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Deconvoluting the Magnetic Structure of the Commensurately Modulated Quinary Zintl Phase Eu 11– x Sr x Zn 4 Sn 2 As 12
The structure, magnetic properties, and 151 Eu and 119 Sn Mössbauer spectra of the solid-solution Eu 11– x Sr x Zn 4 Sn 2 As 12 are presented. A new commensurately modulated structure is described for Eu 11 Zn 4 Sn 2 As 12 ( R 3 m space group, average structure) that closely resembles the original structural description in the monoclinic C 2/ c space group with layers of Eu, puckered hexagonal Zn 2 As 3 sheets, and Zn 2 As 6 ethane-like isolated pillars. The solid-solution Eu 11– x Sr x Zn 4 Sn 2 As 12 (0 < x < 10) is found to crystallize in the commensurately modulated R 3 space group, related to the parent phase but lacking the mirror symmetry. Eu 11 Zn 4 Sn 2 As 12 orders with a saturation plateau at 1 T for 7 of the 11 Eu 2+ cations ferromagnetically coupled (5 K) and shows colossal magnetoresistance at 15 K. The magnetic properties of Eu 11 Zn 4 Sn 2 As 12 are investigated at higher fields, and the ferromagnetic saturation of all 11 Eu 2+ cations occurs at ~8 T. The temperature-dependent magnetic properties of the solid solution were investigated, and a nontrivial structure–magnetization correlation is revealed. The temperature-dependent 151 Eu and 119 Sn Mössbauer spectra confirm that the europium atoms in the structure are all Eu 2+ and that the tin is consistent with an oxidation state of less than four in the intermetallic region. The spectral areas of both Eu(II) and Sn increase at the magnetic transition, indicating a magnetoelastic effect upon magnetic ordering.
Deconvoluting the Combined Effects of Gas Composition and Temperature on Olefin Selectivity for Separations Using Silver(I) Ions in Ionic Liquids
Not Available
Water Interplays during Dysprosium Electrodeposition in Pyrrolidinium Ionic Liquid: Deconvoluting the Pros and Cons for Rare Earth Metallization
The electrochemical production of rare earth metals (REMs) in ionic liquids (ILs) has received much attention as a promising, sustainable and replacement to the molten salt electrolysis. Water additives have been recently suggested as a strategy to overcome the limitations of the ionic liquid process, but without complete assessment of its overall viability for the REMs production. In this regard, a full investigation of water impact on dysprosium (Dy) electrodeposition in pyrrolidinium triflate (BMPyOTf) ionic liquid was carried out. Water introduction was revealed to involve an interplay of implications on the electrodeposition process, including coordination, speciation, reduction pathways, interfacial dynamics, nucleation and metal stability and purity. In highly dry conditions, the reduction occurs at very negative potentials (-3.3V) in a consecutive pathway, resulting in negligible metal electrodeposition (low rate and efficiency) at the electrode surface. Initial water introduction (<30% molar fraction) leads to partitioning of the Dy complex between water and IL coordinated speciation, giving rise to an additional wave at more positive potentials (-2.4V). Probing and quantification of the heterogeneous Dy speciation by spectroscopic analyses enabled the uncovering of the reduction mechanism and accurate evaluation of the mass transport properties. While lowering the reduction thermodynamics, water addition also improved the nucleation, deposition rate and faradaic efficiency. In spite of these benefits, stripping voltammetric analysis also indicated substantial chemical reactivity of the deposited Dy metal with water additives and/or electrolyte components, under extended timescales. Surface characterization of the obtained product confirmed limited Dy metal stability (mostly oxidized/fluorinated) and purity (~60%) in the studied system. Moreover, high water introduction (>30% molar fraction) was shown to trigger a fast hydrogen evolution reaction (HER), downgrading the robustness of system efficiency. We report the overall impact of water additives seems to engender both promoting and mitigating effects on the Dy electrodeposition process, making the case for more innovative strategies to be sought.
Metal–Organic Frameworks as a Tunable Platform to Deconvolute Stereoelectronic Effects on the Catalytic Activity of Thioanisole Oxidation
The local environment of a metal active site plays an important role in affecting catalytic activity and selectivity. In re-cent studies, tailoring the behavior of a molybdenum-based active site via modulation of the first coordination sphere has led to improved thioanisole oxidation performance, but disentangling electronic effects from steric influences that arise from these modifications is nontrivial, especially in heterogeneous systems. To this end, the tunability of metal–organic frameworks (MOFs) makes them promising scaffolds for controlling the coordination sphere of a heterogene-ous, catalytically-active metal site while offering additional, attractive features such as crystallinity and high porosity. Herein, we report a variety of MOF-supported Mo species, which were investigated for catalytic thioanisole oxidation to methyl phenyl sulfoxide and/or methyl phenyl sulfone using tert-butyl hydroperoxide (tBHP) as the oxidant. In particular, MOFs of contrasting node architectures were targeted, presenting a unique opportunity to investigate ste-reoelectronic control of Mo active sites in a systematic manner. A Zr 6 -based MOF, NU-1000, was employed along with its sulfated analog Zr 6 -based NU-1000-SO 4 to anchor a dioxymolybdenum species, which enabled examination of sup-port-mediated active site polarizability on catalytic performance. In addition, a MOF containing a mixed metal node, Mo-MFU-4l, was used to probe the stereoelectronic impact of an N-donor ligand environment on the catalytic activity of the transmetalated Mo center. Furthermore, characterization techniques including single crystal X-ray diffraction, were concomi-tantly used with reaction kinetic profiles to better comprehend the dynamics of different Mo active sites, thus correlat-ing structural change with activity.
Application of a long short-term memory for deconvoluting conductance contributions at charged ferroelectric domain walls
Ferroelectric domain walls are promising quasi-2D structures that can be leveraged for miniaturization of electronics components and new mechanisms to control electronic signals at the nanoscale. Despite the significant progress in experiment and theory, however, most investigations on ferroelectric domain walls are still on a fundamental level, and reliable characterization of emergent transport phenomena remains a challenging task. Here, we apply a neural-network-based approach to regularize local I ( V )-spectroscopy measurements and improve the information extraction, using data recorded at charged domain walls in hexagonal (Er 0.99 ,Zr 0.01 )MnO 3 as an instructive example. Using a sparse long short-term memory autoencoder, we disentangle competing conductivity signals both spatially and as a function of voltage, facilitating a less biased, unconstrained and more accurate analysis compared to a standard evaluation of conductance maps. The neural-network-based analysis allows us to isolate extrinsic signals that relate to the tip-sample contact and separating them from the intrinsic transport behavior associated with the ferroelectric domain walls in (Er 0.99 ,Zr 0.01 )MnO 3 . Our work expands machine-learning-assisted scanning probe microscopy studies into the realm of local conductance measurements, improving the extraction of physical conduction mechanisms and separation of interfering current signals.
Deconvoluting charge-transfer, mass transfer, and ohmic resistances in phosphonic acid–sulfonic acid ionomer binders used in electrochemical hydrogen pumps
Ion-pair high-temperature polymer electrolyte membranes (HT-PEMs) paired with phosphonic acid ionomer electrode binders have substantially improved the performance of HT-PEM electrochemical hydrogen pumps (EHPs) and fuel cells. Here, blending poly(pentafluorstyrene-co-tetrafluorostyrene phosphonic acid) (PTFSPA) with Nafion™, and using this blend as an electrode binder, improved proton conductivity in the electrode layer resulting in a 2 W cm –2 peak power density of fuel cells at 240 °C (a HT-PEM fuel cell record). However, much is unknown about how phosphonic acid ionomers blended with perfluorosulfonic acid materials affect electrode kinetics and gas transport in porous electrodes. In this work, we studied the proton conductivity, electrode kinetics, and gas transport resistances of 3 types of phosphonic acid ionomers, poly(vinyl phosphonic acid), poly(vinyl benzyl phosphonic acid), and PTFSPA by themselves and when blended with Aquivion® (a perfluorosulfonic acid material).
Deconvoluting capping ligand influence on photophysical properties in tetrathiafulvalene-based diradicaloids
Tetrathiafulvalene-2,3,6,7-tetrathiolate (TTFtt) complexes are synthetically tunable and emit brightly in the near-infrared II region (NIR II, 1000–1700 nm).
Deconvoluting experimental decay energy spectra: The O 26 case
In nuclear reaction experiments, the measured decay energy spectra can give insights into the shell structure of decaying systems. However, extracting the underlying physics from the measurements is challenging due to detector resolution and acceptance effects. The Richardson-Lucy (RL) algorithm, a deblurring method that is commonly used in optics and has proven to be a successful technique for restoring images, was applied to our experimental nuclear physics data. The only inputs to the method are the observed energy spectrum and the detector's response matrix also known as the transfer matrix. We demonstrate that the technique can help access information about the shell structure of particle-unbound systems from the measured decay energy spectrum that is not immediately accessible via traditional approaches such as χ-square fitting. For a similar purpose, we developed a machine learning model that uses a deep neural network (DNN) classifier to identify resonance states from the measured decay energy spectrum. We tested the performance of both methods on simulated data and experimental measurements. Then, we applied both algorithms to the decay energy spectrum of 26 O → 24 O + n + n measured via invariant mass spectroscopy. Here, the resonance states restored using the RL algorithm to deblur the measured decay energy spectrum agree with those found by the DNN classifier. Both deblurring and DNN approaches suggest that the raw decay energy spectrum of 26 O exhibits three peaks at approximately 0.15 MeV, 1.50 MeV, and 5.00 MeV, with half-widths of 0.29 MeV, 0.80 MeV, and 1.85 MeV, respectively.
RED: A ReRAM-Based Efficient Accelerator for Deconvolutional Computation
Not provided.
Deconvolution of metal apportionment in bulk metal-organic frameworks
We report a general route to decipher the apportionment of metal ions in bulk metal-organic frameworks (MOFs) by solid-state nuclear magnetic resonance spectroscopy. We demonstrate this route in Mg 1-x Ni x -MOF-74, where we uncover all eight possible atomic-scale Mg/Ni arrangements through identification and quantification of the distinct chemical environments of 13 C-labeled carboxylates as a function of the Ni content. Here, we use magnetic susceptibility, bond pathway, and density functional theory calculations to identify local metal bonding configurations. The results refute the notion of random apportionment from solution synthesis; rather, we reveal that only two of eight Mg/Ni arrangements are preferred in the Ni-incorporated MOFs. These preferred structural arrangements manifest themselves in macroscopic adsorption phenomena as illustrated by CO/CO 2 breakthrough curves. We envision that this nondestructive methodology can be further applied to analyze bulk assembly of other mixed-metal MOFs, greatly extending the knowledge on structure-property relationships of MOFs and their derived materials.
Structural Modeling of the Treponema pallidum Outer Membrane Protein Repertoire: a Road Map for Deconvolution of Syphilis Pathogenesis and Development of a Syphilis Vaccine
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AlloSHP: deconvoluting single homeologous polymorphism for phylogenetic analysis of allopolyploids
Background The genomic and evolutionary study of allopolyploid organisms involves multiple copies of homeologous chromosomes, making their assembly, annotation, and phylogenetic analysis challenging. Bioinformatics tools and protocols have been developed to study polyploid genomes, but sometimes require the assembly of their genomes, or at least the genes, limiting their use. Results We have developed AlloSHP, a command-line tool for detecting and extracting single homeologous polymorphisms (SHPs) from the subgenomes of allopolyploid species. This tool integrates three main algorithms, WGA, VCF2ALIGNMENT and VCF2SYNTENY, and allows the detection of SHPs for the study of diploid-polyploid complexes with available diploid progenitor genomes, without assembling and annotating the genomes of the allopolyploids under study. AlloSHP has been validated on three diploid-polyploid plant complexes, Brachypodium, Brassica, and Triticum-Aegilops, and a set of synthetic hybrid yeasts and their progenitors of the genus Saccharomyces. The results and congruent phylogenies obtained from the four datasets demonstrate the potential of AlloSHP for the evolutionary analysis of allopolyploids with a wide range of ploidy and genome sizes. Conclusions AlloSHP combines the strategies of simultaneous mapping against multiple reference genomes and syntenic alignment of these genomes to call SHPs, using as input data a single VCF file and the reference genomes of the known or closest extant diploid progenitor species. This novel approach provides a valuable tool for the evolutionary study of allopolyploid species, both at the interspecific and intraspecific levels, allowing the simultaneous analysis of a large number of accessions and avoiding the complex process of assembling polyploid genomes.
Datasets for Pty-co-SAXSNN: CNN-Based Deconvolution for Simultaneous X-ray Ptychography and SAXS
The data comprise a simulated 3D nanoparticle clathrate dataset and an experimental 3D PtychoSAXS dataset of a supercrystal colloidal clathrate assembly, which were used to evaluate our custom Pty-co-SAXSNN framework.
Hahn-Echo Assisted Deconvolution (HEAD)
This repository contains the Bruker pulse program for acquire 2D HEAD data in addition to the C++ program used for data processing. Data must be acquired with identical digital resolution in both dimensions. The resulting 2D spectrum is converted to a ASCII file using the Topspin 'totxt' command. This file can be handled by the HEAD_processing program.