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Quantitative volatile organic compound sensing with liquid crystal core fibers
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Performance Characteristics of Mass Spectrometry-Based Analytical Procedures for Quantitation of Nitrosamines in Pharmaceuticals: Insights from an Inter-laboratory Study
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A quantitative assessment of the model form error of friction models across different interface representations for jointed structures
Hysteretic models are widely used to model frictional interactions in joints to recreate experimental behavior. However, it is unclear which models are best suited for fitting or predicting the responses of structures. Here, the present study evaluates 26 friction model/interface representation combinations to quantify the model form error. A Quasi-Static Modal Analysis approach (termed Rayleigh Quotient Nonlinear Modal Analysis) is adopted to calculate the nonlinear system response, and a Multi-Objective Optimization is solved to fit experimental data of the first mode of the Brake-Reuß Beam. Optimized parameters from the first mode are applied to the second and third bending modes to quantify the predictive ability of the models. Formulations for both tracing full hysteresis loops and recreating hysteresis loops from a single loading curve (Masing assumptions) are considered. Smoothly varying models applied to a five patch representation showed the highest flexibility (for fitting mode 1) and good predictive potential (for modes 2 and 3). For a second formulation, which uses 152 frictional elements to represent the interface, the physically motivated spring in series with a Coulomb slip model (elastic dry friction) has high error for fitting mode 1 and performs near the middle for predicting higher modes. For both interface representation, the best fit models are not the most physical, but rather the ones with the most parameters (as expected); however, the more physical models perform somewhat better for predicting the higher modes.
Quantitative Assessment and Measurement of X-ray Detector Performance and Solid Angle in the Analytical Electron Microscope
A wide range of X-ray detectors and geometries are available today on transmission/scanning transmission analytical electron microscopes. While there have been numerous reports of their individual performance, no single experimentally reproducible metric has been proposed as a basis of comparison between the systems. In this paper, we detail modeling, experimental procedures, measurements, and specimens which can be used to provide a manufacturer-independent assessment of the performance of an analytical system. Using these protocols, the geometrical collection efficiency, system peaks, and minimum detection limits can be independently assessed and can be used to determine the best conditions to conduct modern hyperspectral and/or spectrally resolved tomographic analyses for an individual instrument. Here, a simple analytical formula and specimen is presented which after suitable system calibrations can be used to experimentally determine the X-ray detector solid angle.
Raman Spectroscopy Coupled with Chemometric Analysis for Speciation and Quantitative Analysis of Aqueous Phosphoric Acid Systems
Complex chemical systems that exhibit varied and matrix-dependent speciation are notoriously difficult to monitor and characterize on-line and in real-time. Optical spectroscopy is an ideal tool for in situ characterization of chemical species that can enable quantification as well as species identification. Chemometric modeling, a multivariate method, has been successfully paired with optical spectroscopy to enable measurement of analyte concentrations even in complex solutions where univariate methods such as Beer’s law analysis fail. Here, Raman spectroscopy is used to quantify the concentration of phosphoric acid and its three deprotonated forms during a titration. In this system, univariate approaches would be difficult to apply due to multiple species being present simultaneously within the solution as pH is varied. Locally Weighted Regression (LWR) modeling was used to determine phosphate concentration from spectral signature. LWR results, in tandem with Multivariate Curve Resolution modeling, provide direct measurement of the concentration of each phosphate species using only the Raman signal. Furthermore, results are presented within the context of fundamental solution chemistry, including Pitzer equations to compensate for activity coefficients and non-idealities associated with high ionic strength systems.
Quantitative Structure–Activity Relationship Models to Predict Cardiac Adverse Effects
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Cluster-Graph Fingerprinting: A Framework for Quantitative Analysis of Machine-Learned Interatomic Model Training and Simulation Data
Machine-learned interatomic models represent a significant advancement in simulation methods, extending the predictive ability of first-principles methods to previously inaccessible length and time scales. However, the data-driven nature of these models can lead to difficult-to-detect errors that can compromise prediction accuracy. To address this challenge, we introduce a novel fingerprinting approach based on the Chebyshev Interaction Model for Efficient Simulation (ChIMES) ML-IAM graph-based descriptor. Our strategy enables efficient and statistically rigorous analysis of system configurations used in ML-IAM training and those generated by their application, e.g., in molecular dynamics simulations. We demonstrate that these fingerprints can effectively assess novelty of a configuration relative to an existing data set and determine dissimilarity among individual configurations, which are two key tasks in workflows for active learning-based ML-IAM training, data set curation, and on-the-fly uncertainty quantification.
Quantitative Account of the Bonding Properties of a Rubredoxin Model Complex [Fe(SCH3)4]q, q = -2, -1, +2, +3
Iron-sulfur clusters play important roles in biology as parts of electron transfer chains and catalytic cofactors. Here, we report a detailed computational analysis of a structural model of the simplest natural iron-sulfur cluster of rubredoxin and its cationic counterparts. Specifically, we report results for the ground and low-lying electronically excited states of the complex [Fe(SCH3)4]2-/1-/2+/3+, using Multi-Reference (CASSCF, MRCISD), and Coupled Cluster [CCSD(T)] methodology in order to provide accurate adiabatic reduction energies, dissociation energies and insights into the bonding analysis. The nature of the Fe-S chemical bond and the magnitude of the ionization potentials in the anionic and cationic [Fe(SCH3)4] complexes offer a physical rationale for the relative stabilization, structure and speciation of these complexes. Anionic and cationic complexes present different types of chemical bonds: prevalently ionic in [Fe(SCH3)4]2-/1- complexes and covalent in [Fe(SCH3)4]2+/3+ complexes. The ionic bonds result in an energy gain for the transition [Fe(SCH3)4]2-®[Fe(SCH3)4]- (i.e., FeII®FeIII) of 1.5 eV, while the covalent bonds result in an energy loss for the transition [Fe(SCH3)4]2+®[Fe(SCH3)4]3+ of 16.6 eV, almost half of the IP of Fe2+. The ionic vs covalent bond character influences the Fe-S bond strength and length, i.e., ionic Fe-S bonds are longer than covalent ones by about 0.2 Å (for FeII) and 0.04 Å (for FeII). Finally, the average Fe-S heterolytic bond strength is 6.7 eV (FeII) and 14.6 (FeIII) eV at the RCCSD(T) level of theory.
Soft X-ray Spectroscopy Simulations with Multiconfigurational Wave Function Theory: Spectrum Completeness, Sub-eV Accuracy, and Quantitative Reproduction of Line Shapes
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Digital Database of Absorption Spectra of Diverse Flavonoids Enables Structural Comparisons and Quantitative Evaluations
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Quantitative Detection of Products and Radical Intermediates in Low-Temperature Oxidation of Cyclopentane
We present a combined experimental and theoretical investigation of the autoignition chemistry of a prototypical cyclic hydrocarbon, cyclopentane. Experiments using a high-pressure photolysis reactor coupled to time-resolved synchrotron VUV photoionization mass spectrometry directly probe the short-lived radical intermediates and products in cyclopentane oxidation reactions. We detect key peroxy radical intermediates ROO and OOQOOH, as well as several hydroperoxides, formed by second O 2 addition. Automated quantum chemical calculations map out the R + O 2 + O 2 reaction channels and demonstrate that the detected intermediates belong to the dominant radical chain-branching pathway: ROO (+ O 2 ) → γ-QOOH + O 2 → γ-OOQOOH → products. ROO, OOQOOH, and hydroperoxide products of second-O 2 addition undergo extensive dissociative ionization, making their experimental assignment challenging. We use photoionization dynamics calculations to aid in their characterization and report the absolute photoionization spectra of isomerically pure ROO and γ-OOQOOH. Here, a global statistical fit of the observed kinetics enables reliable quantification of the time-resolved concentrations of these elusive, yet critical species, paving the way for detailed comparisons with theoretical predictions from master-equation-based models.
Quantitative Cu Counting Methodologies for Cu/SSZ-13 Selective Catalytic Reduction Catalysts by Electron Paramagnetic Resonance Spectroscopy
Here, two Cu/SSZ-13 selective catalytic reduction (SCR) catalysts with distinct Si/Al ratios and isolated Z2Cu and ZCuOH distributions are prepared for in situ electron paramagnetic resonance (EPR) spectroscopic studies. These in situ studies include dehydration, titration of dehydrated samples with NO+O 2 and NH 3 , titration of NH 3 saturated samples with NO+O 2 , and finally steady-state standard NH 3 -SCR reaction. During dehydration, EPR active hydrated ZCuOH loses H 2 O ligands and becomes EPR silent due to a pseudo Jahn-Teller effect; a portion of ZCuOH also undergoes autoreduction to ZCu(I) species, a process that also induces EPR invisibility. During NO+O 2 treatment of dehydrated samples, ZCu(I) species are oxidized to Cu(II)-NO 3 - species, regaining EPR visibility. During NH3 titration, EPR silent dehydrated ZCuOH can also regain EPR visibility by coordinating with NH 3 ligands. During NO+O 2 titration of NH 3 -saturated samples, EPR active Cu contents first decrease due to Cu(II) reduction to Cu(I), and then increase due to Cu(II)-NO 3 - species formation. However, the Cu(II)-NO 3 - formation chemistry is substantially slower for the Si/Al = 36 catalyst. In steady-state SCR studies, the EPR active content decreases with increasing temperature in the kinetically controlled low-temperature regime and becomes largely invariant in mass-transfer limited regime. Importantly, Cu sites in the SCR more active Si/Al = 6 catalyst display substantially higher EPR visibility than the SCR less active Si/Al = 36 catalyst at any reaction temperatures tested. The higher Cu loading for the former catalyst is believed to be key for this difference.