ACS Measurement Science Au最新文献

High-precision measurement of peak parameters such as intensity (I), peak position (ω_c), full width at half-maximum (Γ), and area (A) is pivotally important for advancing scientific research. Achieving high-precision requires elucidating the physical principles governing measurement precision and establishing guidelines for optimizing analytical conditions. Although the pseudo-Voigt profile is a widely used line-shape model, the underlying principles governing the precision of its parameter estimation remained unclear. For this study, we developed a model to quantify the parameter estimation precision under arbitrary conditions by integrating theoretical analysis, numerical calculations, and Monte Carlo simulations. Our quantification results indicate that when the mixing parameter (η) is fixed, the precision of I, Γ, and A is proportional to {Δx/ΓI}^0.5, whereas the precision of ω_c is proportional to {ΓΔx/I}^0.5, where Δx denotes the sampling interval. Furthermore, the analytical precision exhibits η-dependence: for I and Γ, when the profile becomes more Lorentzian, the absolute value of the covariance between Γ and η as well as between I and η increases, thereby degrading their estimation precision. This finding suggests that in addition to conventional methods such as improving the signal-to-noise ratio and reducing sampling interval, appropriately controlling η can be an effective strategy for optimizing precision. For instance, if broadening effects (e.g., instrumental or Doppler broadening) are deliberately introduced to tune η from 1 to 0, then this alone improves Γ estimation precision by a factor of 3.7, equivalent to a 14-fold increase in signal intensity. Furthermore, when the effect of increased Γ due to broadening is considered, even greater improvements in precision can be achieved. Overall, our model provides a foundational framework for research on peak parameter estimation. It serves as an alternative approach to error estimation when experimental evaluation is challenging and as a quantitative tool for assessing precision gain from instrument upgrades.

Elastin-like polymers (ELPs) have been used for a variety of biomedical applications, including drug delivery and tissue scaffolding. ELPs are useful due to their adjustable lower critical solution temperature and tunable structure for different applications. However, despite ample characterization of ELPs in aqueous solutions, the characterization of ELPs on surfaces is less well explored. For example, sources of inconsistency in ELP modification to surfaces have yet to be explored in detail. Surface modifications of large macromolecules often suffer from poor reproducibility and inconsistent measurements. We developed and optimized a method for modifying a gold electrode surface with ELPs using a thiol-gold interaction through a single cysteine residue near the N-terminus. The modification parameters were tuned for reproducible charge-transfer resistance of the surface, as measured by electrochemical impedance spectroscopy. The final optimized surface modification parameters, without dimethyl sulfoxide or other cosurfactant treatment, are 0.0125 mg/mL ELP for 30 min at 4 °C in 3.5 mM TCEP in ultrahigh-purity water at pH 7.4. The relative amount of cysteine modified to gold versus ELP solution concentration was determined via thiol reduction. Using these data, the source of poor reproducibility was confirmed to be nonspecific polymer interactions.

Dynamic systems, defined by their continuous temporal evolution, are central to advancements in chemistry, biology, and materials science. Optical techniques that leverage light absorption, scattering, and emission are essential for characterizing structural and property changes in these systems. However, conventional optical tools─such as UV–vis spectroscopy, fluorescence, and scattering techniques─provide fragmented or incomplete insights, making it challenging to comprehensively understand dynamic processes and ensure reliable data interpretation. Herein, we introduce a charge-coupled device (CCD)-based multitrack linearly polarized spectrometer (MLPS) designed for simultaneous kinetic UV–vis, polarization-resolved scattering, and photoluminescence measurements. The MLPS facilitates concurrent quantification of scattering and fluorescence intensities and depolarizations, alongside UV–vis extinction, with subsecond temporal resolution. By integrating high temporal resolution with the ability to capture complementary spectra, the MLPS significantly enhances the functionality of optical spectroscopy, paving the way for broader applications in dynamic system analysis and advancing research across multiple scientific disciplines. Furthermore, the instrument characterization and data preprocessing methodologies presented here provide valuable insights for the future development of multitrack CCD-based spectrometers.

Temperature is a critical parameter that can significantly influence the outcome of the redox reactions. However, determining the temperature-dependent properties of redox couples is often time-consuming and susceptible to inconsistencies. In this work, we present a temperature-controlled electrochemical station capable of acquiring electrochemical measurements under preprogrammed conditions to extract key thermodynamic parameters. We demonstrate the functionality of this system using electrochemical impedance spectroscopy to determine the activation energies of the [Fe(CN)₆]^3–/^4– redox couple and the hydrogen evolution reaction on platinum and gold electrodes. Additionally, we illustrate automated cyclic voltammetry data acquisition for [Fe(CN)₆]^3–/^4–, [Ru(NH₃)₆]²⁺/³⁺, benzoquinone, and anthraquinone. By analyzing the temperature-dependent shifts in E_1/2, we calculated the entropy changes and thermogalvanic coefficients of these systems. Furthermore, we examined the entropy variations of ferricyanide in mixed aqueous–organic electrolytes, highlighting the role of solvation reconfiguration. The versatility of this setup offers a robust and efficient platform for the rapid characterization of temperature-dependent redox properties, with implications for energy conversion and sensing applications.

In this paper, we describe how 3D printing can be used to fabricate a microfluidic-based transwell cell culture system with robust fluidic connections for long-term cell culture and recirculating flow. This approach consists of an electrospun collagen scaffold sandwiched between two laser-cut Teflon membranes that match the fluidic design. Madin-Darby canine kidney (MDCK) cells were cultured on the collagen scaffold to create an epithelial cell monolayer. Introduction of cells into the device was facilitated by a printed reservoir that could be closed after proper cell seeding with minimal effect of the flow profile over the cells. The resulting MDCK cell monolayer was exposed to continuous flow and transport through the cell layer and could be monitored by sampling from the basolateral channel network. COMSOL simulations and flow injection analysis were used to determine the effect of the reservoir geometry on the shear stress that cells experience. A variety of analytical tools were used to assess the effect of flow over the cells in this model. This includes confocal microscopy and potentiometric scanning ion conductance microscopy (to determine morphology and conductance), as well as transendothelial/epithelial electrical resistance (TEER) measurements and reverse transcription-quantitative polymerase chain reaction studies (for gene expression analysis). Finally, a drug transport study with the cell model was carried out using two drugs (caffeine and digoxin) to determine the apparent permeability of high and low permeability drugs, with results being similar to findings from in vivo studies as well as studies where MDCKs have been transfected to form more resistive barriers. This approach holds great promise for the creation of more in vivo-like, flow-based barrier models for transport studies.

The glycerol electrooxidation reaction (GEOR) has been gaining increasing attention as a substitute for the oxygen evolution reaction to improve H₂ production while producing high-value-added products. During GEOR, several C₃, C₂, and C₁ species can be generated, making the detection and quantification of all these products a complex challenge that has not been fully addressed yet. Our study describes the development and optimization of a simple high-performance liquid chromatography (HPLC) method, capable not only of detecting but also simultaneously quantifying eight different GEOR products using a single diode array detector (DAD). To address possible overlapping signals, an indirect quantification approach is also proposed. The optimized method has been applied to real electrochemical GEOR systems, employing a Ni foil in alkaline media or a Pt foil in acidic media as oxidation electrocatalysts. Results show how product distributions varied significantly along with the pH, with formate being the main product in alkaline conditions (∼68% selectivity), whereas glyceraldehyde and dihydroxyacetone were the major products in acidic conditions (∼40% and ∼26%, respectively).

The identification of chemical warfare agents, particularly Novichok variants, presents significant challenges due to the inherent dangers and practical limitations of experimental analysis. This study advances a computational approach using quantum chemistry electron ionization mass spectrometry (QCxMS, x = EI) to predict the electron ionization mass spectra (EIMS) of these compounds. We obtained experimental mass spectral data from three synthesized Novichok compounds, providing a crucial benchmark for validating computational predictions. Through systematic comparison of the experimental and predicted spectra, we evaluated how the incorporation of additional polarization functions and expanded valence space in basis sets influences prediction accuracy. Our investigation demonstrated that more complete basis sets yielded significantly improved matching scores across seven compounds while maintaining consistent functional parameters for ionization potential (IP) calculations. Comprehensive analysis of mass spectral patterns revealed distinct correlations between the molecular structure and fragmentation behavior. We identified characteristic patterns in both high and low m/z regions that correspond to specific structural features, enabling the development of a systematic framework for spectral interpretation. This understanding of the fragmentation mechanisms allowed for the prediction of mass spectra for four additional compounds with varying structural complexity. The strong correlation between the predicted and experimental results for the synthesized compounds validates this computational approach as a promising tool for the rapid identification of new chemical agents without requiring extensive experimental analysis. This methodology represents a significant advancement in our ability to identify and characterize emerging chemical threats while minimizing exposure risks to research personnel.