Elucidation of the pre-nucleation phase directing metal-organic framework formation

Metal-organic framework (MOF) crystallization is governed by molecular assembly processes in the pre-nucleation stage. Yet, unravelling these pre-nucleation pathways and rationalizing their impact on crystal formation poses a great challenge since probing molecular-scale assemblies and macroscopic particles simultaneously is very complex. Herein, we present a multimodal, integrated approach to monitor MOF nucleation across multiple length scales by combining in situ optical spectroscopy, mass spectrometry, and molecular simulations. This approach allows tracing initial metal-organic complexes in solution and their assembly into oligomeric nuclei and simultaneously probing particle formation. During Co-ZIF-67 nucleation, a metal-organic pool forms with a variety of complexes caused by ligand exchange and symmetry reduction reactions. We discriminate complexes capable of initiating nucleation from growth species required for oligomerization into frameworks. Co4-nuclei are observed, which grow into particles following autocatalytic kinetics. The geometric and compositional variability of metal-organic pool species clarifies long-debated amorphous zeolitic imidazolate framework (ZIF)-particle nucleation and non-classic pathways of MOF crystallization

Nature of active sites on UiO-66 and beneficial influence of water in the catalysis of Fischer esterification

[EN] Zirconium terephthalate UiO-66 type metal organic frameworks (MOFs) are known to be highly active, stable and reusable catalysts for the esterification of carboxylic acids with alcohols. Moreover, when defects are present in the structure of these MOFs, coordinatively unsaturated Zr ions with Lewis acid properties are created, which increase the catalytic activity of the resulting defective solids. In the present work, molecular modeling techniques combined with new experimental data on various defective hydrated and dehydrated materials allow to unravel the nature and role of defective active sites in the Fischer esterification and the role of coordinated water molecules to provide additional Bronsted sites. Periodic models of UiO-66 and UiO-66-NH2 catalysts have been used to unravel the reaction mechanism on hydrated and dehydrated materials. Various adsorption modes of water and methanol are investigated. The proposed mechanisms are in line with experimental observations that amino groups yield a reduction in the reaction barriers, although they have a passive role in modulating the electronic structure of the material. Water has a beneficial role on the reaction cycle by providing extra Bronsted sites and by providing stabilization for various intermediates through hydrogen bonds. (C) 2017 The Authors. Published by Elsevier Inc.This work is supported by the Fund for Scientific Research Flanders (FWO) (project number 3G048612), the Research Board of Ghent University (BOF) and BELSPO in the frame of IAP/7/05. This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 641887 (project acronym: DEFNET). Funding was also received from the European Union's Horizon 2020 research and innovation programme [consolidator ERC grant agreement no. 647755-DYNPOR (2015-2020)]. Computational resources (Stevin Supercomputer Infrastructure) and services were provided by Ghent University. Financial support from the Generalitat Valenciana (project AICO/2015/065), the Spanish Ministry of Economy and Competitiveness (program Severo Ochoa SEV20120267), and the Spanish Ministry of Science and Innovation (project MAT2014-52085-C2-1-P) is gratefully acknowledged.Caratelli, C.; Hajek, J.; García Cirujano, F.; Warroquier, M.; Llabrés I Xamena, FX.; Van Speybroeck, V. (2017). Nature of active sites on UiO-66 and beneficial influence of water in the catalysis of Fischer esterification. Journal of Catalysis. 352:401-414. https://doi.org/10.1016/j.jcat.2017.06.014S40141435

The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector.

The development and operation of liquid-argon time-projection chambers for neutrino physics has created a need for new approaches to pattern recognition in order to fully exploit the imaging capabilities offered by this technology. Whereas the human brain can excel at identifying features in the recorded events, it is a significant challenge to develop an automated, algorithmic solution. The Pandora Software Development Kit provides functionality to aid the design and implementation of pattern-recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition, in which individual algorithms each address a specific task in a particular topology. Many tens of algorithms then carefully build up a picture of the event and, together, provide a robust automated pattern-recognition solution. This paper describes details of the chain of over one hundred Pandora algorithms and tools used to reconstruct cosmic-ray muon and neutrino events in the MicroBooNE detector. Metrics that assess the current pattern-recognition performance are presented for simulated MicroBooNE events, using a selection of final-state event topologies

A Proposal for a Three Detector Short-Baseline Neutrino Oscillation Program in the Fermilab Booster Neutrino Beam

A Short-Baseline Neutrino (SBN) physics program of three LAr-TPC detectors located along the Booster Neutrino Beam (BNB) at Fermilab is presented. This new SBN Program will deliver a rich and compelling physics opportunity, including the ability to resolve a class of experimental anomalies in neutrino physics and to perform the most sensitive search to date for sterile neutrinos at the eV mass-scale through both appearance and disappearance oscillation channels. Using data sets of 6.6e20 protons on target (P.O.T.) in the LAr1-ND and ICARUS T600 detectors plus 13.2e20 P.O.T. in the MicroBooNE detector, we estimate that a search for muon neutrino to electron neutrino appearance can be performed with ~5 sigma sensitivity for the LSND allowed (99% C.L.) parameter region. In this proposal for the SBN Program, we describe the physics analysis, the conceptual design of the LAr1-ND detector, the design and refurbishment of the T600 detector, the necessary infrastructure required to execute the program, and a possible reconfiguration of the BNB target and horn system to improve its performance for oscillation searches.Comment: 209 pages, 129 figure

Convolutional Neural Networks Applied to Neutrino Events in a Liquid Argon Time Projection Chamber

We present several studies of convolutional neural networks applied to data coming from the MicroBooNE detector, a liquid argon time projection chamber (LArTPC). The algorithms studied include the classification of single particle images, the localization of single particle and neutrino interactions in an image, and the detection of a simulated neutrino event overlaid with cosmic ray backgrounds taken from real detector data. These studies demonstrate the potential of convolutional neural networks for particle identification or event detection on simulated neutrino interactions. We also address technical issues that arise when applying this technique to data from a large LArTPC at or near ground level

Reconstruction and measurement of (100) MeV energy electromagnetic activity from π0 arrow γγ decays in the MicroBooNE LArTPC

We present results on the reconstruction of electromagnetic (EM) activity from photons produced in charged current νμ interactions with final state π0s. We employ a fully-automated reconstruction chain capable of identifying EM showers of (100) MeV energy, relying on a combination of traditional reconstruction techniques together with novel machine-learning approaches. These studies demonstrate good energy resolution, and good agreement between data and simulation, relying on the reconstructed invariant π0 mass and other photon distributions for validation. The reconstruction techniques developed are applied to a selection of νμ + Ar → μ + π0 + X candidate events to demonstrate the potential for calorimetric separation of photons from electrons and reconstruction of π0 kinematics

Calibration of the charge and energy loss per unit length of the MicroBooNE liquid argon time projection chamber using muons and protons

We describe a method used to calibrate the position- and time-dependent response of the MicroBooNE liquid argon time projection chamber anode wires to ionization particle energy loss. The method makes use of crossing cosmic-ray muons to partially correct anode wire signals for multiple effects as a function of time and position, including cross-connected TPC wires, space charge effects, electron attachment to impurities, diffusion, and recombination. The overall energy scale is then determined using fully-contained beam-induced muons originating and stopping in the active region of the detector. Using this method, we obtain an absolute energy scale uncertainty of 2% in data. We use stopping protons to further refine the relation between the measured charge and the energy loss for highly-ionizing particles. This data-driven detector calibration improves both the measurement of total deposited energy and particle identification based on energy loss per unit length as a function of residual range. As an example, the proton selection efficiency is increased by 2% after detector calibration

The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector

The development and operation of Liquid-Argon Time-Projection Chambers for neutrino physics has created a need for new approaches to pattern recognition in order to fully exploit the imaging capabilities offered by this technology. Whereas the human brain can excel at identifying features in the recorded events, it is a significant challenge to develop an automated, algorithmic solution. The Pandora Software Development Kit provides functionality to aid the design and implementation of pattern-recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition, in which individual algorithms each address a specific task in a particular topology. Many tens of algorithms then carefully build up a picture of the event and, together, provide a robust automated pattern-recognition solution. This paper describes details of the chain of over one hundred Pandora algorithms and tools used to reconstruct cosmic-ray muon and neutrino events in the MicroBooNE detector. Metrics that assess the current pattern-recognition performance are presented for simulated MicroBooNE events, using a selection of final-state event topologies.Comment: Preprint to be submitted to The European Physical Journal

Noise Characterization and Filtering in the MicroBooNE Liquid Argon TPC

The low-noise operation of readout electronics in a liquid argon time projection chamber (LArTPC) is critical to properly extract the distribution of ionization charge deposited on the wire planes of the TPC, especially for the induction planes. This paper describes the characteristics and mitigation of the observed noise in the MicroBooNE detector. The MicroBooNE's single-phase LArTPC comprises two induction planes and one collection sense wire plane with a total of 8256 wires. Current induced on each TPC wire is amplified and shaped by custom low-power, low-noise ASICs immersed in the liquid argon. The digitization of the signal waveform occurs outside the cryostat. Using data from the first year of MicroBooNE operations, several excess noise sources in the TPC were identified and mitigated. The residual equivalent noise charge (ENC) after noise filtering varies with wire length and is found to be below 400 electrons for the longest wires (4.7 m). The response is consistent with the cold electronics design expectations and is found to be stable with time and uniform over the functioning channels. This noise level is significantly lower than previous experiments utilizing warm front-end electronics.Comment: 36 pages, 20 figure

Design and construction of the MicroBooNE Cosmic Ray Tagger system

The MicroBooNE detector utilizes a liquid argon time projection chamber (LArTPC) with an 85 t active mass to study neutrino interactions along the Booster Neutrino Beam (BNB) at Fermilab. With a deployment location near ground level, the detector records many cosmic muon tracks in each beam-related detector trigger that can be misidentified as signals of interest. To reduce these cosmogenic backgrounds, we have designed and constructed a TPC-external Cosmic Ray Tagger (CRT). This sub-system was developed by the Laboratory for High Energy Physics (LHEP), Albert Einstein center for fundamental physics, University of Bern. The system utilizes plastic scintillation modules to provide precise time and position information for TPC-traversing particles. Successful matching of TPC tracks and CRT data will allow us to reduce cosmogenic background and better characterize the light collection system and LArTPC data using cosmic muons. In this paper we describe the design and installation of the MicroBooNE CRT system and provide an overview of a series of tests done to verify the proper operation of the system and its components during installation, commissioning, and physics data-taking