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Atomic neural networks (ANNs) constitute a class of machine learning methods for predicting potential energy surfaces and physicochemical properties of molecules and materials. Despite many successes, developing interpretable ANN architectures and implementing existing ones efficiently are still challenging. This calls for reliable, general-purpose and open-source codes. Here, we present a python library named PiNN as a solution toward this goal. In PiNN, we implemented an interpretable graph convolutional neural network variant, PiNet, as well as the established Behler-Parrinello high-dimensional neural network potential. These implementations were tested using datasets of isolated small molecules, crystalline materials, liquid water and an aqueous alkaline electrolyte. PiNN comes with a visualizer called PiNNBoard to extract chemical insight "learned" by ANNs, provides analytical stress tensor calculations and interfaces to both the Atomic Simulation Environment and a development version of the Amsterdam Modeling Suite. Moreover, PiNN is highly modularized which makes it useful not only as a standalone package but also as a chain of tools to develop and to implement novel ANNs. The code is distributed under a permissive BSD license and is freely accessible at https://github.com/Teoroo-CMC/PiNN/ with full documentation and tutorials.

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The hydration-shell of CO is characterized using Raman multivariate curve resolution (Raman-MCR) spectroscopy combined with ab initio molecular dynamics (AIMD) vibrational density of states simulations, to validate our assignment of the experimentally observed high-frequency OH band to a weak hydrogen bond between water and CO. Our results reveal that while the hydration-shell of CO is highly tetrahedral, it is also occasionally disrupted by the presence of entropically stabilized defects associated with the CO-water hydrogen bond. Moreover, we find that the hydration-shell of CO undergoes a temperature-dependent structural transformation to a highly disordered (less tetrahedral) structure, reminiscent of the transformation that takes place at higher temperatures around much larger oily molecules. The biological significance of the CO hydration shell structural transformation is suggested by the fact that it takes place near physiological temperatures.