The influence of intermolecular correlations on the infrared spectrum of liquid dimethyl sulfoxide

PEDOT:Nafion for Highly Efficient Supercapacitors

Supercapacitors offer notable properties as energy storage devices, providing high power density and fast charging and discharging while maintaining a long cycling lifetime. Although poly(3,4-ethylenedioxythiophene) doped with poly(4-styrenesulfonate) (PEDOT/PSS) has become a gold standard among organic electronics materials, researchers are still investigating ways to further improve its capacitive characteristics. In this work, we introduced Nafion as an alternative polymeric counterion to PSS to form highly capacitive PEDOT/Nafion; its advantageous supercapacitive properties were further improved by treatment with either dimethyl sulfoxide or ethylene glycol. Accordingly, electrochemical characterization of PEDOT/Nafion films revealed their high areal capacitance (22 mF cm-2 at 10 mV/s) and low charge transfer resistance (∼380 Ω), together with excellent volumetric capacitance (74 F cm-3), Coulombic efficiency (99%), and an energy density of 23.1 ± 1.5 mWh cm-3 at a power density of 0.5 W cm-3, resulting from a more effective ion diffusion inside the conductive film, as confirmed by the results of spectroscopic studies. A proof-of-concept symmetric supercapacitor based on PEDOT/Nafion was characterized with a specific capacitance of approximately 15.7 F g-1 and impressive long-term stability (Coulombic efficiency ∼99% and capacitance ∼98.7% after 1000 charging/discharging cycles), overperforming the device based on PEDOT/PSS.

Collaboration on Machine-Learned Potentials with IPSuite: A Modular Framework for Learning-on-the-Fly

The field of machine learning potentials has experienced a rapid surge in progress, thanks to advances in machine learning theory, algorithms, and hardware capabilities. While the underlying methods are continuously evolving, the infrastructure for their deployment has lagged. The community, due to these rapid developments, frequently finds itself split into groups built around different implementations of machine-learned potentials. In this work, we introduce IPSuite, a Python-driven software package designed to connect different methods and algorithms from the comprehensive field of machine-learned potentials into a single platform while also providing a collaborative infrastructure, helping ensure reproducibility. Furthermore, the data management infrastructure of the IPSuite code enables simple model sharing and deployment in simulations. Currently, IPSuite supports six state-of-the-art machine learning approaches for the fitting of interatomic potentials as well as a variety of methods for the selection of training data, running of ab initio calculations, learning-on-the-fly strategies, model evaluation, and simulation deployment.

Evaporation-Induced Polyelectrolyte Complexation: The Role of Base Volatility and Cosolvents

Film formation is a vital step for coating applications where a homogeneous, defect-free solid phase should be obtained, starting from a liquid casting formulation. Recently, an alternative waterborne-coating approach was proposed, based on the formation of a polyelectrolyte complex film. In this approach, an evaporating base induces a pH change during drying that initiates the complexation of oppositely charged polyelectrolytes, followed by further densification. In previous studies, ammonia was used as the evaporative base, leading to relatively fast evaporation and resulting in films showing significant brittleness, which tended to crack at low relative humidity or larger thicknesses. We hypothesize that slower complexation and/or evaporation can reduce the problematic stress build-up in the prepared polyelectrolyte complex coatings. For this reason, we studied the changes in the film formation process when there are different bases and cosolvents. We found that reducing the evaporation rate by changing ammonia to the slower evaporating dimethylamine or by adding DMSO as a cosolvent, led to less internal stress build-up during film formation, which could be beneficial for film application. Indeed, films prepared with ammonia showed cracking after 1 h, while films prepared with dimethylamine only showed cracking after one month. The fast evaporation of ammonia was also found to cause a temporary turbid phase, indicating phase separation, while for the slower evaporating bases, this did not occur. All prepared films remained sensitive to humidity, which poses the next challenge for these promising coatings.

Continuing progress in the field of two-dimensional correlation spectroscopy (2D-COS): Part III. Versatile applications

In this review, the comprehensive summary of two-dimensional correlation spectroscopy (2D-COS) for the last two years is covered. The remarkable applications of 2D-COS in diverse fields using many types of probes and perturbations for the last two years are highlighted. IR spectroscopy is still the most popular probe in 2D-COS during the last two years. Applications in fluorescence and Raman spectroscopy are also very popularly used. In the external perturbations applied in 2D-COS, variations in concentration, pH, and relative compositions are dramatically increased during the last two years. Temperature is still the most used effect, but it is slightly decreased compared to two years ago. 2D-COS has been applied to diverse systems, such as environments, natural products, polymers, food, proteins and peptides, solutions, mixtures, nano materials, pharmaceuticals, and others. Especially, biological and environmental applications have significantly emerged. This survey review paper shows that 2D-COS is an actively evolving and expanding field.