finding a solution while providing some additional insights into the underlying cause of the numerical instability.
33 ADVANCED PROPULSION SYSTEMS↗
Stabilization of colloidal crystals engineered with nucleic acid
A post-synthetic method for stabilizing colloidal crystals programmed from nucleic acid is disclosed herein. In some embodiments, the method relies on Ag + ions to stabilize the particle-connecting nucleic acid duplexes within the crystal lattice, essentially transforming them from loosely bound structures to ones with very strong interparticle links. In some embodiments, the nucleic acid is DNA. Such crystals do not dissociate as a function of temperature like normal DNA or DNA-interconnected colloidal crystals, and they can be moved from water to organic media or the solid state, and stay intact. The Ag + -stabilization of the nucleic acid (e.g., DNA) bonds is accompanied by a nondestructive contraction of the lattice, and both the stabilization and contraction are reversible with the chemical extraction of the Ag + ions, e.g., by AgCl precipitation with NaCl.
Mirkin, Chad A.↗
A Three-Stage Enhanced Reactive Power and Voltage Optimization Method for High Penetration of Solar
This paper presents a three-stage enhanced volt/var optimization method to stabilize voltage fluctuations in transmission networks by optimizing the usage of reactive power control devices. In contrast with existing volt/var optimization algorithms, the proposed method optimizes the voltage profiles of the system, while keeping the voltage and real power output of the generators as close to the original scheduling values as possible. This allows the method to accommodate realistic power system operation and market scenarios, in which the original generation dispatch schedule will not be affected. The proposed method was tested and validated on a modified IEEE 118-bus system with photovoltaic data.
photovoltaic, Volt/Var Control, indexes, simulatio↗
Interior Decoration of Stable Metal–Organic Frameworks
Metal–organic frameworks (MOFs) are a diverse class of hybrid organic/inorganic crystalline materials composed of metal-containing nodes held in place by organic linkers. Through a discerning selection of these components, many properties such as the internal surface area, cavity size and shape, catalytic properties, thermal properties, and mechanical properties may be manipulated. Because of this high level of tunability, MOFs have been heralded as ideal platforms for various applications including gas storage, separation, catalysis, and chemical sensing.(1-8) Regrettably, these theoretical possibilities are limited by the reality of constraining conditions for solvothermal synthesis, which typically include high temperatures (usually over 100 °C), the use of specific solvents, and necessary exposure to acidic or basic conditions. In order to incorporate more delicate functionalities, postsynthesis decoration methods were developed. This feature article focuses on developed interior decoration methods for stable MOFs and the dynamic relationship between such methods and MOF stability. In particular, methods to transform organic, inorganic, and organometallic MOF parts as well as combination techniques, the generation of defects, and the inclusion of enzymes are addressed.
36 MATERIALS SCIENCE↗
Using a Coarse-Grained Modeling Framework to Identify Oligomeric Motifs with Tunable Secondary Structure
Coarse-grained modeling can be used to explore general theories that are independent of specific chemical detail. In this paper, we present cg_openmm, a Python-based simulation framework for modeling coarse-grained hetero-oligomers and screening them for structural and thermodynamic characteristics of cooperative secondary structures. cg_openmm facilitates the building of coarse-grained topology and random starting configurations, setup of GPU-accelerated replica exchange molecular dynamics simulations with the OpenMM software package, and features a suite of postprocessing thermodynamic and structural analysis tools. In particular, native contact analysis, heat capacity calculations, and free energy of folding calculations are used to identify and characterize cooperative folding transitions and stable secondary structures. In this work, we demonstrate the capabilities of cg_openmm on a simple 1–1 Lennard-Jones coarse-grained model, in which each residue contains 1 backbone and 1 side-chain bead. By scanning both nonbonded and bonded force-field parameter spaces at the coarse-grained level, we identify and characterize sets of parameters which result in the formation of stable helices through cooperative folding transitions. Furthermore, we show that the geometries and stabilities of these helices can be tuned by manipulating the force-field parameters.
36 MATERIALS SCIENCE↗
On the Stochastic Stability of Deep Markov Models
Deep Markov models (DMM) are generative models which are scalable and expressive generalization of Markov models for representation, learning, and inference problems. However, the fundamental stochastic stability guarantees of such models have not been thoroughly investigated. In this paper, we present a novel stability analysis method and provide sufficient conditions of DMM's stochastic stability. The proposed stability analysis is based on the contraction of probabilistic maps modeled by deep neural networks. We make connections between the spectral properties of neural network's weights and different types of used activation function on the stability and overall dynamic behavior of DMMs with Gaussian distributions. Based on the theory, we propose a few practical methods for designing constrained DMMs with guaranteed stability. We empirically substantiate our theoretical results via intuitive numerical experiments using the proposed stability constraints.
Drgona, Jan↗
Analysis of the Spectral Stability of the Generalized Runge–Kutta Methods Applied to Initial-Boundary-Value Problems for Equations of the Parabolic Type. I. Explicit Methods
We develop a general algorithm for the analysis the spectral stability of generalized multistage Runge–Kutta methods of various orders of accuracy as applied to the numerical integration with respect to time of an initial-boundary-value problem for the second-order parabolic equation. The expression for the function of spectral stability is obtained in two alternative forms: on the basis of matrix relations and in the determinant form. We study specific realizations of various generalized explicit Runge–Kutta methods and their spectral stability. It is shown that all explicit generalized Runge–Kutta methods possess the property of conditional spectral stability and the property of conditional monotonicity of the numerical solution in time whose violation leads to the appearance of false oscillations of the approximate solution. The stability function for these methods is polynomial. It is shown that the application of two-stage generalized explicit Runge–Kutta methods leads to the appearance of predictor-corrector-type schemes. In the case of nonstationary one-dimensional heat-conduction problem, on the basis of a one-stage generalized Runge–Kutta method, we obtain the classical two-layer conditionally stable explicit finite-difference scheme on a four-point template. It is demonstrated that the five-stage generalized Runge–Kutta–Merson method is characterized by the weakest condition of spectral stability as compared with all investigated explicit generalized Runge–Kutta methods.
42 ENGINEERING↗
Polishing slurry preventing agglomeration of charged colloids without loss of surface activity
A method for chemically stabilizing polishing slurries in aqueous suspension to prevent their agglomeration while maintaining their surface activity is disclosed. The method prevents the formation of irreversible particle agglomerates during drying and permits the subsequent re-suspension of dried particles with no impact on the particle size distribution. The stabilization method can be customized based on knowledge of the colloid surface charge at suspension pH conditions, addition of a charged species having like charge to the colloid at the suspension conditions, and control of the concentrations of the charged species and other ions in suspension.
Dylia-Spears, Rebecca↗
Impact of boundary layer simulation on predicting radioactive pollutant dispersion: a case study for HANARO Research Reactor using the WRF-MMIF-CALPUFF modeling system
Wind plays an important role in cases of unexpected radioactive pollutant dispersion, deciding distribution and concentration of the leaked substance. The accurate prediction of wind has been challenging in numerical weather prediction models, especially near the surface because of the complex interaction between turbulent flow and topographic effect. As such, in this study, we investigated the characteristics of atmospheric dispersion of radioactive material (i.e. 137 Cs) according to the simulated boundary layer around the HANARO research nuclear reactor in Korea using the Weather Research and Forecasting (WRF)-Mesoscale Model Interface (MMIF)-California Puff (CALPUFF) model system. We examined the impacts of orographic drag on wind field, stability calculation methods, and planetary boundary layer parameterizations on the dispersion of radioactive material under a radioactive leaking scenario. We found that inclusion of the orographic drag effect in the WRF model improved the wind prediction most significantly over the complex terrain area, leading the model system to estimate the radioactive concentration near the reactor more conservatively. We also emphasized the importance of the stability calculation method and employing the skillful boundary layer parameterization to ensure more accurate low atmospheric conditions, in order to simulate more feasible spatial distribution of the radioactive dispersion in leaking scenarios.
54 ENVIRONMENTAL SCIENCES↗
Complete synchronization of uncertain chaotic systems via a single proportional adaptive controller: A comparative study
This paper addresses a comparative computational study on the synchronization quality, cost and converging speed for two pairs of identical chaotic and hyperchaotic systems with unknown time-varying parameters. It is assumed that the unknown time-varying parameters are bounded. Based on the Lyapunov stability theory and using the adaptive control method, a single proportional controller is proposed to achieve the goal of complete synchronizations. Accordingly, appropriate adaptive laws are designed to identify the unknown time-varying parameters. The designed control strategy is easy to implement in practice. Numerical simulations results are provided to verify the effectiveness of the proposed synchronization scheme.
42 ENGINEERING↗
A neural network for determination of latent dimensionality in Nonnegative Matrix Factorization
Non-negative Matrix Factorization (NMF) has proven to be a powerful unsupervised learning method for uncovering hidden features in complex and noisy datasets with applications in data mining, text recognition, dimension reduction, face recognition, anomaly detection, blind source separation, and many other fields. An important input for NMF is the latent dimensionality of the data, that is, the number of hidden features, K, present in the explored dataset. Unfortunately, and this quantity is rarely known a priori. The existing methods for determining latent dimensionality, such as Automatic Relevance Determination (ARD), are mostly heuristic and utilize different characteristics to estimate the number of hidden features. However, all of them require human presence to make a final determination of K. Here we utilize a supervised machine learning approach in combination with a recent method for model determination, called NMFk, to determine the number of hidden features automatically. NMFk performs a set of NMF simulations on an ensemble of matrices, obtained by bootstrapping the initial dataset, and estimates which K produces stable groups of latent features that reconstruct the initial dataset well. We then train a Multi-Layter Perceptron (MLP) classifier network to determine the correct number of latent features utilizing the statistics and characteristics of the NMF solution, obtained from NMFk. In order to train the MLP classifier, a training set of 58,660 matrices with predetermined latent features were factorized with NMFk. The MLP classifier in conjunction with NMFk maintains a greater than 95% success rate when applied to a held out test set. Additionally, when applied to two well-known benchmark datasets, the swimmer and MIT face data, NMFk/MLP correctly recovers the established number of hidden features. Finally, we compare the accuracy of our method to the ARD, AIC and Stability-based methods.
97 MATHEMATICS AND COMPUTING↗
An Evolve-Filter-Relax Stabilized Reduced Order Stochastic Collocation Method for the Time-Dependent Navier--Stokes Equations
In this paper, we propose a filter-based stabilization of reduced order models (ROMs) for uncertainty quantification (UQ) of the time-dependent Navier--Stokes equations in convection-dominated regimes. Here we propose a novel high-order ROM differential filter and use it in conjunction with an evolve-filter-relax (EFR) algorithm to attenuate the numerical oscillations of standard ROMs. We also examine how stochastic collocation methods can be combined with the EFR algorithm for efficient UQ of fluid flows. We test the new framework in the numerical simulation of a two-dimensional flow past a circular cylinder with a random viscosity that yields a random Reynolds number with mean Re = 100.
97 MATHEMATICS AND COMPUTING↗