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At least 181 records · Page 10

Acceleration of Crystallization Kinetics in Ge‐Sb‐Te‐Based Phase‐Change Materials by Substitution of Ge by Sn

Abstract Thin films of (Ge 1– x Sn x ) 8 Sb 2 Te 11 are prepared to study the impact of Sn‐substitution on properties relevant for application in phase‐change memory, a next‐generation electronic data storage technology. It is expected that substitution decreases the crystallization temperature, but it is not known how the maximum crystallization rate is affected. Ge 8 Sb 2 Te 11 is chosen from the (GeTe) y (Sb 2 Te 3 ) 1– y system of phase‐change materials as a starting point due to its higher crystallization temperature as compared to the common material Ge 2 Sb 2 Te 5 . In situ X‐ray diffraction at 5 K min −1 heating rate is performed to determine the crystallization temperature and the resulting structure. To measure the maximum crystallization rate, femtosecond optical pulses that heat the material repetitively and monitor the resulting increase of optical reflectance are used. Glasses over the entire composition range are prepared using a melt‐quenching process. While at x = 0, 97, subsequent pulses are required for crystallization, one single pulse is enough to achieve the same effect at x = 0.5. The samples are further characterized by optical ellipsometry and calorimetry. The combined electrical and optical contrast and the ability to cycle between states with single femtosecond pulses renders Ge 4 Sn 4 Sb 2 Te 11 promising for photonics applications.

Zalden, Peter↗

Dynamic experiments to study the α - ε phase transition in cerium

The ability to understand and predict the response of matter at extreme conditions requires knowledge of a material’s equation-of-state including the location of phase boundaries, transition kinetics, and the evolution of material strength. Cerium is a material with a complex phase diagram that continues to attract significant scientific interest. Recent dynamic experiments have provided information on the low-pressure γ–α phase transition, sound speed, and Hugoniot data for the higher-pressure α phase, as well as the incipient shock melt transition. Despite these efforts, there are still regions of the phase diagram that are largely unexplored dynamically, including the high-pressure region below the melt boundary. Along a room temperature isotherm, diamond anvil cell data report a transition to the ϵ phase between 13 and 17 GPa. At higher temperatures, similar diamond anvil cell data show significant disagreement regarding the existence, location, and slope of the ϵ-phase boundary. In this work, double-shock loading was used to access the α–ϵ region of the phase diagram to obtain equation-of-state information and to determine the location of the ϵ-phase boundary for shock loading.

74 ATOMIC AND MOLECULAR PHYSICS↗

Modeling the Impact of the Organic Aerosol Phase State on Multiphase OH Reactive Uptake Kinetics and the Resultant Heterogeneous Oxidation Timescale of Organic Aerosol in the Amazon Rainforest

Accurate predictions of chemical lifetime, i.e., oxidation timescale and change in the mass of organic aerosols (OAs) in atmospheric models, are critical to quantify the impacts of OA on aerosol–cloud interactions, radiative forcing, and air quality. The heterogeneous oxidation of OA by hydroxyl (OH) radicals is a key process governing OA mass changes during their oxidation. Recently, laboratory observations of the OH uptake coefficient (γ OH ) and heterogeneous reaction rate (k het,OH ) for different OA systems with varying phase states have been combined to develop a new parameterization of γ OH and k het,OH as a function of the OA phase state, i.e., viscosity (η OA ). Here, in this work, we use a recently published viscosity prediction framework to analyze the new γ OH and k het,OH parameterization with a box model. Subsequently, we implement this box model to predict γ OH and k het,OH over the Amazon rainforest in the dry-to-wet transition season with both significant biomass burning and biogenic influences. Relevant parameters within our box model are specified based on detailed regional model simulations over the Amazon using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). η OA is predicted as a function of species volatility, OA composition (including water uptake) along with ambient relative humidity (RH), and temperature. Based on ambient conditions simulated by WRF-Chem over the entire atmospheric column, we use the box model to predict the upper bounds of the heterogeneous oxidation timescale of OA. Based on previous laboratory measurements, we assume that this heterogeneous OH oxidation causes fragmentation (carbon loss) of OA, followed by the evaporation of the fragmented molecules that results in the exponential decay of OA. We predict that the oxidation timescale of OA is ~1 month near the Earth’s surface in the pristine Amazonian background because of low OH concentrations. But OA is oxidized more rapidly within urban and wildfire plumes near the Earth’s surface with an order of magnitude higher OH concentrations compared to the pristine background, causing the simulated oxidation timescale of OA to be much shorter, ~3–4 days. At 3–5 km altitudes where biomass burning OA is predicted to be semisolid, the heterogeneous oxidation timescale is estimated as ~6 days to 3 weeks and decreases with increasing OH concentrations within plumes. We show that the simulated mass loss of OA is strongly size-dependent, where smaller particles oxidize more rapidly compared to larger particles due to their greater per-particle surface area-to-volume ratio. Increasing urbanization and deforestation in the Amazon in the future might increase OH concentrations in the background Amazon, causing faster oxidation of OA. At higher altitudes above liquid clouds, especially in the upper troposphere where temperatures approach ~250 K, future measurements are needed to reduce the uncertainties related to the mass loss of OA at colder temperatures and low relative humidity conditions due to its heterogeneous OH oxidation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Learning heterogeneous reaction kinetics from X-ray videos pixel by pixel

Reaction rates at spatially heterogeneous, unstable interfaces are notoriously difficult to quantify, yet are essential in engineering many chemical systems, such as batteries and electrocatalysts. Experimental characterizations of such materials by operando microscopy produce rich image datasets, but data-driven methods to learn physics from these images are still lacking because of the complex coupling of reaction kinetics, surface chemistry and phase separation. Here we show that heterogeneous reaction kinetics can be learned from in situ scanning transmission X-ray microscopy (STXM) images of carbon-coated lithium iron phosphate (LFP) nanoparticles. Combining a large dataset of STXM images with a thermodynamically consistent electrochemical phase-field model, partial differential equation (PDE)-constrained optimization and uncertainty quantification, we extract the free-energy landscape and reaction kinetics and verify their consistency with theoretical models. We also simultaneously learn the spatial heterogeneity of the reaction rate, which closely matches the carbon-coating thickness profiles obtained through Auger electron microscopy (AEM). Across 180,000 image pixels, the mean discrepancy with the learned model is remarkably small (<7%) and comparable with experimental noise. Our results open the possibility of learning nonequilibrium material properties beyond the reach of traditional experimental methods and offer a new non-destructive technique for characterizing and optimizing heterogeneous reactive surfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Intermolecular Interactions in Direct Air Capture Materials: Insights from Charge Density Analysis

Direct air capture (DAC) materials enable the removal of CO 2 from the atmosphere, but improving their efficiency requires a detailed understanding of the intermolecular interactions that govern CO 2 sorption and release. Here, we present an experimental electron density study of methylglyoxal-bis(iminoguanidine) (MGBIG), a promising DAC material, using high-resolution X-ray and neutron diffraction data combined with quantum crystallographic analysis. This approach bridges theoretical and experimental data by quantifying electron density distributions and revealing how hydrogen bonds stabilize CO 2 -derived carbonate phases and may influence the desorption behavior. We identify distinct hydrogen-bonding environments in two crystalline carbonate phases: P1, a transient kinetic product, and P3, a thermodynamically stable phase. Multipolar refinement and electrostatic potential and multipole moment calculations precisely map electron density distributions, revealing key hydrogen bonds involved in CO 2 capture. Topological analysis of electron density highlights a cooperative hydrogen-bonding network in the thermodynamically favored P3 phase, where enhanced electron density delocalization and water-mediated interactions contribute to a more stable lattice. Energetic analyses confirm that stronger hydrogen bonding networks enhance the stability of P3 with a binding energy of −607.0 kJ/mol and greater lattice stability (−847.3 kJ/mol) compared to P1 (−302.5 and −571.0 kJ/mol, respectively). Electrostatic potential maps further illustrate polarization patterns that may influence the stability of the binding of CO 2 and release conditions. These findings establish a direct experimental framework for linking electron density distributions to intermolecular interactions in DAC materials, providing a rational design strategy for optimizing sorbents with improved CO 2 capture efficiency and reduced energy demands.

Electron density↗

Thermodynamics and kinetics of core-shell versus appendage co-precipitation morphologies

What determines precipitate morphologies in co-precipitating alloy systems? We focus on alloys of two precipitating phases, with the fast-precipitating phase acting as heterogeneous nucleation sites for a second phase manifesting slower kinetics. Kinetic lattice Monte Carlo simulations show that the interplay between interfacial and ordering energies, plus active diffusion paths, strongly affect the selection of core-shell verses appendage morphologies. We study a FeCuMnNiSi alloy using the combination of atom probe tomography and simulations, and show that the ordering energy reduction of the MnNiSi phase heterogeneously nucleated on a pre-existing copper-rich precipitate exceeds the energy penalty of a predominantly Fe/Cu interface, leading to initial appendage, rather than core-shell, formation. Diffusion of Mn, Ni and Si around and through the Cu core towards the ordered phase results in subsequent appendage growth. We further show that in cases with higher primary precipitate interface energies and/or suppressed ordering, the coreshell morphology is favored.

Shu, Shipeng↗

A highly wear resistant nanostructured bainitic steel with accelerated transformation kinetics

A coupled Calculation of Phase Diagrams (CALPHAD), machine learning, and data mining approach was used to design a new, highly wear-resistant nanostructured bainitic steel. Arc melting of the designed compositions, dilatometry, and advanced microscopy indicate that the designed steel had a nanoscale dual-phase structure of ferrite and austenite (approximately 50 nm) with kinetics 7x faster for the onset of bainite and 2x faster for complete transformation. Under dry sliding conditions using the current state-of-the-art AISI 52100 bearing steel as the counter sample, the designed steel little to no wear, indicating its potential for applications in high-wear service conditions.

36 MATERIALS SCIENCE↗

Stability Analysis of Parameter Varying Genetic Toggle Switches Using Koopman Operators

The genetic toggle switch is a well known model in synthetic biology that represents the dynamic interactions between two genes that repress each other. The mathematical models for the genetic toggle switch that currently exist have been useful in describing circuit dynamics in rapidly dividing cells, assuming fixed or time-invariant kinetic rates. There is a growing interest in being able to model and extend synthetic biological function for growth conditions such as stationary phase or during nutrient starvation. As cells transition from one growth phase to another, kinetic rates become time-varying parameters. In this paper, we propose a novel class of parameter varying nonlinear models that can be used to describe the dynamics of genetic circuits, including the toggle switch, as they transition from different phases of growth. We show that there exists unique solutions for this class of systems, as well as for a class of systems that incorporates the microbial phenomena of quorum sensing. Further, we show that the domain of these systems, which is the positive orthant, is positively invariant. We also showcase a theoretical control strategy for these systems that would grant asymptotic monostability of a desired fixed point. We then take the general form of these systems and analyze their stability properties through the framework of time-varying Koopman operator theory. A necessary condition for asymptotic stability is also provided as well as a sufficient condition for instability. A Koopman control strategy for the system is also proposed, as well as an analogous discrete time-varying Koopman framework for applications with regularly sampled measurements.

Harrison, Jamiree (ORCID:0000000265351579)↗

Precipitate growth kinetics under inhomogeneous concentration fields using a phase-field model

We investigate precipitation dynamics in the presence of a local solute gradient using phase-field simulations. During the homogenization heat treatment of the solidified Inconel 718 alloy, high Nb concentration within the Laves phases or at the core of the secondary arms results in Nb diffusion into the γ matrix. The volume fraction and spatial distribution of precipitation during subsequent annealing can be controlled by tailoring the Nb concentration gradient in the matrix during homogenization. We use a surrogate Ni-Fe-Nb alloy for Inconel 718 to explore the growth dynamics of δ precipitates related to the local Nb concentration levels. The simulations indicate that in the presence of a Nb concentration gradient the growth rate of δ precipitates is higher than in a matrix of uniform average Nb concentration. The higher growth rate is a result of the higher local thermodynamic driving force at the interface between the solute-rich matrix and the δ interface. Here, we propose a phenomenological model to describe the diffusion-controlled growth kinetics of the δ phase under a solute concentration gradient.

36 MATERIALS SCIENCE↗

Single-Well Push–Pull Tracer Test Analyses to Determine Aquifer Reactive Transport Parameters at a Former Uranium Mill Site (Grand Junction, Colorado)

At a former uranium mill site where tailings have been removed, prior work has determined several potential ongoing secondary uranium sources. These include locations with uranium sorbed to organic carbon, uranium in the unsaturated zone, and uranium associated with the presence of gypsum. To better understand uranium mobility controls at the site, four single-well push–pull tests (with a drift phase) were completed with the goal of deriving aquifer flow and contaminant transport parameters for inclusion in a future sitewide reactive transport model. This goes beyond the traditional use of a constant sorption distribution coefficient (K d ) and allows for the evaluation of alternative remedial injection fluids, which can produce variable K d values. Dispersion was first removed from the resulting data to determine possible reactions before conducting reactive transport simulations. These initial analyses indicated the potential need to include cation exchange, uranium sorption, and gypsum dissolution. A reactive transport model using multiple layers to account for partially penetrating wells was completed using the PHT-USG reactive transport modeling code and calibrated using PEST. The model results quantify the hydraulic conductivity and dispersion parameters using the injected tracer concentrations. Uranium sorption, cation exchange, and gypsum dissolution parameters were quantified by comparing the simulated versus observed geochemistry. All simulations required some cation exchange and calcite equilibrium, and one simulation required gypsum dissolution to improve the model fit for calcium and sulfate. Uranium sorption parameters were not strongly influenced by the other parameter values but were highly influenced by uranium concentrations during the drift phase, with possible kinetic rate limitations. Thus, a future recommendation for such push–pull tests is to collect more geochemical data during the drift phase. The final uranium sorption parameters were within the range of values determined from prior column testing. The flow and transport parameters derived from these single-well push–pull tests will provide initial parameters for any future sitewide reactive transport model.

54 ENVIRONMENTAL SCIENCES↗

Learning heterogeneous reaction kinetics from X-ray movies pixel-by-pixel

Reaction rates at spatially heterogeneous, unstable interfaces are notoriously difficult to quantify, yet are essential in engineering many chemical systems, such as batteries 1 and electrocatalysts 2. Experimental characterizations of such materials by operando microscopy produce rich image datasets 3–6, but data-driven methods to learn physics from these images are still lacking because of the complex coupling of reaction kinetics, surface chemistry and phase separation 7. Here we show that heterogeneous reaction kinetics can be learned from in situ scanning transmission X-ray microscopy (STXM) images of carbon-coated lithium iron phosphate (LFP) nanoparticles. Combining a large dataset of STXM images with a thermodynamically consistent electrochemical phase-field model, partial differential equation (PDE)-constrained optimization and uncertainty quantification, we extract the free-energy landscape and reaction kinetics and verify their consistency with theoretical models. We also simultaneously learn the spatial heterogeneity of the reaction rate, which closely matches the carbon-coating thickness profiles obtained through Auger electron microscopy (AEM). Across 180,000 image pixels, the mean discrepancy with the learned model is remarkably small (<7%) and comparable with experimental noise. Our results open the possibility of learning nonequilibrium material properties beyond the reach of traditional experimental methods and offer a new non-destructive technique for characterizing and optimizing heterogeneous reactive surfaces.

Chueh, William↗

Adsorption Equilibrium, Kinetics, and Column Breakthrough Data of Acetic Acid, Butyric Acid, and Lactic Acid on IRN-78 Ion-exchange Resin at Initial pH ~3 – 7 and Temperature 25 – 55 °C

This work presents systematic aqueous-phase adsorption equilibrium, kinetics, and column breakthrough measurements with three key biointermediates that are common compounds in many bioprocesses. Adsorption equilibrium experiments were carried out with acetic acid, butyric acid, and lactic acid on a commercial ion-exchange resin, Amberlite IRN-78, at wide ranges of acid concentration (8-500 mmol/L), initial pH (similar to 3-7), and temperature (25-55 degrees C), simulating the effluent characteristics from different fermenter operations. The kinetics and column breakthrough experiments were conducted at an initial pH of 6 and a concentration of 200 mmol/L. The equilibrium study shows a higher loading at the initial pH < pK(a) and a lower loading at the initial pH > pK(a). Overall removal varies between 16 and 99% depending on the initial pH, temperature, and organic acid concentration and type. The study further indicates monolayer adsorption at the equilibrium pH > 10 and multilayer adsorption at the equilibrium pH < 6. The thermodynamic modeling of adsorption isotherm data was carried out using Langmuir and Freundlich isotherms. IRN-78 presents fast adsorption kinetics as the maximum loading was attained in <= 10 min and nearly the same breakthrough time for all three organic acids involved in this study.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Effect of magneto-mechanical synergism in the process-structure correlation in Fe–C alloys: A phase-field modeling approach

Applied magnetic fields can alter phase equilibria and kinetics in steels; however, quantitatively resolving how magnetic, chemical, and elastic driving forces jointly influence the microstructure remains challenging. We develop a quantitative magneto-mechanically coupled phase-field model for the Fe–C system that couples a CALPHAD-based chemical free energy with demagnetization-field magnetostatics and microelasticity. Here, the model reproduces single- and multi-particle evolution during the α → γ inverse transformation at 1023 K under external fields up to 20 T, including ellipsoidal morphologies observed experimentally at 8 T. Chemically driven growth is isotropic; a magnetic interaction introduces an anisotropic driving force that elongates γ precipitates along the field into ellipsoids, while elastic coherency promotes faceting, yielding elongated cuboidal or “brick-like” particles under combined magneto-elastic coupling. Growth kinetics increase with C content, and decrease with field strength and misfit strain. Multi-particle simulations reveal dipolar interaction-mediated coalescence for field-parallel neighbors and ripening for field-perpendicular neighbors. Incorporating field-dependent diffusivity from experiment slows kinetics as expected; a first-principles-motivated anisotropic diffusivity correction is estimated to be small (<2%). These results establish a process-structure link for magnetically assisted heat treatments of Fe–C alloys and provide guidance for microstructure control via chemo-magneto-mechanical synergism.

Magnetic field↗

Unexpected Kinetic Solvent Effects Enhance Activity and Selectivity in Biphasic Systems

Biphasic dehydration of fructose to 5-hydroxymethylfurfural (HMF) has shown unprecedented increases in productivity, but a mechanistic understanding is lacking. Herein, we couple fast experimental reaction kinetics, multiscale modeling (phase behavior, classical molecular dynamics(MD), and quantum mechanics/molecular mechanics MD), in situ sampling, and IR and 13 C-NMR spectroscopy to elucidate the complex effects of nonpolar extracting organic solvents on the kinetics of fructose dehydration. We show that these organic solvents can reach significant mutual solubility with water at reaction temperatures, enabling the partition of the sugar and catalyst into the extracting phase. In the organic-rich environment, the dehydration of fructose proceeds faster and more selectively than in water due to increased relative abundance of the reactive furanose isomer, enhanced water–catalyst–substrate interactions driven by nanophase separation, and higher product stability stemming from preferential solvation. Furthermore, we demonstrate that these solvent effects impact other critical biphasic reactions in biomass upgrading and provide qualitative principles for solvent selection.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗