Dynamic Acidity in Defective UiO-66

The metal organic framework (MOF) material UiO-66 has emerged as one of the most promising MOF materials due to its thermal and chemical stability and its potential for catalytic applications. Typically, as-synthesised UiO-66 has a relatively high concentration of missing linker defects. The presence of these defects has been correlated with catalytic activity but characterisation of defect structure has proved elusive. We refine a recent experimental determination of defect structure using static and dynamic first principles approaches, which reveals a dynamic and labile acid centre that could be tailored for functional applications in catalysis.Comment: 5 figure

Triboelectric behaviour of selected zeolitic-imidazolate frameworks: exploring chemical, morphological and topological influences †

Tribo- and contact electrification remain poorly understood, baffling and discombobulating scientists for millennia. Despite the technology needed to harvest mechanical energy with triboelectric generators being incredibly rudimentary and the fact that a triboelectric output can be obtained from almost any two material combinations, research into triboelectric generator materials typically focuses on achieving the highest possible output; meanwhile, understanding trends and triboelectric behaviours of related but lower performing materials is often overlooked or not studied. Metal–organic frameworks, a class of typically highly porous and crystalline coordination polymers are excellent media to study to fill this knowledge gap. Their chemistry, topology and morphology can be individually varied while keeping other material properties constant. Here we study 5 closely related zeolitic-imidazolate type metal–organic frameworks for their triboelectric performance and behaviour by contact-separating each one with five counter materials. We elucidate the triboelectric electron transfer behaviour of each material, develop a triboelectric series and characterise the surface potential by Kelvin-probe force microscopy. From our results we draw conclusions on how the chemistry, morphology and topology affect the triboelectric output by testing and characterising our series of frameworks to help better understand triboelectric phenomena

Glycolaldehyde, methyl formate and acetic acid adsorption and thermal desorption from interstellar ices

We have undertaken a detailed investigation of the adsorption, desorption and thermal processing of the astrobiologically significant isomers glycolaldehyde, acetic acid and methyl formate. Here, we present the results of laboratory infrared and temperature programmed desorption (TPD) studies of the three isomers from model interstellar ices adsorbed on a carbonaceous dust grain analogue surface. Laboratory infrared data show that the isomers can be clearly distinguished on the basis of their infrared spectra, which has implications for observations of interstellar ice spectra. Laboratory TPD data also show that the three isomers can be distinguished on the basis of their thermal desorption behaviour. In particular, TPD data show that the isomers cannot be treated the same way in astrophysical models of desorption. The desorption of glycolaldehyde and acetic acid from water-dominated ices is very similar, with desorption being mainly dictated by water ice. However, methyl formate also desorbs from the surface of the ice, as a pure desorption feature, and therefore desorbs at a lower temperature than the other two isomers. This is more clearly indicated by models of the desorption on astrophysical time-scales corresponding to the heating rate of 25 and 5 M⊙ stars. For a 25 M⊙ star, our model shows that a proportion of the methyl formate can be found in the gas phase at earlier times compared to glycolaldehyde and acetic acid. This has implications for the observation and detection of these molecules, and potentially explains why methyl formate has been observed in a wider range of astrophysical environments than the other two isomers

Trapping and desorption of complex organic molecules in water at 20 K

The formation, chemical and thermal processing of complex organic molecules (COMs) is currently a topic of much interest in interstellar chemistry. The isomers glycolaldehyde, methyl formate and acetic acid are particularly important because of their role as pre-biotic species. It is becoming increasingly clear that many COMs are formed within interstellar ices which are dominated by water. Hence the interaction of these species with water ice is crucially important in dictating their behaviour. Here we present the first detailed comparative study of the adsorption and thermal processing of glycolaldehyde, methyl formate and acetic acid adsorbed on and in water ices at astrophysically relevant temperatures (20 K). We show that the functional group of the isomer dictates the strength of interaction with water ice, and hence the resulting desorption and trapping behaviour. Furthermore, the strength of this interaction directly affects the crystallization of water, which in turn affects the desorption behaviour. Our detailed coverage and composition dependent data allow us to categorize the desorption behaviour of the three isomers on the basis of the strength of intermolecular and intramolecular interactions, as well as the natural sublimation temperature of the molecule. This categorization is extended to other C, H and O containing molecules in order to predict and describe the desorption behaviour of COMs from interstellar ices

Hydrogen bonds and van der Waals forces in ice at ambient and high pressures

The first principles approaches, density functional theory (DFT) and quantum Monte Carlo, have been used to examine the balance between van der Waals (vdW) forces and hydrogen (H) bonding in ambient and high pressure phases of ice. At higher pressure, the contribution to the lattice energy from vdW increases and that from H bonding decreases, leading vdW to have a substantial effect on the transition pressures between the crystalline ice phases. An important consequence, likely to be of relevance to molecular crystals in general, is that transition pressures obtained from DFT functionals which neglect vdW forces are greatly overestimated.Comment: Submitted to Phys. Rev. Lett., 5 pages, 3 figure

On the Accuracy of van der Waals Inclusive Density-Functional Theory Exchange-Correlation Functionals for Ice at Ambient and High Pressures

Density-functional theory (DFT) has been widely used to study water and ice for at least 20 years. However, the reliability of different DFT exchange-correlation (xc) functionals for water remains a matter of considerable debate. This is particularly true in light of the recent development of DFT based methods that account for van der Waals (vdW) dispersion forces. Here, we report a detailed study with several xc functionals (semi-local, hybrid, and vdW inclusive approaches) on ice Ih and six proton ordered phases of ice. Consistent with our previous study [Phys. Rev. Lett. 107, 185701 (2011)] which showed that vdW forces become increasingly important at high pressures, we find here that all vdW inclusive methods considered improve the relative energies and transition pressures of the high-pressure ice phases compared to those obtained with semi-local or hybrid xc functionals. However, we also find that significant discrepancies between experiment and the vdW inclusive approaches remain in the cohesive properties of the various phases, causing certain phases to be absent from the phase diagram. Therefore, room for improvement in the description of water at ambient and high pressures remains and we suggest that because of the stern test the high pressure ice phases pose they should be used in future benchmark studies of simulation methods for water.Comment: 13 pages, 5 figures, 4 table

Logical Segmentation of Source Code

Many software analysis methods have come to rely on machine learning approaches. Code segmentation - the process of decomposing source code into meaningful blocks - can augment these methods by featurizing code, reducing noise, and limiting the problem space. Traditionally, code segmentation has been done using syntactic cues; current approaches do not intentionally capture logical content. We develop a novel deep learning approach to generate logical code segments regardless of the language or syntactic correctness of the code. Due to the lack of logically segmented source code, we introduce a unique data set construction technique to approximate ground truth for logically segmented code. Logical code segmentation can improve tasks such as automatically commenting code, detecting software vulnerabilities, repairing bugs, labeling code functionality, and synthesizing new code.Comment: SEKE2019 Conference Full Pape