Initial Chemical Composition Research Articles

One-pot ternary sequential reactions for photopatterned gradient multimaterials

One-pot ternary sequential reactions for photopatterned gradient multimaterials

Investigation of molecular changes in wine during storage in refrigerated cabinets

Investigation of molecular changes in wine during storage in refrigerated cabinets

Study on Factors Hindering the Single-Phase Formation of Divalent-Ion-Stabilized W-Type Ferrites

Me-substituted W-type ferrites (AMe2Fe16O27 with A = Sr, Ba, …, and Me = Co, Ni, Zn, Mg, …) can be obtained by standard solid state reaction but always contain secondary phases. Phase stability of SrMe2Fe16O27 with Me = Co, Ni, Zn, and Mg sintered in various oxygen pressures of pO2 = 0.2, 1, 10, and 387 atm were investigated using X-ray diffraction analysis, wavelength dispersive X-ray (WDX) analysis, and transmission electron microscopy (TEM). WDX analysis revealed that the W-type ferrites are described as SrMe2−δFe16+δO27 because Fe3+ is partially reduced to Fe2+ even when synthesis is initiated from SrMe2Fe16O27. Increasing the oxygen pressure suppresses the reduction of Fe3+ and the formation of the secondary phases. In addition, TEM analysis shows that the SrCo2Fe16O27 single crystal is free of stacking faults. We conclude that the single-phase formation of the Me-substituted W-type ferrites is hampered by the discrepancy between initial and actual chemical composition caused by the appearance of Fe2+.

Formation of a 10 A phase with halloysite structure under hydrothermal conditions with varying initial chemical composition

Formation of a 10 A phase with halloysite structure under hydrothermal conditions with varying initial chemical composition

Hard-Templated Porous Niobia Films for Optical Sensing Applications

Porous Nb2O5 films obtained by a modified hard-template method were studied and their optical and sensing properties were optimized in order to find applications in chemo-optical sensing. Porous films were prepared by following three steps: liquid mixing of niobium sol and SiO2 colloids in different volume fractions, thermal annealing of spin-coated films for formation of a rigid niobia matrix, and selective removal of silica phase by wet etching thus generating free volume in the films. The morphology and structure of the films were studied using transmission electron microscopy and selected area electron diffraction, while their optical and sensing properties were estimated using UV-VIS-NIR reflectance measurements in different ambiences such as air, argon and acetone vapors and nonlinear curve fitting of the measured reflectance spectra. Bruggeman effective medium approximation was applied for determination of the volume fraction of silica and air in the films, thus revealing the formation of porosity inside the films. For further characterization of composite films, their water contact angles were measured and finally conclusions about the impact of initial chemical composition and etching duration on properties of the films were drawn.

Diffusion/Reaction Limited Aggregation Approach for Microstructure Evolution and Condensation Kinetics during Synthesis of Silica-Based Alcogels.

A base-catalysed methyltrimethoxysilane (MTMS) colloidal gel formation was implemented as a cellular automaton (CA) system, specifically diffusion and/or reaction-limited aggregation. The initial characteristic model parameters were determined based on experimental synthesis of MTMS-based, ambient-pressure-dried aerogels. The applicability of the numerical approach to the prediction of gels' condensation kinetics and their structure was evaluated. The developed model reflects the kinetics properly within the investigated chemical composition range (in strongly reaction-limited aggregation conditions) and, to a slightly lesser extent, the structural properties of aggregates. Ultimately, a relatively simple numerical model reflecting silica-based gel formation was obtained and verified experimentally. The CA simulations have proved valid for understanding the relation between the initial chemical composition and kinetics constants of MTMS-based synthesis and their impact on secondary particle aggregation process kinetics.

Predicting molecule size distribution in hydrocarbon pyrolysis using random graph theory.

Hydrocarbon pyrolysis is a complex process involving large numbers of chemical species and types of chemical reactions. Its quantitative description is important for planetary sciences, in particular, for understanding the processes occurring in the interior of icy planets, such as Uranus and Neptune, where small hydrocarbons are subjected to high temperature and pressure. We propose a computationally cheap methodology based on an originally developed ten-reaction model and the configurational model from random graph theory. This methodology generates accurate predictions for molecule size distributions for a variety of initial chemical compositions and temperatures ranging from 3200 to 5000K. Specifically, we show that the size distribution of small molecules is particularly well predicted, and the size of the largest molecule can be accurately predicted provided that this molecule is not too large.

High-precision abundances of first-population stars in NGC 2808: confirmation of a metallicity spread

Photometric investigations have revealed that Galactic globular clusters (GCs) exhibit internal metallicity variations amongst the so-called first-population stars, which until now were considered to have a homogeneous initial chemical composition. This is not fully supported by the sparse spectroscopic evidence, which so far gives conflicting results. Here, we present a high-resolution re-analysis of five stars in the Galactic GC NGC 2808 taken from the literature. Target stars are bright red giants with nearly identical atmospheric parameters belonging to the first population according to their identification in the chromosome map of the cluster, and we measured precise differential abundances for Fe, Si, Ca, Ti, and Ni to the ∼0.03 dex level. Thanks to the very small uncertainties associated with the differential atmospheric parameters and abundance measurements, we find that target stars span a range of iron abundance equal to 0.25 ± 0.06 dex. The individual elemental abundances are highly correlated with the positions of the stars along the extended sequence described by first-population objects in the cluster chromosome map: bluer stars have a lower iron content. This agrees with inferences from the photometric analysis. The differential abundances of all other elements also show statistically significant ranges that point to intrinsic abundance spreads. The Si, Ca, Ti, and Ni variations are highly correlated with iron variations and the total abundance spreads for all elements are consistent within the error bars. This suggests a scenario in which short-lived massive stars exploding as supernovae contributed to the self-enrichment of the gas in the natal cloud while star formation was still ongoing.

Modelling of the post-asymptotic giant branch phase as a tool to understand asymptotic giant branch evolution and nucleosynthesis

ABSTRACT We study a sample of single Galactic post-asymptotic giant branch (post-AGB) stars with known surface chemical composition. Gaia EDR3 and Gaia DR3 parallaxes have enabled accurate determinations of the luminosities of these objects, thus making it possible to characterize them in terms of their initial masses, chemical compositions, and progenitor ages. We used extant evolutionary sequences of asymptotic giant branch (AGB) stars produced using the ATON stellar evolutionary code extended to the post-AGB phase, specifically for this study. The luminosity and surface carbon abundance together prove to be the most valuable indicator of the previous evolution and nucleosynthetic history of the star, particularly regarding the efficiency of mixing mechanisms and the growth of the core. This analysis allows us to place the post-AGB sample into classes based on their evolutionary history on the AGB. This includes low-mass objects that evolved as M-type stars without third dredge-up, carbon stars, and intermediate-mass AGB stars with hot bottom burning (HBB). Additionally, our analysis reveals that AGB nucleosynthesis is not homogeneous, even for stars with similar initial masses and metallicities. The approach of using observations of post-AGB stars to constrain AGB and post-AGB models shed new light on still debated issues related to the AGB evolution, such as the threshold mass required to become a C-star, the minimum mass for HBB and the amount of carbon that can be accumulated in the surface regions of the star during the AGB lifetime, as well as deep mixing experienced during the red giant branch phase.

Study on Factors Hindering the Single-phase Formation of Divalent-ion-stabilized W-type Ferrites

Me-substituted W-type ferrites (AMe2Fe16O27 with A = Sr, Ba, …, and Me = Co, Ni, Zn, Mg, …) can be obtained by standard solid state reaction but always contain secondary phases. Phase stability of SrMe2Fe16O27 with Me = Co, Ni, Zn, and Mg sintered in various oxygen pressures of pO2 = 0.2, 1, 10 and 387 atm were investigated using X-ray diffraction analysis, wavelength-dispersive X-ray (WDX) analysis, and transmission electron microscopy (TEM). WDX analysis revealed that the W-type ferrites are described as SrMe2-δFe16+δO27 because Fe3+ is partially reduced to Fe2+ even when synthesis is initiated from SrMe2Fe16O27. Increasing the oxygen pressure suppresses the reduction of Fe3+ and the formation of the secondary phases. In addition, TEM analysis shows that the SrCo2Fe16O27 single crystal is free of stacking faults. We conclude that the single-phase formation of the Me-substituted W-type ferrites is hampered by the discrepancy between initial and actual chemical composition caused by the appearance of Fe2+.

Chemical evolution in planet-forming regions with growing grains

Context. Planets and their atmospheres are built from gas and solid material in protoplanetary disks. This solid material grows from smaller micron-sized grains to larger sizes in the disks during the process of planet formation. This solid growth may influence the efficiency of chemical reactions that take place on the surfaces of the grains and in turn affect the chemical evolution that the gas and solid material in the disk undergoes, with implications for the chemical composition of the planets. Aims. Our goal is to model the compositional evolution of volatile ices on grains of different sizes, assuming both time-dependent grain growth and several constant grain sizes. We also examine the dependence on the initial chemical composition. Methods. The custom Walsh chemical kinetics code was used to model the chemical evolution. This code was upgraded to account for the time-evolving sizes of solids. Chemical evolution was modelled locally at four different radii in a protoplanetary disk midplane (with associated midplane temperatures of 120, 57, 25, and 19.5 K) for up to 10 Myr. The evolution was modelled for five different constant grain sizes, and in one model, the grain size changed with time according to a grain-growth model appropriate for the disk midplane. Results. Local grain growth, with conservation of the total grain mass, and assuming spherical grains, acts to reduced the total grain-surface area that is available for ice-phase reactions. This reduces the efficiency of these reactions compared to a chemical scenario with a conventional grain-size choice of 0.1 μm. The chemical evolution modelled with grain growth leads to increased abundances of H2O ice. For carbon in the inner disk, grain growth causes CO gas to overtake CO2 ice as the dominant carrier, and in the outer disk, CH4 ice becomes the dominant carrier. Larger grain sizes cause less change the C/O ratio in the gas phase over time than when 0.1 μm sized grains are considered. Overall, a constant grain size adopted from a grain evolution model leads to an almost identical chemical evolution as a chemical evolution with evolving grain sizes. A constant grain size choice, albeit larger than 0.1 μm, may therefore be an appropriate simplification when modelling the impact of grain growth on chemical evolution.

Design and characterization of a novel MgAlZnCuMn low melting point light weight high entropy alloy (LMLW-HEA)

Development of high-entropy alloys (HEAs) is one of the remarkable advancements in the progress of new materials. In recent years, continuous efforts have been made to design light weight high-entropy alloys (LWHEAs) with suitable microstructure and superior properties. This paper reports the preliminary results of a study aimed at design and development of a new low melting point LWHEA (LMLW-HEA) based on AlMgZnCuMn alloy system without excessive intermetallic compounds formation. In this research, first, the initial chemical composition of the alloy was designed according to thermodynamic parameters, and then the alloy was melted in a resistance electric furnace. Since the thermodynamic indicators have been defined based on alloys containing 3d transition elements, formation of binary intermetallic compounds was predicted with the help of Midema model. To investigate the effects of cooling rate and heat treatment on the structure of the designed alloy, the molten alloy was poured into two different molds made of silica sand and steel, and both as cast samples were also heat treated. Microstructural features, mechanical properties and thermal stability of the samples were then examined. Density of the samples was measured to be less than 3.4 gr/cm3 which was very close to the theoretical density of the alloy. Structures of all the samples were complex and multi-phase and contained intermetallic (ordered solid solution) binary and ternary compounds including Mg7Zn3, MgZn2, Cu2Mg, Al2Cu, Mg32 (Al, Zn)49, Mg32Cu7Al47, Al25Mg37.5Zn37.5, and CuMgZn phases. The designed alloy was brittle under all the processing conditions. Compressive strength of the alloy reached to about 95 MPa, and its hardness was in the range of 110–120 HV. Oxidation resistance of the alloy was evaluated at a temperature about 30 °C below its solidus temperature and no weight change was observed in the sample after 14 h. It is suggested that the designed alloy is a suitable candidate for high temperature applications not involving impact or cyclic loading.

Signature of a chemical spread in the open cluster M37

ABSTRACT Recent Gaia photometry of the open cluster M37 has disclosed the existence of an extended main sequence turn-off – like in Magellanic clusters younger than about 2 Gyr – and a main sequence that is broadened in colour beyond what is expected from the photometric errors, at magnitudes well below the region of the extended turn-off, where neither age differences nor rotation rates (the candidates to explain the extended turn-off phenomenon) are expected to play a role. Moreover, not even the contribution of unresolved binaries can fully explain the observed broadening. We investigated the reasons behind this broadening by making use of synthetic stellar populations and differential colour–colour diagrams, using a combination of Gaia and Sloan filters. From our analysis, we have concluded that the observed colour spread in the Gaia colour–magnitude diagram can be reproduced by a combination of either a metallicity spread $\Delta \rm [Fe/H] \sim 0.15$ plus a differential reddening across the face of the cluster spanning a total range ΔE(B − V) ∼ 0.06, or a spread of the initial helium mass fraction ΔY ∼ 0.10 plus a smaller range of reddening ΔE(B − V) ∼ 0.03. High-resolution differential abundance determinations of a sizeable sample of cluster stars are necessary to confirm or exclude the presence of a metal abundance spread. Our results raise the possibility that also individual open clusters, like globular clusters and massive star clusters, host stars born with different initial chemical compositions.

Processing time, temperature, and initial chemical composition prediction from materials microstructure by deep network for multiple inputs and fused data

Prediction of the chemical composition and processing history from microstructure morphology can help in material inverse design. In this work, we propose a fused-data deep learning framework that can predict the processing history of a microstructure. We used the Fe-Cr-Co alloys as a model material. The developed framework is able to predict the heat treatment time, temperature, and initial chemical compositions by reading the morphology of Fe distribution and its concentration. The results show that the trained deep neural network has the highest accuracy for chemistry and then time and temperature. We identified two scenarios for inaccurate predictions; 1) There are several paths for an identical microstructure, 2) Microstructures reach steady-state morphologies after a long time of aging. The error analysis shows that the majority of the wrong predictions are indeed not wrong, but the other right answers. We validated the model successfully with an experimental Fe-Cr-Co transmission electron microscopy micrograph.

Fluid-Induced Inhomogeneous Cr-spinel in Dunite and Wehrlite from the Duke Island Complex, Southeastern Alaska

Cr-spinel [(Mg, Fe2+)(Cr, Al, Fe3+)2O4)] is a common mineral in the ultramafic core of the Duke Island complex in southeastern Alaska, US. Cr-spinel grains with an unmixed texture have been observed in dunite and wehrlite of the complex. Inhomogeneous Cr-spinel with a ratio of Cr/(Al + Cr + Fe3+) <0.37 is prominent in dunite. The inhomogeneous Cr-spinel consists of two completely different compositions: Al-rich Cr-spinel, and Fe3+-rich Cr-spinel with a wide range of Cr content (from 11.8 wt.% to 28.6 wt.% Cr2O3). The unmixed texture is complex, and three subtypes of inhomogeneous Cr-spinel are recognized: TypeB1 Cr-spinel showing complete separation, crystallographically oriented type B2 Cr-spinel, and irregular Al-rich Cr-spinel rimmed type B3 Cr-spinel. The unmixed texture was achieved by an unmixing process at around 600 °C due to the miscibility gap of spinel between Al-rich and Fe3+-rich phases. The unmixed patterns of inhomogeneous Cr-spinel are controlled by the initial chemical composition, grain size of the initial spinel, and the cooling process. We propose that the initial composition of inhomogeneous Cr-spinel was formed by the interaction of high-temperature fluid and olivine; Cr-spinel that experienced unmixing may be a useful proxy to unveil the activity of high-temperature fluid in the formation of Alaskan-type complexes.

INDENTIFIKASI SENYAWA EKSTRAK UMBI GARUT DAN TEPUNG IKAN LELE DUMBO MELALUI UJI FITOKIMIA SEBAGAI IMUNOSTIMULAN PADA TIKUS PUTIH YANG DI INDUKSI VAKSIN HEPATITIS B

The variety of biodiversity that grows in Indonesia makes this country the second megacenter in the world after Brazil. More than 30,000 plant species grow and 2,500 of them are medicinal plants one of them is arrowroot (Maranta arundinacea) as well as natural sources of animal wealth such as Dumbo catfish (Powder Clarias gariepinus) which is a source of protein that is needed by the body. Several researchers have also investigated the active compounds contained in the two ingredients, but differences in the environment and the maintenance process significantly affect the chemical content. This research focused on the initial phytochemical test and chemical composition of Maranta arundinacea extract and Clarias gariepinus powder extracted with 40% ethanol by maceration and hydrolysis techniques

Chemical Evolution During the Formation of Molecular Clouds

To study the chemical evolution during the formation of molecular clouds, we model three types of clouds with different density structures: collapsing spherical, collapsing ellipsoidal, and static spherical profiles. The collapsing models are better than the static models in matching the observational characteristics in typical molecular clouds. This is mainly because the gravity can speed up the formation of some important molecules (e.g., H2, CO, OH) by increasing the number density during collapse. The different morphologies of prolate, oblate, and spherical clouds lead to differences in chemical evolution, which are mainly due to their different evolution of number density. We also study the effect of initial chemical compositions on chemical evolution, and find that H atoms can accelerate OH formation by two major reactions: O + H → OH in gas phase and on dust grain surfaces, leading to the models in which hydrogen is mainly atomic initially better match observations than the models in which hydrogen is mainly molecular initially. Namely, to match observations, initially hydrogen must be mostly atomic. The CO molecules are able to form even without the pre-existence of H2. We also study the influence of gas temperature, dust temperature, intensity of interstellar radiation field and cosmic-ray ionization rate on chemical evolution in static clouds. The static CO clouds with high dust temperature, strong radiation field, and intensive cosmic rays are transient due to rapid CO destruction.

Chemistry, Local Molybdenum Clustering, and Electrochemistry in the Li2+xMo1-xO3 Solid Solutions.

A broad range of cationic nonstoichiometry has been demonstrated for the Li-rich layered rock-salt-type oxide Li2MoO3, which has generally been considered as a phase with a well-defined chemical composition. Li2+xMo1-xO3 (-0.037 ≤ x ≤ 0.124) solid solutions were synthesized via hydrogen reduction of Li2MoO4 in the temperature range of 650-1100 °C, with x decreasing with the increase of the reduction temperature. The solid solutions adopt a monoclinically distorted O3-type layered average structure and demonstrate a robust local ordering of the Li cations and Mo3 triangular clusters within the mixed Li/Mo cationic layers. The local structure was scrutinized in detail by electron diffraction and aberration-corrected scanning transmission electron microcopy (STEM), resulting in an ordering model comprising a uniform distribution of the Mo3 clusters compatible with local electroneutrality and chemical composition. The geometry of the triangular clusters with their oxygen environment (Mo3O13 groups) has been directly visualized using differential phase contrast STEM imaging. The established local structure was used as input for density functional theory (DFT)-based calculations; they support the proposed atomic arrangement and provide a plausible explanation for the staircase galvanostatic charge profiles upon electrochemical Li+ extraction from Li2+xMo1-xO3 in Li cells. According to DFT, all electrochemical capacity in Li2+xMo1-xO3 solely originates from the cationic Mo redox process, which proceeds via oxidation of the Mo3 triangular clusters into bent Mo3 chains where the electronic capacity of the clusters depends on the initial chemical composition and Mo oxidation state defining the width of the first charge low-voltage plateau. Further oxidation at the high-voltage plateau proceeds through decomposition of the Mo3 chains into Mo2 dimers and further into individual Mo6+ cations.

Deep learning approach for chemistry and processing history prediction from materials microstructure

Finding the chemical composition and processing history from a microstructure morphology for heterogeneous materials is desired in many applications. While the simulation methods based on physical concepts such as the phase-field method can predict the spatio-temporal evolution of the materials’ microstructure, they are not efficient techniques for predicting processing and chemistry if a specific morphology is desired. In this study, we propose a framework based on a deep learning approach that enables us to predict the chemistry and processing history just by reading the morphological distribution of one element. As a case study, we used a dataset from spinodal decomposition simulation of Fe–Cr–Co alloy created by the phase-field method. The mixed dataset, which includes both images, i.e., the morphology of Fe distribution, and continuous data, i.e., the Fe minimum and maximum concentration in the microstructures, are used as input data, and the spinodal temperature and initial chemical composition are utilized as the output data to train the proposed deep neural network. The proposed convolutional layers were compared with pretrained EfficientNet convolutional layers as transfer learning in microstructure feature extraction. The results show that the trained shallow network is effective for chemistry prediction. However, accurate prediction of processing temperature requires more complex feature extraction from the morphology of the microstructure. We benchmarked the model predictive accuracy for real alloy systems with a Fe–Cr–Co transmission electron microscopy micrograph. The predicted chemistry and heat treatment temperature were in good agreement with the ground truth.

A numerical approach to model chemistry of complex organic molecules in a protoplanetary disk

Abstract Multiphase astrochemical modeling presents a numerical challenge especially for the simulation of objects with the wide range of physical parameters such as protoplanetary disks. We demonstrate an implementation of the analytical Jacobian for the numerical integration of the system of differential rate equations that govern chemical evolution in star-forming regions. The analytical Jacobian allowed us to greatly improve the stability of the code in protoplanetary disk conditions. We utilize the MONACO code to study the evolution of abundances of chemical species in protoplanetary disks. The chemical model includes 670 species and 6,015 reactions in the gas phase and on interstellar grains. The specific feature of the utilized chemical model is the inclusion of low-temperature chemical processes leading to the formation of complex organic molecules (COMs), included previously in the models of chemistry of COMs in prestellar clouds. To test the impact of analytical Jacobian on the stability of numerical simulations of chemical evolution in protoplanetary disks, we calculated the chemical composition of the disk using a two-phase model and four variants of the chemical reaction network, three values of the surface diffusion rates, and two types of the initial chemical composition. We also show a preliminary implementation of the analytical Jacobian to a three-phase model.