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Results for “two-step transformation”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Structure-activity relationship of Pt catalyst on engineered ceria-alumina support for CO oxidation

In heterogeneous catalysis, the promotion of low temperature activity and enhancement of thermal stability simultaneously especially for precious metal catalysts is always highly demanded but very challenging. In this work, we report a novel Pt catalyst on ceria-alumina (CeO 2 /Al 2 O 3 ) support (Pt/CA-T) engineered by a two-step ceria deposition strategy, exhibiting superior thermal stability and low-temperature carbon monoxide (CO) oxidation activity after activation. Pt single sites anchored to engineered CeO 2 edge sites are much more stable than that to CeO 2 (111) surface, and such stable single sites can be transformed into highly active Pt clusters for efficient low-temperature CO oxidation. Active site identification indicates that the CO oxidation activity of different Pt sites follows such sequence: Pt cluster step sites ≈ Pt cluster terrace sites > Pt cluster corner sites $\gg$ Pt single sites on CeO 2 . The excellent low temperature activity of activated Pt/CA-T catalyst for CO oxidation is associated with its abundant Pt cluster step and terrace sites as well as rich Pt-CeO 2 interfaces, which facilitate the adsorption of active CO species and superior oxygen activation/transfer ability. The present study provides new insights into the structure–activity relationship of Pt-CeO 2 -Al 2 O 3 catalyst, which can also guide the preparation of other highly robust supported catalysts for important industrial applications.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Bayesian learning of orthogonal embeddings for multi-fidelity Gaussian Processes

Uncertainty propagation in complex engineering systems often poses significant computational challenges related to modeling and quantifying probability distributions of model outputs, as those emerge as the result of various sources of uncertainty that are inherent in the system under investigation. Gaussian Processes regression (GPs) is a robust meta-modeling technique that allows for fast model prediction and exploration of response surfaces. Multi-fidelity variations of GPs further leverage information from cheap and low fidelity model simulations in order to improve their predictive performance on the high fidelity model. In order to cope with the high volume of data required to train GPs in high dimensional design spaces, a common practice is to introduce latent design variables that are typically projections of the original input space to a lower dimensional subspace, and therefore substitute the problem of learning the initial high dimensional mapping, with that of training a GP on a low dimensional space. Here in this paper, we present a Bayesian approach to identify optimal transformations that map the input points to low dimensional latent variables. The \projection" mapping consists of an orthonormal matrix that is considered a priori unknown and needs to be inferred jointly with the GP parameters, conditioned on the available training data. The proposed Bayesian inference scheme relies on a two-step iterative algorithm that samples from the marginal posteriors of the GP parameters and the projection matrix respectively, both using Markov Chain Monte Carlo (MCMC) sampling. In order to take into account the orthogonality constraints imposed on the orthonormal projection matrix, a Geodesic Monte Carlo sampling algorithm is employed, that is suitable for exploiting probability measures on manifolds. We extend the proposed framework to multi-fidelity models using GPs including the scenarios of training multiple outputs together. We validate our framework on three synthetic problems with a known lower-dimensional subspace. The benefits of our proposed framework, are illustrated on the computationally challenging aerodynamic optimization of a last-stage blade for an industrial gas turbine, where we study the effect of an 85-dimensional shape parameterization of a three-dimensional airfoil on two output quantities of interest, specifically on the aerodynamic efficiency and the degree of reaction

42 ENGINEERING↗
DOE OSTI2025

Print-and-Plate Architected Electrodes for Electrochemical Transformations Under Flow

Flow cell electrodes are typically composed of porous carbon materials, such as papers, felts, and cloths. However, their random architecture hinders the fundamental characterization of electrode structure-performance relationships during in situ operation of porous electrochemical flow systems. This work describes a “print-and-plate” method that combines direct ink writing of micro-periodic lattices with a two-step metal plating process that converts them into highly conductive (sheet resistance 40 mΩ sq -1 ) electrodes. Their operando performance is assessed in an anthraquinone disulfonic acid half-cell using widefield electrochemical fluorescence microscopy, where output current and fluorescence intensity are in excellent agreement. The pressure drop associated with flow through three electrode designs is determined via simulations from which the most efficient design is identified and manufactured via print-and-plate. Confocal fluorescence microscopy is then used to create a 3D map of the state of charge (SOC) inside this print-and-plate electrode. The experimental state of the charge map is in good agreement with computational predictions. The rapid design, simulation, and fabrication of print-and-plate electrodes enable fundamental investigations of how architected porosity affects electrochemical performance under flow.

3D-printing↗
DOE OSTI2024

Two-dimensional silk

Despite the promise of silk-based devices, the inherent disorder of native silk limits performance. Here, we report highly ordered two-dimensional silk fibroin (SF) films grown epitaxially on van der Waals (vdW) substrates. Using atomic force microscopy, nano–Fourier transform infrared spectroscopy, and molecular dynamics, we show that the films consist of lamellae of SF molecules that exhibit the same secondary structure as the nanocrystallites of native silk. Increasing the SF concentration results in multilayers that grow either by direct assembly of SF molecules into the lamellae or, at high concentrations, along a two-step pathway beginning with a disordered monolayer that then crystallizes. Scanning Kelvin probe measurements show that these films substantially alter the surface potential; thus, they provide a platform for silk-based electronics on vdW solids.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Advanced nanoscale characterization of aluminum nanoparticles with modified surface morphology via atmospheric helium and carbon monoxide plasmas

Aluminum nanoparticles (nAl) have the potential as energetic additives in explosive/propellant formulations. Scalable methodologies must be pursued to mitigate the inactive amorphous alumina shell surrounding the active aluminum (Al) core with modified surface morphology and chemistry for increased combustion effects. This work explores the feasibility of making reactive core/shell nAl with thinned oxide shells and modified surface coatings via a two-step atmospheric plasma surface treatment process in a custom dielectric barrier discharge plasma reactor. The commercial nAl of nominal average size similar to 40-60nm was first treated with helium (He) followed by He/carbon monoxide (CO) plasmas for different durations. The resultant samples were characterized via high-resolution transmission electron microscopy (HRTEM) and Fourier transform IR (FTIR) spectra. HRTEM images revealed sporadic patchy gamma -alumina deposits on particle surfaces and in gaps among particles for all samples, suggesting the non-uniform plasma effects of the He/CO glow. Nanoscale chemical analyses via scanning transmission electron microscopy elemental mapping and x-ray energy dispersive spectroscopy were further performed. Although no carbon-associated structure appeared in electron energy loss spectroscopy (EELS) spectra, the presence of carbonaceous materials was confirmed as a thin dispersive layer evenly distributed on the nAl surface suggesting either its amorphous nature or is present at a level insufficient to generate satisfactory EELS spectra. The trend of intensity profiles for key elements acquired by drawing lines across a single particle on the elemental maps confirmed that carbonaceous materials only existed on the surface and they were most likely carboxylates that increased with increased He/CO treatment duration, as evident by FTIR results. Finally, this work demonstrated the success of atmospheric plasma-treated reactive nAl with comprehensively characterized surface features via advanced microscopy and spectroscopy.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Two-Step Synthesis of Poly (urea formaldehyde) Microcapsules

Self-healing coatings have potential to reduce waste and minimize repair costs in industries where materials need to be protected from harsh environmental conditions and mechanical abrasion. These coatings can be created by embedding healing-agent filled microcapsules which release their contents and fill voids in the event of damage. To synthesize microcapsules that are ideal for self-healing coatings, they must have a diameter less than 100 microns, smooth surface morphology, and have improved dispersibility. Our current one-step method does not produce microcapsules within the desired size distribution, so a two-step route where oligomers of the shell wall material are formed prior to microcapsule formation was investigated. This was done by evaluating the effects of solution viscosity, size of reaction vessel, addition of poly (vinyl alcohol) (PVA), and core/shell ratio on microcapsule properties. Characterization of microcapsule size, morphology, and composition was done using optical microscopy, Fourier-transform infrared spectroscopy (FTIR), and thermogravimetric analysis (TGA). Microcapsules with an average diameter of 78 ± 16 microns were successfully synthesized. Further work must be done to minimize PUF crystallites on the surface of the microcapsules.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A one-pot synthesis of high-density biofuels through bifunctional mesoporous zeolite-encapsulated Pd catalysts

Developing a powerful bifunctional catalyst for tandem reactions is essential to the future carbon neutrality by reducing the energy consumption in chemical industries. Herein, mesoporous zeolite-encapsulated palladium (Pd) nanoparticles (Pd@meso-ZSM-5) synthesized via emulsification-demulsification followed by a dry-gel transformation method were demonstrated to have a remarkable catalytic performance for a one-pot multiple tandem reaction of cyclic ketones (cyclopentanone, cyclohexanone) to bicyclic alkanes (bicyclopentane, bicyclohexane). Compared with supported catalysts (Pd/meso-ZSM-5) and microporous zeolite-encapsulated catalysts (Pd@ZSM-5) with a primary product of monocyclic alkane (cyclopentane, cyclohexane), Pd@meso-ZSM-5 shows much higher catalytic efficiency for the bicyclic alkanes synthesis, which was previously unattainable in the conventional two-step synthesis route. Controlled experiments and detailed characterizations show that mesoporosity provides sufficient space for the generation and diffusion of large molecular intermediates, and the intimate acid-Pd interface promotes the conversion of intermediates. As a result, this work proposes a design strategy for a mesoporous zeolite-encapsulated metal catalyst, which efficiently provides cooperative acid-hydrogenation catalysis.

09 BIOMASS FUELS↗
DOE OSTI2023

Robust Parameter Design on Dual Stochastic Response Models With Constrained Bayesian Optimization

In engineering system design, minimizing the variations of the quality measurements while guaranteeing their overall quality up to certain levels, namely the robust parameter design (RPD), is crucial. Recent works have dealt with the design of a system whose response-control variables relationship is a deterministic function with a complex shape and function evaluation is expensive. In this work, we propose a Bayesian optimization method for the RPD of stochastic functions. Dual stochastic response models are carefully designed for stochastic functions. The heterogeneous variance of the sample mean is addressed by the predictive mean of the log variance surrogate model in a two-step approach. We establish an acquisition function that favors exploration across the feasible and optimality-improvable regions to effectively and efficiently solve the stochastic constrained optimization problem. Further, the performance of our proposed method is demonstrated by the extensive numerical and case studies. Note to Practitioners-Many manufacturing processes involve undesirable variations, which create variations in the final products. For example, many emerging manufacturing processes, such as nanomanufacturing, involve complex physical and chemical dynamics and transformation, creating variations in the manufacturing output. In such processes, it is crucial to design the manufacturing processes or products so that they have minimum variations in their quality. Meanwhile, it is also important to maintain the overall quality of the designed processes or products. Furthermore, acquiring data from many advanced manufacturing processes is often very costly, especially in the designing stage. In this work, we propose a data-driven method that automatically finds the best setting of manufacturing processes or products with the minimum variations of quality and a given constraint on the average quality satisfied. Our proposed method is used before conducting every experiment; It analyzes the historical data from previous experiments and provides a setting to be used in the next experiment. Our proposed method efficiently utilizes the historical data, and thus finds the best robust setting by conducting only a small number of experiments.

42 ENGINEERING↗
DOE OSTI2023

Lead leaching and electrowinning in acetic acid for solar module recycling

It is imperative to recover lead (Pb) contained in end-of-life solar modules. In this paper, a two-step leaching and electrowinning process using acetic acid is investigated for Pb recovery. Acetic acid with hydrogen peroxide can dissolve Pb quickly and, under some conditions, in a matter of minutes. Pb electrowinning has been successfully demonstrated from aqueous solutions of 0.009 M lead(II) acetate with 0–10% v/v acetic acid. Pb-containing deposits are found on both the copper cathode and graphite anode. X-ray diffraction, energy-dispersive X-ray spectroscopy, and Fourier transform infrared spectroscopy confirm the presence of metallic Pb and Pb(II) oxide (PbO) co-deposits on the cathode. Further, there is also the formation of lead subacetate on the cathode under certain conditions. On the anode, the deposit consists of lead(IV) oxide and superoxide (PbO 2 and Pb 1–x O 2 ). A Pb recovery rate of 99% is achieved in 0.009 M lead(II) acetate solutions with 10% v/v acetic acid by applying a reduction potential of either –0.8 V or –1.0 V versus the silver/silver chloride reference electrode for 24h. Pb leaching with acetic acid is also demonstrated from milled silicon solar modules.

14 SOLAR ENERGY↗
DOE OSTI2023

Mending cracks atom-by-atom in rutile TiO2 with electron beam radiolysis

Abstract Rich electron-matter interactions fundamentally enable electron probe studies of materials such as scanning transmission electron microscopy (STEM). Inelastic interactions often result in structural modifications of the material, ultimately limiting the quality of electron probe measurements. However, atomistic mechanisms of inelastic-scattering-driven transformations are difficult to characterize. Here, we report direct visualization of radiolysis-driven restructuring of rutile TiO 2 under electron beam irradiation. Using annular dark field imaging and electron energy-loss spectroscopy signals, STEM probes revealed the progressive filling of atomically sharp nanometer-wide cracks with striking atomic resolution detail. STEM probes of varying beam energy and precisely controlled electron dose were found to constructively restructure rutile TiO 2 according to a quantified radiolytic mechanism. Based on direct experimental observation, a “two-step rolling” model of mobile octahedral building blocks enabling radiolysis-driven atomic migration is introduced. Such controlled electron beam-induced radiolytic restructuring can be used to engineer novel nanostructures atom-by-atom.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Formation and surface melting of nanoparticle superlattices in a solution

The wisdom in the saying of “There are no two snowflakes alike” lies in the importance of history or kinetic pathways in the phase transitions of solids. Likewise, “artificial solids,” namely superlattices consisting of functional nanoparticles, have lattice size, surface morphology, crystallinity, symmetry, and structural reconfiguration (for example, transition into a disordered state) highly dependent on the kinetic pathways as the nanoparticles interact with each other in solution [1]. Great progresses have been made in understanding the formation pathways of superlattices using liquid-phase transmission electron microscopy (TEM) [2-4]. For example, by tracking single nanoparticle’s trajectories, especially aided by U-net neural network-based machine learning, previous studies mapped the fundamental nanoparticle interactions at nanometer resolution [5]. Nonclassical, two-step nucleation pathway has also been elucidated in the system of nanoprisms, by optimizing protocols such as loading nanoparticle suspensions over the supersaturation threshold and minimizing particle‒substrate interaction [2]. Surface morphologies or exposed facets of superlattices have been shown to follow the principles of Wulff construction rule, where the facet-dependent surface energy can be measured based on the capillary wave theory [4]. However, the reverse process of crystallization of superlattices, the conversion from crystalline to disordered state, has been much less explored. On one hand, the melting of nanoparticle superlattices can provide a preferred pathway to induce structural reorganization or shuffling of building blocks for them to transform into different types of crystal structures. On the other hand, understanding nanoscale superlattice melting and comparing such behaviors with the prevailing surface melting theories developed for atomic/molecular solids can provide a potent way to engineer phase transitions of supra- and hierarchical structures constructed from nanoscale entities (e.g., DNA-coated nanoparticles, proteins), for their applications in reprogrammable and switchable materials with multifunctional properties [6, 7]. The experimental challenges to observe melting of superlattices are twofold. Practically it is difficult to load the initial superlattice form, in an intact manner, into the highly confined liquid-phase TEM chamber for in-situ observation. Here, the triggering of melting also needs meticulous manipulation of nanoparticle concentration, interparticle interaction, and solution environment.

Kim, Ahyoung↗
DOE OSTI2022

The role of amorphous ZIF in ZIF-8 crystallization kinetics and morphology

Understanding the composition and structure of amorphous precursor phases is fundamental for elucidating two-step crystallization mechanisms and designing shape- and size-controlled nanomaterials. However, that understanding is largely lacking for metal–organic framework compounds despite their growing significance as functional materials. Here, in this study, we report the crystallization of zeolite imidazolate frameworks-8 (ZIF-8, Zn(C 4 H 5 N 2 ) 2 ) via an amorphous ZIF (am-ZIF) solid precursor phase with a rough stoichiometric composition of Zn(C 4 H 5 N 2 ) 1.78 (C 4 H 6 N 2 ) 0.17 (CH 3 COO) 0.22 . The formation of am-ZIF is attributed to the incomplete deprotonation of 2-Methylimidazole (HmIm) and the involvement of the hydrogen bond between CH 3 COO– and –HN, which can further transform into the dense Dia(Zn) structure with a diamondoid crystal topology in pure water. Taking am-ZIF as a precursor, the tunable dissolution and recrystallization kinetics of am-ZIF into ZIF-8, due to the addition of EtOH and CTAB, allows the selective fabrication of dodecahedral, cubic, and hollow ZIF-8. Overall, an in-depth understanding of the differences in composition and structure of am-ZIF from ZIF-8 and the resulting crystallization kinetics suggests a novel approach to designing metal–organic frameworks with controlled crystal morphology.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Polyhalohydrins: Investigating Vicinal Functionalities by Ring-Opening of Epoxides on Polyolefins

Halohydrins are functional groups that are underexplored in polymer science. This study synthesized and examined structure–property relationships of halohydrin-functionalized polymers derived from polycyclooctene (PCOE), which was obtained via ring-opening metathesis polymerization (ROMP). The polyhalohydrins, including polychlorohydrin, polybromohydrin, and polyiodohydrin, were produced through a two-step process involving epoxidation of PCOE followed by epoxide ring-opening using hydrochloric, hydrobromic, or hydroiodic acid. These stereoirregular and regioirregular polymers are amorphous as measured by differential scanning calorimetry and X-ray scattering. Lap joint shear testing revealed an enhanced adhesive performance in polychlorohydrin and polybromohydrin, with the former demonstrating nearly three times the ultimate shear stress compared to a model polyethylene, hydrogenated PCOE. Additionally, contact angle measurements and surface free energy analysis showed an increase in hydrophilicity and polarity from iodine- to bromine- to chlorine-functionalized polyhalohydrins, aligning with trends in adhesion strength. Furthermore, these results underscore the potential of halohydrin functionalization as a versatile approach for tuning surface properties, offering new opportunities for polymer-to-polymer transformations.

Functional groups↗
DOE OSTI2021

Pushing the efficiency limit of low-cost, industrially relevant Si solar cells to > 22.5% by advancing cell structures and technology innovations (Final Report)

The overall objective of this program is to achieve ~23% bifacial n-type cell efficiencies by developing and implementing optimized homogeneous or selective boron (B) emitter on front and tunnel oxide passivated contact (TOPCon) on rear side, in combination with advanced fine-line screen-printing metallization with floating busbars. During this research project, first we developed a technology roadmap to drive the 21% n-PERT cell efficiency from 21% to 23% by transforming the cell design to n-TOPCon and establishing the requirements for each layer, including B emitter, rear n-TOPCon, n-base Si and screen-printed contacts. Next, consistent with our roadmap, we developed advanced homogeneous implanted B emitter (150-180 Ω/⌫) passivated with ALD Al 2 O 3 layer capped with PECVD SiN x /SiO x double-layer antireflection coating This gave a very low recombination current density of 10-15 fA/cm 2 prior to metallization. In addition, we demonstrated metallized recombination current density of ~31 fA/cm 2 for this advanced homogeneous B emitter with industrial screen-printed, fire-through contacts with 40 μm wide grid lines, floating busbars and implementation of an advanced Ag-Al paste which resulted in local or reduced area metal-Si contact under the grid lines with virtually no emitter surface etching. This paste reduced the full area metallized J oe,metal from >1100 fA/cm 2 to ~700 fA/cm 2 . We also developed novel processes for the formation of p + /p ++ selective B emitter by a) single B diffusion with selective etch back and b) two-steps diffusion with implanted B in field region and APCVD B diffusion under the metal grid. We achieved very low un-metallized recombination current density (J 0 ) of ~18 fA/cm 2 for the selective p ++ p + emitters (30/150 Ω/⌫) and metallized J 0 of ~28 fA/cm 2 with ~3% screen-printed metal contact to p ++ regions. Next, we developed the technology for n-TOPCon by growing phosphorus-doped LPCVD and PECVD poly-Si on top of ~ 15Å chemically grown (NAO) tunnel oxide. After an optimized anneal at 875 °C for 30 min, passivated n-TOPCon have unmetallized J 0 of ~ 5 fA/cm 2 which went down further to ~ 1 fA/cm 2 after a 700 Å SiN x capping layer and simulated contact firing cycle at 770 °C. After screen-printed fire-through metallization on this n-TOPCon with ~13% metal coverage, metallized J 0 value increased to only ~5 fA/cm 2 which is among the lowest reported value to the best of our knowledge for screen-printed metallization. Finally, we integrated all the above technology innovations and enhancements and demonstrated low-cost manufacturable screen-printed n-TOPCon bifacial Si solar cell with ~23% efficiencies. Based on the experimental and theoretical understanding developed in this project, we have developed a new technology roadmap that shows that implementation of busbarless contacts, 10-20 ms bulk lifetime Si, and selective B emitter or selective TOPCon on the front can drive ~23% efficient cells achieved in this research to ~25% at low-cost.

14 SOLAR ENERGY↗
DOE OSTI2022

Investigation of twin growth mechanisms in precipitate hardened AZ91

Here, in this work, an elasto-viscoplastic fast-Fourier-transform (EVP-FFT) model with a dislocation-density (DD) based hardening law is employed to study the growth of a {10$\bar{1}$2} tensile twin that is blocked by basal-precipitates in precipitate-hardened AZ91 magnesium alloy. It is frequently reported that twin growth is hindered in precipitate-hardened Mg alloys; however, thick twin domains are often observed experimentally in these material systems. Detailed numerical investigation of deformation twinning starting from an early propagation stage, before twin growth, reveals that the stress fields that result from two sequentially propagated twins co-impinging on a precipitate relaxes the twin back stress locally and promotes twin growth at the twin-precipitate junction. Based on these findings, a two-step growth mechanism is proposed for twins arrested by precipitates. In the first step, the interaction of a twin tip with a precipitate develops a stress concentration on the other side of the precipitate, prompting the formation of a second twin. Subsequently, the back stresses associated with the first twin are relaxed by the formation of the second twin, allowing the first twin to grow at the twin-precipitate junction and eventually engulf the precipitate. This mechanism suggests that twin growth can be achieved locally with minimal additional external forces, explaining how relatively large twin domains can develop even in the presence of arrays of precipitates.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Computational Predictions of the Hydrolysis of 2,4,6-Trinitrotoluene (TNT) and 2,4-Dinitroanisole (DNAN)

Hydrolysis is a common transformation reaction that can affect the environmental fate of many organic compounds. In this study, three proposed mechanisms of alkaline hydrolysis of 2,4,6-trinitrotoluene (TNT) and 2,4-dinitroaniline (DNAN) were investigated with plane-wave density functional theory (DFT) combined with ab initio and classical molecular dynamics (AIMD/MM) free energy simulations, Gaussian basis set DFT calculations, and correlated molecular orbital theory calculations. Most of the computations in this study were carried out using the Arrows web based tools. For each mechanism: Meisenheimer complex formation, nucleophilic aromatic substitution, and proton abstraction reaction energies and activation barriers were calculated for the reaction at each relevant site. For TNT, it was found that the most kinetically favorable first hydrolysis steps involve Meisenheimer complex formation by attachment of OH$^{-}$ at the C1 and C3 arene carbons and proton abstraction from the methyl group. The nucleophilic aromatic substitution reactions at the C2 and C4 arene carbons were found to be thermodynamically favorable. However, the calculated activation barriers were slightly lower than previous studies, but still found to be $\Delta$G$^{\ddagger} \approx 18$ kcal/mol using PBEo AIMD/MM free energy simulations, suggesting the reactions are not kinetically significant. For DNAN, the barriers of nucleophilic aromatic substitution were even greater ($\Delta$G$^{\ddagger} > 29$ kcal/mol PBEo AIMD/MM). Further, the most favorable hydrolysis reaction for DNAN was found to be a two-step process in which the hydroxyl first attacks the C1 carbon to form a Meisenheimer complex at the C1 arene carbon C1-(OCH$_3$)OH$^{-}$, subsequently, the methoxy anion (-OCH$_3$) at the C1 arene carbon dissociates and the proton shuttles from the C1-OH to the dissociated methoxy group, resulting in methanol and an aryloxy anion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Metastability and Ostwald step rule in the crystallisation of diamond and graphite from molten carbon

Abstract Experimental challenges in determining the phase diagram of carbon at temperatures and pressures near the graphite-diamond-liquid triple point are often related to the persistence of metastable crystalline or glassy phases, superheated crystals, or supercooled liquids. A deeper understanding of the crystallisation kinetics of diamond and graphite is crucial for effectively interpreting the outcomes of these experiments. Here, we reveal the microscopic mechanisms of diamond and graphite nucleation from liquid carbon through molecular simulations with first-principles machine learning potentials. Our simulations accurately reproduce the experimental phase diagram of carbon near the triple point and show that liquid carbon crystallises spontaneously upon cooling. Metastable graphite crystallises in the domain of diamond thermodynamic stability at pressures above the triple point. Furthermore, whereas diamond crystallises through a classical nucleation pathway, graphite follows a two-step process in which low-density fluctuations forego ordering. Calculations of the nucleation rates of the two competing phases confirm this result and reveal a manifestation of Ostwald’s step rule, where the strong metastability of graphite hinders the transformation to the stable diamond phase. Our results provide a key to interpreting melting and recrystallisation experiments and shed light on nucleation kinetics in polymorphic materials with deep metastable states.

Science & Technology - Other Topics↗
DOE OSTI2023

Bi-Level Linear Programming Model for Automatic Load Shedding: A Distributed Wide-Area Measurement System-based Solution

Load shedding is currently implemented as a two-step based approach. In the first step, manual load shedding is taken place, were system operators, using estimates, inform distribution utilities of predicted stressful conditions. Information provided include the potential use of energy reserves, as well as load shedding amount. In a second step, automatic load shedding is done. The latter is realized using protection relays. While considering frequency variation, pre-defined values of load to be shed and correspondent number of stages for such to be realized are transformed into relay settings. Under-frequency protection relays use only local measurements towards decision making, thus operate in a decentralized architecture. Decision making is done in milliseconds plus breaker time. While this approach has provided much system reliability, considering the new smart grid paradigm, where system dynamics are much faster due to increasing renewable resources penetration, in some operating conditions it will generate sub-optimal solutions, such as islanding. Phasor measurement units provide a source of information which can be useful for this problem. Centralized architecture-based solutions for automatic load shedding, as present in the state-of-the-art, require though total processing times which are not acceptable for real-life implementation. In this work, considering the above, a bi-level linear programming model is presented. The model is implemented considering a distributed architecture while leveraging phasor measurement units data. The upper-level model estimates the current system state. Results of this model are embedded in a lower-level model, which decision variables are the location and load value to be shed. Easy-to-implement model, built-on the classic weighted least squares solution, highlight potential aspects towards real-life applications.

Bretas, Arturo Suman↗