Faraday Discussions最新文献

Investigating the electrical double layer (EDL) structure has been a long-standing challenge and has seen the emergence of several sophisticated techniques able to probe selectively the few molecular layers of a solid/water interface. While a qualitative estimation of the thickness of the EDL can be obtained using simple theoretical models, following experimentally its evolution is not straightforward and can be even more complicated in nano- or microscale systems, particularly when changing the ionic concentration by several orders of magnitude. Here, we bring insight into the structure of the EDL of SiO₂ nanoparticle suspensions and its evolution with increasing ionic concentration using angle-resolved second harmonic scattering (AR-SHS). Below millimolar salt concentrations, we can successively characterize inner-sphere adsorption, diffuse layer formation, and outer-sphere adsorption. Moreover, we show for the first time that, by appropriately selecting the nanoparticle size, it is possible to retrieve information also in the millimolar range. There, we observe a decrease in the magnitude of the surface potential corresponding to a compression in the EDL thickness, which agrees with the results of several other electroanalytical and optical techniques. Molecular dynamics simulations suggest that the EDL compression mainly results from the diffuse layer compression rather than outer-sphere ions (Stern plane) moving closer to the surface.

Conical channels filled with an aqueous electrolyte have been proposed as promising candidates for iontronic neuromorphic circuits. This is facilitated by a novel analytical model for the internal channel dynamics [T. M. Kamsma, W. Q. Boon, T. ter Rele, C. Spitoni and R. van Roij, Phys. Rev. Lett., 2023, 130(26), 268401], the relative ease of fabrication of conical channels, and the wide range of achievable memory retention times by varying the channel lengths. In this work, we demonstrate that the analytical model for conical channels can be generalized to channels with an inhomogeneous surface charge distribution, which we predict to exhibit significantly stronger current rectification and more pronounced memristive properties in the case of bipolar channels, i.e. channels where the tip and base carry a surface charge of opposite sign. Additionally, we show that the use of bipolar conical channels in a previously proposed iontronic circuit features hallmarks of neuronal communication, such as all-or-none action potentials and spike train generation. Bipolar channels allow, however, for circuit parameters in the range of their biological analogues, and exhibit membrane potentials that match well with biological mammalian action potentials, further supporting their potential biocompatibility.

In order to obtain a good understanding of astrochemistry, it is crucial to better understand the key parameters that govern grain-surface chemistry. For many chemical networks, these crucial parameters are the binding energies of the species. However, there exists much disagreement regarding these values in the literature. In this work, a Bayesian inference approach is taken to estimate these values. It is found that this is difficult to do in the absence of enough data. The Massive Optimised Parameter Estimation and Data (MOPED) compression algorithm is then used to help determine which species should be prioritised for future detections in order to better constrain the values of binding energies. Finally, an interpretable machine learning approach is taken in order to better understand the non-linear relationship between binding energies and the final abundances of specific species of interest.

We report direct frequency comb spectroscopy of the 2ν₁ band of H¹³CN in the short-wave infrared (λ = 1.56 μm) towards experimental validation of molecular line lists that support observatories like JWST. The laboratory measurements aim to test spectral reference data generated from an experimentally accurate potential energy surface (PES) and an ab initio dipole moment surface (DMS) calculated from quantum chemistry theory. Benchmarking theory with experiment will improve confidence in new astrophysics and astrochemistry inferred from spectroscopic observations of HCN and HNC. Here we describe our instrumentation and initial results using a cross-dispersed spectrometer with a virtually imaged phased array (VIPA).

A general theory of coupled ion–electron transfer (CIET) is presented, which unifies Marcus kinetics of electron transfer (ET) with Butler–Volmer kinetics of ion transfer (IT). In the limit of large reorganization energy, the theory predicts normal Marcus kinetics of “electron-coupled ion transfer” (ECIT). In the limit of large ion transfer energies, the theory predicts Butler–Volmer kinetics of “ion-coupled electron transfer” (ICET), where the charge transfer coefficient and exchange current are connected to microscopic properties of the electrode/electrolyte interface. In the ICET regime, the reductive and oxidative branches of Tafel’s law are predicted to hold over a wide range of overpotentials, bounded by the ion-transfer energies for oxidation and reduction, respectively. The probability distribution of transferring electron energies in CIET smoothly interpolates between a shifted Gaussian distribution for ECIT (as in the Gerischer–Marcus theory of ET) to an asymmetric, fat-tailed Meixner distribution centered at the Fermi level for ICET. The latter may help interpret asymmetric line shapes in x-ray photo-electron spectroscopy (XPS) and Auger electron spectroscopy (AES) for metal surfaces in terms of shake-up relaxation of the ionized atom and its image polaron by ICET. In the limit of large overpotentials, the theory predicts a transition to inverted Marcus ECIT, leading to a universal reaction-limited current for metal electrodes, dominated by barrierless quantum transitions. Uniformly valid, closed-form asymptotic approximations are derived that smoothly transition between the limiting rate expressions for ICET and ECIT for metal electrodes, using simple but accurate mathematical functions. The theory is applied to lithium intercalation in lithium iron phosphate (LFP) and found to provide a consistent description of the observed current dependence on overpotential, temperature and concentration. CIET theory thus provides a critical bridge between quantum electrochemistry and electrochemical engineering, which may find many other applications and extensions.

Gradients of voltage, pressure, temperature, and salinity can transport objects in micro- and nanofluidic systems by well-known mechanisms. This paper explores the dynamics of particles in a viscosity gradient with numerical simulations. The different stochastic rules used to integrate the random motion of Brownian particles affect the steady-state distribution of particles in a diffusivity gradient. Importantly, the simulations illuminate the important role that the boundary conditions play, disallowing a steady-state flux when the boundary conditions mimic those of a closed container, but allowing flux when they mimic electrodes. These results provide an interpretation for measurements of a steady ionic current flowing between electrodes separated by a nanofluidic channel with a liquid viscosity gradient.