Double Electrode Experiments Reveal the Processes Occurring at PEDOT-Coated Neural Electrode Arrays.

Neural electrodes have recently been developed with surface modifications of conductive polymers, in particular poly(3,4-ethylenedioxythiophene) (PEDOT), and extensively studied for their roles in recording and stimulation, aiming to improve their biocompatibility. In this work, the implications for the design of practical neural sensors are clarified, and systematic procedures for their preparation are reported. In particular, this study introduces the use of in vitro double electrode experiments to mimic the responses of neural electrodes with a focus on signal-recording electrodes modified with PEDOT. Specifically, potential steps on one unmodified electrode in an array are used to identify the responses for PEDOT doped with different anions and compared with that of a bare platinum (Pt) electrode. The response is shown to be related to the rearrangement of ions in solution near the detector electrode resulting from the potential step, with a current transient seen at the detector electrode. A rapid response for PEDOT doped with chloride (ca. 0.04 s) ions was observed and attributed to the fast movement of chloride ions in and out of the polymer film. In contrast, PEDOT doped with poly(styrenesulfonate) (PSS) responds much slower (ca. 2.2 s), and the essential immobility of polyanion constrains the direction of current flow.

The solubility product controls the rate of calcite dissolution in pure water and seawater.

Quantification of calcite dissolution underpins climate and oceanographic modelling. We report the factors controlling the rate at which individual crystals of calcite dissolved. Clear, generic criteria based on the change of calcite particle dimensions measured microscopically with time are established to indicate if dissolution occurs under kinetic or thermodynamic control. The dissolution of calcite crystals into water is unambiguously revealed to be under thermodynamic control such that the rate at which the crystal dissolved is controlled by the rate of diffusion of ions from a saturated surface layer adjacent to the calcite surface. As such the dissolution rate is controlled by the true stoichiometric solubility product which is inferred from the microscopic measurement as a function of the concentration of NaCl. Comparison with accepted literature values shows that the role of ion pairing at high ionic strengths as in seawater, specifically that of CaCO3 and other ion pairs, exerts a significant influence since these equilibria control the amount of dissolved calcium and carbonate ions in the later of solution immediately adjacent to the solid.

Discovering Electrochemistry with an Electrochemistry-Informed Neural Network (ECINN).

Machine learning is increasingly integrated into chemistry research by guiding experimental procedures, correlating structure and function, interpreting large experimental datasets, to distill scientific insights that might be challenging with traditional methods. Such applications, however, largely focus on gaining insights via big data and/or big computation, while neglecting the valuable chemical prior knowledge dwelling in chemists' minds. In this paper, we introduce an Electrochemistry-Informed Neural Network (ECINN) by explicitly embedding electrochemistry priors including the Butler-Volmer (BV), Nernst and diffusion equations on the backbone of neural networks for multi-task discovery of electrochemistry parameters. We applied the ECINN to voltammetry experiments of F e 2 + / F e 3 + ${{\rm F}{{\rm e}}^{2+}/{\rm F}{{\rm e}}^{3+}}$ and R u N H 3 6 2 + / R u N H 3 6 3 + ${{\rm R}{\rm u}{\left({\rm N}{{\rm H}}_{3}\right)}_{6}^{2+{\rm \ }}/{\rm R}{\rm u}{\left({\rm N}{{\rm H}}_{3}\right)}_{6}^{3+{\rm \ }}}$ redox couples to discover electrode kinetics and mass transport parameters. Notably, ECINN seamlessly integrated mass transport with BV to analyze the entire voltammogram to infer transfer coefficients directly, so offering a new approach to Tafel analysis by outdating various mass transport correction methods. In addition, ECINN can help discover the nature of electron transfer and is shown to refute incorrect physics if imposed. This work encourages chemists to embed their domain knowledge into machine learning models to start a new paradigm of chemistry-informed machine learning for better accountability, interpretability, and generalization.

Rotating Disk Electrodes beyond the Levich Approximation: Physics-Informed Neural Networks Reveal and Quantify Edge Effects.

Physics-informed neural networks are used to characterize the mass transport to the rotating disk electrode (RDE), the most widely employed hydrodynamic electrode in electroanalysis. The PINN approach was first quantitatively verified via 1D simulations under the Levich approximation for cyclic voltammetry and chronoamperometry, allowing comparison of the results with finite difference simulations and analytical equations. However, the Levich approximation is only accurate for high Schmidt numbers (Sc > 1000). The PINN approach allowed consideration of smaller Sc, achieving an analytical level of accuracy (error <0.1%) comparable with independent numerical evaluation and confirming that the errors in the Levich equation can be as high as 3% when Sc = 1000 for rapidly diffusing species in aqueous solution. Entirely novel, the PINNs permit the solution of the 2D diffusion equation under cylindrical geometry incorporating radial diffusion and reveal the rotating disk electrode edge effect as a consequence of the nonuniform accessibility of the disc with greater currents flowing near the extremities. The contribution to the total current is quantified as a function of the rotation speed, disk radius, and analyte diffusion coefficient. The success in extending the theory for the rotating disk electrode beyond the Levich equation shows that PINNs can be an easier and more powerful substitute for conventional methods, both analytical and simulation based.

Calcifying Coccolithophore: An Evolutionary Advantage Against Extracellular Oxidative Damage.

The evolutionary advantages afforded by phytoplankton calcification remain enigmatic. In this work, fluoroelectrochemical experiments reveal that the presence of a CaCO3 shell of a naturally calcifying coccolithophore, Coccolithus braarudii, offers protection against extracellular oxidants as measured by the time required for the switch-off in their chlorophyll signal, compared to the deshelled equivalents, suggesting the shift toward calcification offers some advantages for survival in the surface of radical-rich seawater.

AI facilitated fluoro-electrochemical phytoplankton classification.

Marine phytoplankton is extremely diverse. Counting and characterising phytoplankton is essential for understanding climate change and ocean health not least since phytoplankton extensively biomineralize carbon dioxide whilst generating 50% of the planet's oxygen. We report the use of fluoro-electrochemical microscopy to distinguish different taxonomies of phytoplankton by the quenching of their chlorophyll-a fluorescence using chemical species oxidatively electrogenerated in situ in seawater. The rate of chlorophyll-a quenching of each cell is characteristic of the species-specific structural composition and cellular content. But with increasing diversity and extent of phytoplankton species under study, human interpretation and distinction of the resulting fluorescence transients becomes increasingly and prohibitively difficult. Thus, we further report a neural network to analyse these fluorescence transients, with an accuracy >95% classifying 29 phytoplankton strains to their taxonomic orders. This method transcends the state-of-the-art. The success of the fluoro-electrochemical microscopy combined with AI provides a novel, flexible and highly granular solution to phytoplankton classification and is adaptable for autonomous ocean monitoring.

Kinetics of Lipophilic Pesticide Uptake by Living Maize.

We report the uptake of a lipophilic fungicide into the cuticle of living leaves of young maize from droplets of a suspension concentrate. The action of a "coffee-ring" effect is demonstrated during fungicide formulation drying, and the fungicide particle distribution is quantified. We develop a simple, two-dimensional model of uptake leading to a "reservoir" of cuticular fungicide. This model allows inferences of physicochemical properties for fungicides inside the cuticular medium. The diffusion coefficient closely agrees with literature penetration experiments (Dcut ≈ 10-18 m2 s-1). The logarithm of the inferred cuticle-water partition coefficient log10 Kcw = 6.03 ± 0.04 is consistent with ethyl acetate as a model solvent for the maize cuticle. Two limiting kinetic uptake regimes are inferred from the model for short and long times, with the transition resulting from longitudinal saturation of the cuticle beneath the droplet. We discuss the strengths, limitations, and generalizability of our model within the "cuticle reservoir" approximation.

Reversible Cyclic Voltammetry and Non-Unity Stoichiometry: The Ag/AgBr/Br- Redox Couple.

The voltammetry of electrochemically reversible couples in which a soluble reactant is converted into an insoluble product is investigated computationally via simulation and, in the context of the Ag/AgBr/Br-redox couple, experimentally. The voltammetric waveshape is characterized and, when analyzed via apparent transfer coefficient analysis, shown to give rise to apparent transfer coefficients very considerably in excess of unity, leading to the generic insight for the characterization of electrode reactions involving solution and solid phase reactants.

Electrode kinetics from a single experiment: multi-amplitude analysis in square-wave chronoamperometry.

The recently introduced technique of square-wave chronoamperometry (SWCA) is studied under conditions of progressively increasing height of potential pulses (square-wave amplitude) within a single experiment. In multi-amplitude square-wave chronoamperometry (MA-SWCA) a potential modulation consisting of square-wave forward and reverse potential pulses is imposed on a constant mid-potential; the amplitude of pulses increases progressively during the experiment. This allows the fast and reliable estimation of kinetic parameters at a constant pulse frequency in a single experiment, based on the resulting feature known as the amplitude-based quasireversible maximum. The proposed methodology is tested by simulating the responses of a simple quasireversible electrode reaction of a dissolved redox couple and a surface confined electrode reaction. Compared with conventional square-wave voltammetry (SWV) and SWCA, MA-SWCA shows advantages in estimation of the standard rate constant in terms of simplicity, speed and efficiency for both studied electrode mechanisms.

Quantifying the Extent of Calcification of a Coccolithophore Using a Coulter Counter.

Although, in principle, the Coulter Counter technique yields an absolute measure of particle volume, in practice, calibration is near-universally employed. For regularly shaped and non-biological samples, the use of latex beads for calibration can provide sufficient accuracy. However, this is not the case with particles encased in biogenically formed calcite. To date, there has been no effective route by which a Coulter Counter can be calibrated to enable the calcification of coccolithophores─single cells encrusted with biogenic calcite─to be quantified. Consequently, herein, we seek to answer the following question: to what extent can a Coulter Counter be used to provide accurate information regarding the calcite content of a single-species coccolithophore population? Through the development of a new calibration methodology, based on the measurement and dynamic tracking of the acid-driven calcite dissolution reaction, a route by which the cellular calcite content can be determined is presented. This new method allows, for the first time, a Coulter Counter to be used to yield an absolute measurement of the amount of calcite per cell.

Voltammetry of Carbon Nanotubes and the Limitations of Particle-Modified Electrodes: Are Carbon Nanotubes Electrocatalytic?

The use of carbon nanotubes (CNTs) as electrocatalysts is summarized; the limitations of using voltammetry based on CNT-modified electrodes is explained; and the role of mass transport, as well as electrode kinetics, with respect to dictating the voltammetric responses is discussed. The use of single-entity electrochemistry to at least complement, if not replace, ensemble voltammetry is advocated along with other caveats, notably purity, with respect to CNT voltammetry.

Electrochemical Heterogeneity at the Nanoscale: Diffusion to Partially Active Nanocubes.

How does heterogeneity in activity affect the response of nanoparticles? This problem is key to studying the structure-activity relationship of new electrocatalytic materials. However, addressing this problem theoretically and to a high degree of accuracy requires the use of three-dimensional electrochemical simulations that have, until recently, been challenging to undertake. To start to probe this question, we investigate how the diffusion-limited flux to a cube changes as a function of the number of active faces. Importantly, it is clearly demonstrated how the flux is not linearly proportional to the active surface area of the material due to the faces of the cube not having diffusional independence, meaning that the flux to each face reflects the activity or not of nearby faces. These results have clear and important implications for experimental work that uses a correlation-based approach to evidence changes in activity at the nanoscale.

Calcium Carbonate Dissolution from the Laboratory to the Ocean: Kinetics and Mechanism.

The ultimate fate, over the course of millennia, of nearly all of the carbon dioxide formed by humankind is for it to react with calcium carbonate in the world's oceans. Although, this reaction is of global relevance, aspects of the calcite dissolution reaction remain poorly described with apparent contradictions present throughout the expansive literature. In this perspective we aim to evidence how a lack of appreciation of the role of mass-transport may have hampered developments in this area. These insights have important implications for both idealised experiments performed under laboratory conditions and for the measurement and modelling of oceanic calcite sediment dissolution.

Modeling Transcuticular Uptake from Particle-Based Formulations of Lipophilic Products.

We report a mathematical model for the uptake of lipophilic agrochemicals from dispersed spherical particles within a formulation droplet across the leaf cuticle. Two potential uptake pathways are identified: direct uptake via physical contact between the cuticle and particle and indirect uptake via initial release of material into the formulation droplet followed by partition across the cuticle-formulation interface. Numerical simulation is performed to investigate the relevance of the particle-cuticle contact angle, the release kinetics of the particle, and the particle size relative to the cuticle thickness. Limiting cases for each pathway are identified and investigated. The input of typical physicochemical parameters suggests that the indirect pathway is generally dominant unless pesticide release is under strict kinetic control. Evidence is presented for a hitherto unrecognized "leaching effect" and the mutual exclusivity of the two pathways.

Understanding Carbon Nanotube Voltammetry: Distinguishing Adsorptive and Thin Layer Effects via "Single-Entity" Electrochemistry.

Cyclic voltammetry of ensembles of nanotube-modified electrodes fails to distinguish between signals from electroactive material adsorbed on the tubes from those due to a thin-layer response of analyte material occluded in the pores of the ensemble. We demonstrate that the distinction can be clearly made by combining cyclic voltammetry with single-entity measurements and provide proof of concept for the case of b-MWCNTs and the oxidation of 4-hexylresorcinol (HR), where the increased signals seen at the modified electrode are concluded to arise from thin-layer diffusion and not adsorptive effects. The physical insights are generic to porous, conductive composites.

Anodic stripping voltammetry using underpotential deposition allows sub 10 ppb measurement of Total As and As(III) in water.

We report a sensitive stripping voltammetry method for the detection of total arsenic in aqueous solution using gold macroelectrodes based on the underpotential deposition (UPD) of As ad-atoms. The detection of As(III) or total arsenic can be selectively made by changing deposition potential, with detection of the total As content by deposition at high potential (- 1.3 V) and of As(III) by deposition at lower potential (- 0.9 V). Linear responses were found for both arsenic species in the range 0.01 µM-0.1 µM at gold macroelectrodes. The analytical useful signals were recorded at concentrations as low as 0.01 µM (0.8 µg L-1) for both arsenic species suggesting that this method can be used to detect total arsenic concentrations in drinking water within the threshold value of the WHO of 0.13 µM (10 µg L-1).

Oxygen Reduction Reaction at Single Entity Multiwalled Carbon Nanotubes.

The electrocatalysis of the oxygen reduction reaction (ORR) in aqueous base (0.1 M KOH) by multiwalled carbon nanotubes (MWCNTs) is studied at the single entity level. Electroactive surface functionality is shown to facilitate significant electrocatalysis leading to peroxide formation which is seen to occur at lower potentials as compared to the voltammetric responses obtained at bare carbon macroelectrodes and at such electrodes modified with layers of carbon nanotubes.

Experimental Voltammetry Analyzed Using Artificial Intelligence: Thermodynamics and Kinetics of the Dissociation of Acetic Acid in Aqueous Solution.

Artificial intelligence (AI) is used to quantitatively analyze the voltammetry of the reduction of acetic acid in aqueous solution generating thermodynamic and kinetic data. Specifically, the variation of the steady-state current for the reduction of protons at a platinum microelectrode as a function of the bulk concentration of acetic acid is recorded and analyzed giving data in close agreement with independent measurements, provided the AI is trained with accurate and precise knowledge of diffusion coefficients of acetic acid, acetate ions, and H+.

The application of physics-informed neural networks to hydrodynamic voltammetry.

Electrochemical problems are widely studied in flowing systems since the latter offer improved sensitivity notably for electro-analysis and the possibility of steady-state measurements for fundamental studies even with macro-electrodes. We report the exploratory use of Physics-Informed Neural Networks (PINNs) as potentially simpler, and easier way to implement alternatives to finite difference or finite element simulations to predict the effect of flow and electrode geometry on the currents observed in channel electrodes where the flow is constrained to a rectangular duct with the electrode embedded flush with the wall of the cell. Several problems are addressed including the evaluation of the transport limited current at a micro channel electrode, the transport of material between two adjacent electrodes in a channel flow and the response of an electrode where the electrode reaction follows a preceding chemical reaction. The approach is shown to give quantitative agreement in the limits for which existing solutions are known whilst offering predictions for the case of the previously unexplored CE reaction at a micro channel electrode.

Electro-oxidation of amino-functionalized multiwalled carbon nanotubes.

We report the electrochemistry of amino-functionalized multiwalled carbon nanotubes (MWCNTs-NH2) in the pH range from 0.3 to 6.4 using quantitative cyclic voltammetry (CV) and single entity electrochemistry measurements, making comparison with non-functionalized MWCNTs. CV showed the latter to both catalyze the solvent (water) decomposition and to undergo irreversible electro-oxidation forming oxygen containing surface functionality. The MWCNTs-NH2 additionally undergo an irreversible oxidation to an extent which is dependent on the pH of the solution, reflecting the variable amount of deprotonated amino groups present as a function of pH. Nano-impact experiments conducted at the single particle level confirmed the oxidation of both types of MWCNTs, showing agreement with the CV. The pK a of the amino groups in MWCNTs was determined via both electrochemical methods giving consistent values of ca. 2.5.