The focus of this review is to provide an overview ofthe nomenclature,structure, and properties of perfluoroalkyl and polyfluoroalkyl substances(PFAS) that dictate the selection of analytical methods for analyzingPFAS in treated semiconductor wastewater. The review is organizedby introducing the fundamental concepts of how structure dictatesthe physical-chemical properties of PFAS and how these propertiesdetermine the suitability and applicability of standardized analyticalmethods for individual PFAS as well as methods for total fluorine.Structures for PFAS measured in semiconductor wastewater or knownto be in use by industry are given with tables intended as guidancefor method selection. This review includes current guidance on samplecollection, storage, and handling along with a comparison of U.S.Environmental Protection Agency and American Society for Testing andMaterials analytical methods for target PFAS as well as methods forultrashort PFAS. Methods are reviewed for volatile PFAS in wastewateras well as workflows for suspect and nontarget nonvolatile and volatilePFAS. Nonspecific methods for PFAS including the total oxidizableprecursor assay, total fluorine analyses, and extractable and adsorbableorganic fluorine assays are reviewed. Alternative detectors for totalfluorine are reviewed along with nuclear magnetic resonance spectroscopyand sensors for online wastewater monitoring.

High-precision measurement of peak parameters such asintensity(I), peak position (ωc), full width at half-maximum (Γ), and area (A) is pivotally important for advancing scientific research.Achieving high-precision requires elucidating the physical principlesgoverning measurement precision and establishing guidelines for optimizinganalytical conditions. Although the pseudo-Voigt profile is a widelyused line-shape model, the underlying principles governing the precisionof its parameter estimation remained unclear. For this study, we developeda model to quantify the parameter estimation precision under arbitraryconditions by integrating theoretical analysis, numerical calculations,and Monte Carlo simulations. Our quantification results indicate thatwhen the mixing parameter (η) is fixed, the precision of I, Γ, and A is proportional to {Δx/ΓI}0.5, whereas theprecision of ωc is proportionalto {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 moreLorentzian, the absolute value of the covariance between Γ andη as well as between I and η increases,thereby degrading their estimation precision. This finding suggeststhat in addition to conventional methods such as improving the signal-to-noiseratio and reducing sampling interval, appropriately controlling ηcan be an effective strategy for optimizing precision. For instance,if broadening effects (e.g., instrumental or Doppler broadening) aredeliberately introduced to tune η from 1 to 0, then this aloneimproves Γ estimation precision by a factor of 3.7, equivalentto a 14-fold increase in signal intensity. Furthermore, when the effectof increased Γ due to broadening is considered, even greaterimprovements in precision can be achieved. Overall, our model providesa foundational framework for research on peak parameter estimation.It serves as an alternative approach to error estimation when experimentalevaluation is challenging and as a quantitative tool for assessingprecision gain from instrument upgrades.

Elastin-like polymers (ELPs) have been used for a varietyof biomedicalapplications, including drug delivery and tissue scaffolding. ELPsare useful due to their adjustable lower critical solution temperatureand tunable structure for different applications. However, despiteample characterization of ELPs in aqueous solutions, the characterizationof ELPs on surfaces is less well explored. For example, sources ofinconsistency in ELP modification to surfaces have yet to be exploredin detail. Surface modifications of large macromolecules often sufferfrom poor reproducibility and inconsistent measurements. We developedand optimized a method for modifying a gold electrode surface withELPs using a thiol-gold interaction through a single cysteine residuenear the N-terminus. The modification parameters were tuned for reproduciblecharge-transfer resistance of the surface, as measured by electrochemicalimpedance spectroscopy. The final optimized surface modification parameters,without dimethyl sulfoxide or other cosurfactant treatment, are 0.0125mg/mL ELP for 30 min at 4 °C in 3.5 mM TCEP in ultrahigh-puritywater at pH 7.4. The relative amount of cysteine modified to goldversus ELP solution concentration was determined via thiol reduction.Using these data, the source of poor reproducibility was confirmedto be nonspecific polymer interactions.

Dynamic systems, defined by their continuous temporalevolution,are central to advancements in chemistry, biology, and materials science.Optical techniques that leverage light absorption, scattering, andemission are essential for characterizing structural and propertychanges in these systems. However, conventional optical toolssuchas UV–vis spectroscopy, fluorescence, and scattering techniquesprovidefragmented or incomplete insights, making it challenging to comprehensivelyunderstand dynamic processes and ensure reliable data interpretation.Herein, we introduce a charge-coupled device (CCD)-based multitracklinearly polarized spectrometer (MLPS) designed for simultaneous kineticUV–vis, polarization-resolved scattering, and photoluminescencemeasurements. The MLPS facilitates concurrent quantification of scatteringand fluorescence intensities and depolarizations, alongside UV–visextinction, with subsecond temporal resolution. By integrating hightemporal 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 analysisand advancing research across multiple scientific disciplines. Furthermore,the instrument characterization and data preprocessing methodologiespresented here provide valuable insights for the future developmentof multitrack CCD-based spectrometers.

Temperature is a critical parameter that can significantlyinfluencethe outcome of the redox reactions. However, determining the temperature-dependentproperties of redox couples is often time-consuming and susceptibleto inconsistencies. In this work, we present a temperature-controlledelectrochemical station capable of acquiring electrochemical measurementsunder preprogrammed conditions to extract key thermodynamic parameters.We demonstrate the functionality of this system using electrochemicalimpedance spectroscopy to determine the activation energies of the[Fe­(CN)6]3–/4– redoxcouple and the hydrogen evolution reaction on platinum and gold electrodes.Additionally, we illustrate automated cyclic voltammetry data acquisitionfor [Fe­(CN)6]3–/4–,[Ru­(NH3)6]2+/3+, benzoquinone,and anthraquinone. By analyzing the temperature-dependent shifts in E1/2, we calculated the entropy changes and thermogalvaniccoefficients of these systems. Furthermore, we examined the entropyvariations of ferricyanide in mixed aqueous–organic electrolytes,highlighting the role of solvation reconfiguration. The versatilityof this setup offers a robust and efficient platform for the rapidcharacterization of temperature-dependent redox properties, with implicationsfor energy conversion and sensing applications.

In this paper, wedescribe how 3D printing can be used to fabricatea microfluidic-based transwell cell culture system with robust fluidicconnections for long-term cell culture and recirculating flow. Thisapproach consists of an electrospun collagen scaffold sandwiched betweentwo laser-cut Teflon membranes that match the fluidic design. Madin-Darbycanine kidney (MDCK) cells were cultured on the collagen scaffoldto create an epithelial cell monolayer. Introduction of cells intothe device was facilitated by a printed reservoir that could be closedafter proper cell seeding with minimal effect of the flow profileover the cells. The resulting MDCK cell monolayer was exposed to continuousflow and transport through the cell layer and could be monitored bysampling from the basolateral channel network. COMSOL simulationsand flow injection analysis were used to determine the effect of thereservoir geometry on the shear stress that cells experience. A varietyof analytical tools were used to assess the effect of flow over thecells in this model. This includes confocal microscopy and potentiometricscanning ion conductance microscopy (to determine morphology and conductance),as well as transendothelial/epithelial electrical resistance (TEER)measurements and reverse transcription-quantitative polymerase chainreaction studies (for gene expression analysis). Finally, a drug transportstudy with the cell model was carried out using two drugs (caffeineand digoxin) to determine the apparent permeability of high and lowpermeability drugs, with results being similar to findings from invivo studies as well as studies where MDCKs have been transfectedto form more resistive barriers. This approach holds great promisefor the creation of more in vivo-like, flow-based barrier models fortransport studies.

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

The identificationof chemical warfare agents, particularly Novichokvariants, presents significant challenges due to the inherent dangersand practical limitations of experimental analysis. This study advancesa computational approach using quantum chemistry electron ionizationmass spectrometry (QCxMS, x = EI) to predict the electron ionizationmass spectra (EIMS) of these compounds. We obtained experimental massspectral data from three synthesized Novichok compounds, providinga crucial benchmark for validating computational predictions. Throughsystematic comparison of the experimental and predicted spectra, weevaluated how the incorporation of additional polarization functionsand expanded valence space in basis sets influences prediction accuracy.Our investigation demonstrated that more complete basis sets yieldedsignificantly improved matching scores across seven compounds whilemaintaining consistent functional parameters for ionization potential(IP) calculations. Comprehensive analysis of mass spectral patternsrevealed distinct correlations between the molecular structure andfragmentation behavior. We identified characteristic patterns in bothhigh and low m/z regions that correspondto specific structural features, enabling the development of a systematicframework for spectral interpretation. This understanding of the fragmentationmechanisms allowed for the prediction of mass spectra for four additionalcompounds with varying structural complexity. The strong correlationbetween the predicted and experimental results for the synthesizedcompounds validates this computational approach as a promising toolfor the rapid identification of new chemical agents without requiringextensive experimental analysis. This methodology represents a significantadvancement in our ability to identify and characterize emerging chemicalthreats while minimizing exposure risks to research personnel.