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This project aims to investigate room temperature ionic liquids morphology; and the impact their chemical properties have on the electron transfer processes of simple inorganic ions.
The relationships are described among prepolymer purity, processing parameters, and additives to the thermophysical and chemical properties of polybenzimidazole foams in the density range from 24 to 80 kg/cu m. Foam properties are shown to be affected by differences in prepolymer purity, curing schedule, and the presence of additives in the foam. High-temperature compressive properties were improved by postcuring at 527 C. Surfactant additives were found to improve uniformity of cell size. Foams were characterized according to high-temperature mechanical properties, density, porosity, thermal diffusivity, thermal conductivity, and specific heat.
This contribution provides a thorough examination of the structural characteristics of pyrochlore-type lanthanide titanates and zirconates Ln2Ti2O7 and Ln2Zr2O7, across various length scales. This paper also examines their processing, interesting physical properties (electrical, magnetic, and thermal characteristics), and responses to high pressure and ion irradiation. Brief sections on the elemental oxides' crystal chemistry, pertinent phase diagrams, and energetics of defect formation are also provided. Pyrochlore-type Ln2Ti2O7 and Ln2Zr2O7 stand out as truly multifunctional materials. Moreover, they have emerged as fascinating materials due to magnetic geometrical frustration, arising from the ordering of magnetic Ln3+ and non-magnetic Ti4+ (or Zr4+) cations into separate, interpenetrating lattices of corner-sharing tetrahedra. This results in a diverse array of exotic magnetic ground states, such as spin-ice (e.g., Dy2Ti2O7 or Ho2Ti2O7) or quantum spin ice (e.g., Tb2Ti2O7), observed at both low and room temperatures. They also exhibit varied electrical and electrochemical characteristics. Some members such as Gd2Zr2O7, function as fast ion conductors with a conductivity (σ) of ≈10−2 S·cm−1 at 800 °C and activation energy (Ea) ranging from 0.85 to 1.52 eV, depending on the degree of structural disorder. Others, such as Gd2TiMoO7, are mixed ionic-electronic conductors with σ ≈ 25 S·cm−1 at 1000 °C, making them promising candidate materials for applications in energy conversion and storage devices and oxygen separation membranes. Their exceptionally low thermal conductivity (e.g., κ ∼ 1.1–1.7 W·m−1·K−1 between 700 and 1200 °C for Ln2Zr2O7), close to the glass-like lower limit of highly disordered solids, positions them as valuable materials for thermal barrier coatings. They can also effectively accommodate actinides (e.g., Pu, Np, Cm, Am) in solid solutions and sustain prolonged exposure to radiation due to alpha-decay events, while preserving the integrity of the periodic atomic structure. Proposed as major components in actinide-bearing ceramics, they contribute to the long-term immobilization and disposal of long-lived waste radionuclides from nuclear programs. Some of these properties are displayed simultaneously, opening avenues for new applications. Despite the wealth of data available in the literature, this review highlights the need for a better understanding of order/disorder processes in pyrochlore-type materials and the influence of the structural length scale on their physical and chemical properties. Recent experimental evidence has revealed that pyrochlore short-range structure is far more complex than originally thought. Moreover, pyrochlore local structure is now believed to include short-range, lower symmetry, ordered domains, such as the orthorhombic weberite-type of structure. Notably, short- and long-range structures appear decoupled across different length scales and temperature regimes, and these differences persist even in well-ordered samples. We believe that the pyrochlore structure offers a unique opportunity for examining the interplay between chemical composition, defect chemistry, and properties. In Memoriam: Rodney C. Ewing, Fondly Remembered.
Fast pyrolysis of lignocellulosic materials is a promising research area to produce renewable fuels and chemicals. Dehydration is known to be among the most important reaction families during cellulose pyrolysis; water is the most important product. Together with water, dehydration reactions also form a range of poorly known oligomer species of varying molecular sizes, often collected as part of bio-oil water-soluble (WS) fraction. In this work, we used electronic structure calculations to evaluate the relative thermodynamic stabilities of several oligomer species resulting from up to three consecutive dehydration events from cellulose depolymerization intermediates. A library of the thermodynamically favored candidate molecular structures was compiled. Results revealed that most of the water molecules are eliminated from the non-reducing end, forming thermodynamically more stable conjugated compounds. This is consistent with results reported by other researchers in literature where dehydration reactions occur preferably at the non-reducing ends of oligomers. The physical-chemical properties of the proposed structures were estimated using quantitative structure-property relationships (QSPRs) and quantitative property-property relationships (QPPRs). The anhydro-sugars derived from cellulose are often blamed for coke formation during bio-oil hydrotreatment. Understanding their chemical structure could help to develop rational strategies to mitigate coke formation. Furthermore, the thermo-physical properties reported (boiling point, melting point, Gibb’s free energy of formation, enthalpy of formation, and solubility parameters among others) are also fundamental to conducting first principle engineering calculations to design and analyze new pyrolysis reactors and bio-oil up-grading units.
Bimetallics are emerging as important materials that often exhibit distinct chemical properties from monometallics. However, there is limited access to homogeneously alloyed bimetallics because of the thermodynamic immiscibility of the constituent elements. Overcoming the inherent immiscibility in bimetallic systems would create a bimetallic library with unique properties. Here, we present a nonequilibrium synthesis strategy to address the immiscibility challenge in bimetallics. As a proof of concept, we synthesize a broad range of homogeneously alloyed Cu-based bimetallic nanoparticles regardless of the thermodynamic immiscibility. The nonequilibrated bimetallic nanoparticles are further investigated as electrocatalysts for carbon monoxide reduction at commercially relevant current densities (>100 mA cm -2 ), in which Cu 0.9 Ni 0.1 shows the highest multicarbon product Faradaic efficiency of ~76% with a current density of ~93 mA cm -2 . The ability to overcome thermodynamic immiscibility in multimetallic synthesis offers freedom to design and synthesize new functional nanomaterials with desired chemical compositions and catalytic properties.
The family of two-dimensional (2D) carbides and/or nitrides, also known as MXenes, has generated great excitement within the scientific community and has been proposed for a wide variety of applications since its discovery. Despite this attention, there have been only limited studies of the atomically resolved local electronic and physical structure of MXene surfaces strongly affecting the physicochemical properties of these materials. Here, in this study, we report local structural, spectroscopic, and chemical investigations of the surfaces of Ti 3 C 2 T x flakes using scanning tunneling microscopy and spectroscopy, closely coupled to theoretical studies. Terminal groups are visualized and characterized, along with surface TiO 2 clusters formed upon exposure to air. Fundamental insight into the local electronic and chemical properties associated with different terminal groups on MXenes and their oxidation products is presented.
Single-walled carbon nanotubes (SWCNTs) are among the most promising nanostructures because of their special and unusual physico-chemical properties that make them strong candidates for a variety of applications. Since their discovery, chemical vapor deposition (CVD) methods have become the preferred synthesis method. CVD uses a carbon-containing precursor species, which is decomposed over a catalyst yielding C atoms that eventually evolve in carbon nanostructures. CVD temperatures are in the order of 1000K or lower, and pressures in the range of 1-5 atm, although some processes use higher pressures. Depending on the nature of the catalyst, and on the conditions of pressure, temperature, and presence of other inert compounds, the resultant nanostructures may include nanofibers, nano-onions, multiple-, or single-wall carbon nanotubes, among others. When the CVD synthesis process is appropriately tuned, however, it is possible to obtain only SWCNTs, which are geometrically characterized by their diameter and by their chiral angle. The chiral indexes (n,m) determine the degree of helical twist of the graphite lattice along the nanotube axis, where the term chirality is derived from the left and right-handed helicity of the tubes defined by their chiral indexes (n,m) and (m,n) respectively. The main goal of this research is to build fundamental understanding that will help elucidating the nature and structure of the actual catalyst in a combined catalyst/support system, which we claim is essential especially when the catalyst is of nanodimensions. Given that we are considerably advanced in the understanding of selective single-walled carbon nanotube catalyst synthesis, we take this process as a case study. Thus, we focus on the understanding of the selective growth of SWCNTs on supported nanocatalysts in systems where the catalyst synthesis takes place in the same reactor preceding the nanotube synthesis. Once we understand what type of catalyst structure would be necessary for this specific growth, we will try to elucidate the catalytic synthesis process that leads to such catalytic structure. Thus, our aim of controlling nanostructure synthesis may start to be delineated.
Partial anion substitution in transition metal oxides provides rich opportunities to control and tune physical and chemical properties, for example, combining the merits of oxides and nitrides. In addition, the possibility of resulting anion sublattice order provides a means to target polar and chiral structures based on a wide array of accessible structural archetypes by design. Here, in this work, we investigate the local structures of a family of perovskite tantalum oxynitrides—ATaO 2 N (A = Ba, Sr, and Ca)—using a combination of experimental and theoretical approaches including neutron total scattering, density functional theory (DFT), and ab initio molecular dynamics (AIMD) simulations. We present the first experimental study of chemical short-range order (CSRO) in CaTaO 2 N, confirming local cis N ordering of the anion sub-lattice. Our systematic exploration of a local structure across the A cation size series (from the larger Ba to the smaller Ca) reveals a perovskite motif increasingly distorted with respect to long-range average structures. DFT and AIMD simulations support the observed trends. Overall, structures with cis ordering of the nitrogen anions in each TaO 4 N 2 octahedron are favored over those with trans ordering. With diminishing A cation size, local cis ordering and Ta off-centering play decreasing roles in overall lattice stability, overshadowed by the stabilizing effects of octahedral tilting. The influence of these factors on local dipole formation and frustrated dipole ordering are discussed.
The ability to change material properties through phase engineering has long been sought, with the goal of ad hoc tunability of the physical and chemical properties of the transformed phases. The synthesis and study of graphene have made it possible to explore the mechanisms of 2D phase transformations, opening up paths towards the formation of 2D diamond and diamond thin films. This Review examines the state-of-the-art phase transformations in 2D graphitic systems and beyond. The theoretical models formulated to describe the sp2-to-sp3 transitions from graphene to 2D diamond and the experimental processes developed to induce the transition to 2D diamond are discussed, focusing on the transformations induced by chemical functionalization and pressure. The effects of different structural and environmental factors on the evolution of the phase transformations and on the properties of the transformed diamond phases are explored. Without comprehensively reviewing phase transitions in all 2D materials, we briefly mention hexagonal boron nitride, phosphorene, transition metal dichalcogenides and MXenes systems. Lastly, the Review delves into the technologies and applications of phase transformations in 2D materials and the opportunities for this field.
Confining materials within nanoscale volumes alters their physical and chemical properties, with positive consequences for energy storage, conversion, and catalysis. The pore structure and composition of scaffolds are essential variables for optimizing these properties, with carbon-based materials being preferred due to their tunable porous structures and chemical versatility. This study investigates the influence of surface functional groups on the dehydrogenation kinetics of nanoconfined NaAlH4 using zeolite-templated carbons (ZTCs). Here we focus on oxygen functional groups commonly present as intrinsic impurities on carbon scaffolds, analyzing three ZTC scaffolds to determine how their concentrations and configurations affect dehydrogenation behavior. Our findings reveal that carbonyl groups enhance charge transfer and destabilize Al–H bonds more effectively than ether or phenol groups. This indicates that the type of oxygen functional group is more critical than the quantity, highlighting the importance of properly tailoring oxygen defects to improve hydrogen storage performance in nanoconfined systems.
Polycyclic aromatic hydrocarbons (PAHs) are a group of environmental toxicants found ubiquitously as complex mixtures in human-impacted environments. Developmental zebrafish exposures have been used widely to study PAH toxicity, but most studies report nominal exposure concentrations. Nominal exposure concentrations can be unreliable dose metrics due to differences in toxicant bioavailability resulting from disparate exposure methodologies and chemical properties. Toxicokinetic modeling can predict toxicant tissue doses to facilitate comparison between exposures of different chemicals, methodologies, and biological models. We parameterize a biologically based dosimetry model for developmental zebrafish toxicity assays for 9 PAHs. The model was optimized with measurements from media, tissue, and plastic plate walls throughout a static developmental exposure to a mixture of 10 PAHs of high abundance within the Portland Harbor Superfund Site. Plate binding, volatilization, zebrafish permeability, and tissue—media partitioning coefficients vary widely between PAHs. Model predictions accounted for 83% and 54% of 48 hpf body burdens within a factor of 2 resulting from exposures to mixtures and individual PAHs, respectively. Accounting for solubility significantly improves model performance. Competition for active sites in metabolizing enzymes may change biotransformation kinetics between individual PAH and mixture exposures. Area under the curve estimations of concentrations in zebrafish resulted in altered hazard rankings from nominal exposure concentrations. Future work will be oriented to generalizing the model to other PAHs. This PAH dosimetry model improves the interpretability of developmental zebrafish toxicity assays by providing time-resolved body burdens from nominal exposure concentrations.
Autoxidation chemistry catalyzed by cobalt(II) acetate is an industrial pathway for converting hydrocarbons into oxygenated compounds and has promising potential applications in plastic waste deconstruction. However, the chemical properties of the Co acetate-based catalysts and their roles in the reaction mechanism are poorly understood, and as a result, attempts to redesign the autoxidation chemical process for novel applications lack clear direction. In this work, we investigate the structure and electronic properties of a series of multinuclear Co(III) compounds that have been proposed as active participants in catalytic autoxidation. Through a combination of X-ray spectroscopic measurements [Co K-edge X-ray absorption spectroscopy (XAS), extended X-ray absorption fine structure (EXAFS), Kβ X-ray emission spectroscopy (XES), and high-energy resolution fluorescence detection (HERFD) XAS] and theoretical methods, we characterize the interactions of Co with acetate and hydroxyl ligands in these compounds. Here we show that the substitution of acetate ligands with hydroxyls in these compounds causes an increase in the electron density on Co, driven by the loss of a π back-bonding interaction between Co and acetate and an increase in electron donation to Co from the hydroxyl ligands. We further classify the bonding between Co and acetate based on the orbital overlap and show that the experimental absorption and emission spectra are well-described by the resulting molecular orbitals. Finally, we predict the impacts of acetate/hydroxyl ligand exchange on autoxidation catalytic properties, showing that the reaction free energies for key Co oxidation and reduction steps are extremely sensitive to metal-ligand bonding interactions and thus have meaningful impacts on overall reactivity. The results of this study constitute an important set of design criteria for developing novel homogeneous autoxidation catalysts.
Chemical characterization of atmospheric organic aerosols using gas chromatography with 70 eV electron ionization mass spectrometry (GC/EI-MS) has been used for decades in advancing molecular marker detection and identification, though primarily through suspect screening and/or targeted analyses. To advance non-targeted analyses of environmental samples, we have catalogued approximately 27 000 mass spectra (MS) of the trimethylsilyl derivatives of semi-volatile organic aerosol (OA) analytes in the open-access University of California Berkeley Goldstein Library of Organic Biogenic Environmental Spectra (UCB-GLOBES). Analytes were observed in ambient samples from the U.S. and the Central Amazon and/or laboratory simulations of secondary OA (SOA) formation. These samples are representative of OA under urban and biomass burning influences as well as SOA derived from biogenic precursors (e.g., isoprene, monoterpenes, sesquiterpenes) and biomass burning intermediates. MS are documented in UCB-GLOBES without regard to known chemical identity, annotated with extensive metadata such as sample source/experimental conditions, any structural information gained from MS analyses, and predicted chemical properties such as average carbon oxidation state and carbon number. UCB-GLOBES MS are compatible for importing into the NIST MS Search program, and we have also provided a Jupyter Notebook for MS visualization and comparisons. We demonstrate the utility of UCB-GLOBES through MS reanalyses of prior analytes observed in ambient data, finding a 20 % reduction in the number of analytes assigned to OA source categories reliant solely on time series correlation and an overall 11 % increase in new MS-based OA source categorization for the Southeast U.S. For 1513 analytes observed previously in the Central Amazon, we found 375 MS matches using UCB-GLOBES vs. 136 MS matches during prior analyses, representing a 14 % gain in newly confirmed or newly categorized OA species. While OA from laboratory oxidation experiments in UCB-GLOBES are highly diverse chemically, on average only 29 % of UCB-GLOBES MS have a mass spectral match to another MS entry in UCB-GLOBES and/or in databases of known compounds (i.e. NIST MS Database, Adams Essential Oil, MANE Flavor and Fragrance Company). This indicates that roughly 70 % of UCB-GLOBES MS are unique thus far, not observed more than once among the laboratory oxidation samples and ambient data in UCB-GLOBES MS. Further, only 18 % can be positively identified using these databases or known authentic standards. This points to a large gap between these laboratory simulations and ambient OA. Overall, the UCB-GLOBES database can be utilized for improving confidence in OA source categorization and/or identification, novel chemical marker discovery, tracking chemical diversity, de novo structure and properties prediction, and improving MS search and matching algorithms. This can ultimately inform future research priorities for the chemical characterization of atmospheric organic samples.
To meet market demands, the aviation sector is interested in utilizing drop-in Synthetic Aviation Turbine Fuels (SATF), either as neat fuels or in blends with conventional Jet A. SATF currently approved in standard specifications may have lower aromatic content with significant fractions of normal, branched, and cyclo-alkanes. Fundamental studies on soot formation from aviation fuels (Jet A, SATF) and their surrogate components are essential to understand how fuel composition influences soot and soot precursor formation. Here, this study reports new measurements of polycyclic aromatic hydrocarbons (PAH) and soot in counterflow diffusion flames (CDFs) of aviation fuel surrogates. Both intrusive and non-intrusive diagnostics are employed to determine the profiles of temperature, gas phase species, PAHs (up to C16), and soot volume fraction (SVF) in CDFs of iso-octane and surrogate mixtures. These measurements shed light on the transition of soot precursors to primary soot particles. In addition to serving as a common surrogate component in Jet A surrogate mixtures, iso-octane is a template species for larger, less volatile branched alkanes found in SATF mixtures. The newly developed Lawrence Livermore National Laboratory (LLNL) PAH and soot model successfully captures temperature, precursor species, and SVF profiles for the mixtures and conditions discussed in this work. Finally, a high-fidelity surrogate for Jet A is proposed that matches targeted physical and chemical properties well, while leveraging the wide range of candidate fuel molecules available in the LLNL detailed chemical model. The proposed surrogate formulation is validated against newly acquired measurements of the surrogate and literature measurements of Jet A. These new experiments and simulations provide critical insights into the PAH and soot formation from aviation fuels. Reaction pathways which require further investigation are highlighted, such that future work may bridge the remaining quantitative gaps in predicting soot formation from aviation fuel surrogates and surrogate components.
Here, this paper presents a comprehensive review of existing research examining the effects of supplementary cementitious materials on age-dependent concrete properties with the most profound implications for precast concrete production. The review covers the physical and chemical properties of selected types of supplementary cementitious materials, concrete mixture proportions, concrete curing methods, testing procedures, and test results related to the fresh properties and strengths of a range of concrete mixtures. Although the use of supplementary cementitious materials in precast concrete products is common, the detailed information provided in this paper may facilitate more widespread use of these materials to enhance concrete properties and comply with sustainability initiatives.
Developing methods to identify mineral species confidently and rapidly from Raman spectral analysis is critical to numerous fields. Traditionally, analysis relies on pattern matching the Raman spectrum of an unknown dataset with a supporting library of well-characterized spectral data, which may prove difficult for environmental samples that are poorly crystalline or phase mixtures. Here, we developed interpretable machine learning models that can classify uranium minerals by secondary oxyanion chemistry and other physicochemical properties based solely on Raman spectra. This new ML method produces a mineral profile of physical and chemical properties for an unknown sample and can rapidly classify or identify unknown minerals from Raman data, without the need for an exact pattern match in a spectral library. Training models are validated by 1. Strong correlation of high confidence model regions with published spectroscopic assignments and 2. Correct classification of a mineral not present in training data. Training data are from the Compendium of Uranium Raman and Infrared Experimental Spectra and available crystallographic information files within the open-source Smart Spectral Matching scientific framework. Physically meaningful classifier models can rapidly identify key structural and chemical information about unknown uranium minerals and the overall methodology is broadly applicable for mineral phases.
The main results have been published in the refereed literature, and thus this report serves mainly to summarize the main findings and indicate where the detailed papers may be found. Reflectance spectroscopy has been an important tool for determining the mineralogic makeup of the near surface materials on Mars. Analysis of the spectral properties of the surface have demonstrated that these attributes are heterogeneous from the coarse spatial but high spectral resolution spectra obtained with telescopes to the high spatial but coarse spectral resolution Viking data (e.g. Arvidson et al., 1989; McEwen et al., 1989). Low albedo materials show strong evidence for the presence of igneous rock forming minerals while bright materials are generally interpreted as representing heavily altered crustal material. How these materials are physically and genetically related has important implications for understanding martian surface properties and processes, weathering histories and paths, and crustal composition. The goal of this research is to characterize the physical and chemical properties of low albedo materials on Mars and the relationship to intermediate and high albedo materials. Fundamental science questions to be pursued include: (1) the observed distributions of soil, rock, and dust a function of physical processes or weathering and (2) different stages of chemical and physical alteration fresh rock identified. These objectives will be addressed through detailed analyses and modelling of the ISM data from the Phobos-2 mission with corroborating evidence of surface composition and properties provided by data from the Viking mission.
In the present study, mixed-mode combustion of an E30 fuel in a direct-injection spark-ignition engine is numerically investigated at a fuel-lean operating condition using multidimensional computational fluid dynamics (CFD). A fuel surrogate matching Research Octane Number (RON) and Motor Octane Number (MON) of E30 is first developed using neural network based non-linear regression model. To enable efficient 3D engine simulations, a 164-species skeletal reaction mechanism incorporating NO, chemistry is reducedfrom a detailed chemical kinetic model. A hybrid approach that incorporates the G-equation model for tracking turbulentflame front, and the multi-zone well-stirred reactor model for predicting auto-ignition in the end gas, is employed to account for turbulent combustion interactions in the engine cylinder. Predicted in-cylinder pressure and heat release rate traces agree well with experimental measurements. The proposed modelling approach also captures moderated cyclic variability. Two different types of combustion cycles, corresponding to purely deflagrative and mixed-mode combustion, are observed. In contrast to the purely deflagrative cycles, mixed-mode combustion cycles feature early flame propagation followed by end-gas auto-ignition, leading to two distinctive peaks in heat release rate traces. The positive correlation between mixed-mode combustion cycles and early flame propagation is well captured by simulations. With the validated numerical setup, effects of NOx chemistry on mixed-mode combustion predictions are investigated. NOx chemistry is found to promote auto-ignition through residual gas recirculation, while the deflagrative flame propagation phase remains largely unaffected. Local sensitivity analysis is then performed to understand effects of physical and chemical properties of the fuel, i.e., heat of evaporation (HoV) and laminar flame speed (S-L). An increased HoV tends to suppress end-gas auto-ignition due to increased vaporization cooling, while the impact of HoV on flame propagation is insignificant. In contrast, an increased SL is found to significantly promote both flame propagation and auto-ignition. The promoting effect of SL on auto-ignition is not a direct chemical effect; it is rather caused by an advancement of the combustion phasing, which increases compression heating of the end gas.