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Joseph Parker

Publications and source records attributed to Joseph Parker.

6 recordsLinked to original sources

Atomic-resolution imaging of gold species at organic liquid-solid interfaces

Understanding solid-liquid interfaces at the atomic-scale is key to improved performance of heterogeneous catalysts, electrodes and membranes. Here we combine unique specimen design, record atomic resolution in situ electron microscopy, and artificial intelligence-enabled analysis to achieve a step change in quantitative understanding of interfacial atomic behaviour. We create the first graphene liquid cells with organic solvents and employ them to track over 106 gold adatoms and clusters at a graphene surface immersed in acetone and cyclohexanone. We reveal dynamic correlated behaviour of gold adatom monomers, dimers, trimers and clusters, strongly influenced by each other, the solvent properties, and the atomic lattice of the substrate, in good agreement with theoretical calculations. We use the results to interpret differences in catalytic activity towards the industrially important acetylene hydrochlorination reaction. This new capability for exploration of atomic scale chemistry could enable rational design of future catalysts, membranes and electrodes with improved functionality.

cond-mat.mtrl-sci

Phase engineering of 1T$'$ and 1T CrS2 and Cr2S3 by MOCVD

Layered Cr-chalcogenides compounds offer a rich range of crystal phases with different magnetic properties some of which have been predicted only but not experimentally verified. Here we demonstrate a previously unreported crystal phase of CrS2, namely the distorted octahedral (1T$'$) structure, synthesized via metal-organic chemical vapour deposition (MOCVD). We achieved the tuneable synthesis of either 1T$'$ or 1T phase CrS2. The structure were identified using polarized Raman spectroscopy, density functional perturbation theory (DFPT), as well as scanning electron diffraction (4D-STEM). 4D-STEM reveals that 1T$'$ crystals grow from an originally nucleated kinetically favoured 1T phase which then transform into the thermodynamically stable 1T$'$ phase. Magneto-optic Kerr imaging reveals that the 1T$'$ CrS2 crystals have soft ferromagnetic nature at low temperature. Our MOCVD growth of complex phases of 2D CrS2 with long-range magnetic order paves the way for the scalable synthesis of 2D magnets for ultrathin magnetic memories for logic-in-memory applications and spintronics.

cond-mat.mtrl-sci

MABe22: A Multi-Species Multi-Task Benchmark for Learned Representations of Behavior

We introduce MABe22, a large-scale, multi-agent video and trajectory benchmark to assess the quality of learned behavior representations. This dataset is collected from a variety of biology experiments, and includes triplets of interacting mice (4.7 million frames video+pose tracking data, 10 million frames pose only), symbiotic beetle-ant interactions (10 million frames video data), and groups of interacting flies (4.4 million frames of pose tracking data). Accompanying these data, we introduce a panel of real-life downstream analysis tasks to assess the quality of learned representations by evaluating how well they preserve information about the experimental conditions (e.g. strain, time of day, optogenetic stimulation) and animal behavior. We test multiple state-of-the-art self-supervised video and trajectory representation learning methods to demonstrate the use of our benchmark, revealing that methods developed using human action datasets do not fully translate to animal datasets. We hope that our benchmark and dataset encourage a broader exploration of behavior representation learning methods across species and settings.

cs.LG

Species Distribution Modeling for Machine Learning Practitioners: A Review

Conservation science depends on an accurate understanding of what's happening in a given ecosystem. How many species live there? What is the makeup of the population? How is that changing over time? Species Distribution Modeling (SDM) seeks to predict the spatial (and sometimes temporal) patterns of species occurrence, i.e. where a species is likely to be found. The last few years have seen a surge of interest in applying powerful machine learning tools to challenging problems in ecology. Despite its considerable importance, SDM has received relatively little attention from the computer science community. Our goal in this work is to provide computer scientists with the necessary background to read the SDM literature and develop ecologically useful ML-based SDM algorithms. In particular, we introduce key SDM concepts and terminology, review standard models, discuss data availability, and highlight technical challenges and pitfalls.

cs.LG

NEWAGE

NEWAGE is a direction-sensitive dark matter search experiment with a gaseous time-projection chamber. We improved the direction-sensitive dark matter limits by our underground measurement. After the first underground run, we replaced the detector components with radio-pure materials. We also studied the possibilities of head-tail recognition of nuclear tracks in the surface laboratory. For the future large volume detector, we are developing a pixel ASIC named QPIX. In this paper, these recent R&D activities are described.

astro-ph.IM

First underground results with NEWAGE-0.3a direction-sensitive dark matter detector

A direction-sensitive dark matter search experiment at Kamioka underground laboratory with the NEWAGE-0.3a detector was performed. The NEWAGE- 0.3a detector is a gaseous micro-time-projection chamber filled with CF4 gas at 152 Torr. The fiducial volume and target mass are 20*25*31 cm3 and 0.0115 kg, respectively. With an exposure of 0.524 kgdays, improved spin-dependent weakly interacting massive particle (WIMP)-proton cross section limits by a direction-sensitive method were achieved including a new record of 5400 pb for 150 GeV/c2 WIMPs. We studied the remaining background and found that ambient gamma-rays contributed about one-fifth of the remaining background and radioactive contaminants inside the gas chamber contributed the rest.

astro-ph.CO