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2,118 results for “Metal”
London Dispersion Governs the Interaction Mechanism of Small Polar and Non-Polar Molecules in Metal-Organic Frameworks
<p>Raw data set relating to publication.</p>
SI data: A high-throughput structural and electrochemical study of metallic glass formation in Ni-Ti-Al
<p>Journal: ACS Combinatorial Science<br> Title: A high-throughput structural and electrochemical study of metallic glass formation in Ni-Ti-Al<br> Author(s): Joress, Howie; DeCost, Brian; sarker, suchismita; Braun, Trevor; Jilani, Sidra; Smith, Ryan; Ward, Logan; Laws, Kevin; Mehta, Apurva; Hattrick-Simpers, Jason</p>
Computational modelling of metal soap formation in historical oil paintings: the influence of fatty acid concentration and nucleus geometry on the induced chemo-mechanical damage.
<p>Metal soap formation is one of the most wide-spread degradation mechanisms observed in historical oil paintings, affecting works of art from museum collections worldwide. Metal soaps develop from a chemical reaction between metal ions present in the pigments and saturated fatty acids, which are released by the oil binder. The presence of large metal soap crystals inside paint layers or at the paint surface can be detrimental for the visual appearance of artworks. Moreover, metal soaps can possibly trigger mechanical damage, ultimately resulting in flaking of the paint. This paper departs from a recently proposed computational model to predict chemo-mechanical degradation in historical oil paintings, as presented in Eumelen et al. (J Mech Phys Solids 132:103683, 2019). The model describes metal soap formation and growth, which are phenomena that are driven by the diffusion of saturated fatty acids and proceed by a nucleation process from a crystalline nucleus of small size. This results into a chemically-induced strain in the paint, which may promote crack nucleation and propagation. The proposed model is here used to investigate the effects of saturated fatty acid concentration and initial nucleus geometry on the amount of chemo-mechanical damage generated. Numerical simulations show that both factors have a marginal influence on the growth rate of the metal soap crystal, but play a significant role on the extent of fracture induced in the paint.</p>
Characterization data for the manuscript "A data-driven perspective on the colours of metal-organic frameworks"
<p>Visualize the data in this dataset: <a href="https://www.c6h6.org/zenodo/record/4044212">open entry</a>. </p>
Raw Data related to Research Article: Scaling of metal-clad InP nanodisk lasers: optical performance and thermal effects, Optics Express, volume 29, issue 3, 2021
<p>These are the plotted and raw data used to obtain figures shown in:</p> <p>P. Tiwari, P. Wen, D. Caimi, S. Mauthe, N. Vico Triviño, M. Sousa, and K. E. Moselund, Scaling of metal-clad InP nanodisk lasers: optical performance and thermal effects., Optics Express, volume 29, issue 3, 2021</p> <p>Please comply with copyright rules of the Optical Society of America under the terms of the OSA Open Access Publishing Agreement.:</p> <p>https://www.osapublishing.org/library/license_v1.cfm#VOR-OA</p> <p> </p>
Data and Code for "Metal-enriched, sub-kiloparsec gas clumps in the circumgalactic medium of a faint z = 2.5 galaxy"
<p>This repository has code and data used in the paper "Metal-enriched, sub-kiloparsec gas clumps in the circumgalactic medium of a faint z = 2.5 galaxy" (http://arxiv.org/abs/1406.4239). If you find any of the data or code useful for a publication, please consider citing that paper.</p>
Using coupled micropillar compression and micro-Laue diffraction to investigate deformation mechanisms in a complex metallic alloy Al13Co4
<p>In this investigation, we have used <em>in-situ</em> micro-Laue diffraction combined with micropillar compression of focused ion beam milled Al<sub>13</sub>Co<sub>4</sub> complex metallic alloy to study the evolution of deformation in Al<sub>13</sub>Co<sub>4</sub>. Streaking of the Laue spots showed that the onset of plastic flow occured at stresses as low as 0.8 GPa, although macroscopic yield only becomes apparent at 2 GPa. The measured misorientations, obtained from peak splitting, enabled the geometrically necessary dislocation density to be estimated as 1.1 x 10<sup>13</sup> m<sup>-2</sup>.</p>
Research data supporting "Plasmonic chirality imprinting on nucleobase-displaying supramolecular nanohelices via metal-nucleobase recognition"
<p>This file contains the raw research data supporting the publication:</p> <p>Y. Lin<em> et al</em>., Plasmonic chirality imprinting on nucleobase-displaying supramolecular nanohelices via metal-nucleobase recognition, Angew. Chem. Int. Ed. 2017, DOI: 10.1002/anie.201610976.</p> <p> </p>
Engineering skyrmions in transition-metal multilayers for spintronics
<p>Magnetic skyrmions are localized, topologically protected spin structures that have been<br> proposed for storing or processing information due to their intriguing dynamical and transport<br> properties. Important in terms of applications is the recent discovery of interface stabilized<br> skyrmions as evidenced in ultra-thin transition-metal films. However, so far only skyrmions at<br> interfaces with a single atomic layer of a magnetic material were reported, which greatly<br> limits their potential for application in devices. Here we predict the emergence of skyrmions<br> in [4d/Fe2/5d]n multilayers, that is, structures composed of Fe biatomic layers sandwiched<br> between 4d and 5d transition-metal layers. In these composite structures, the exchange<br> and the Dzyaloshinskii–Moriya interactions that control skyrmion formation can be tuned<br> separately by the two interfaces. This allows engineering skyrmions as shown based on<br> density functional theory and spin dynamics simulations.</p>
Images for "Nano-scale magnetic skyrmions in metallic films and multilayers: a new twist for spintronics"
<p>Magnetic skyrmions are chiral quasiparticles that show promise for the transportation and storage of information. On a fundamental level, skyrmions are model systems for topologically protected spin textures and can be considered as the counterpart of topologically protected electronic states, emphasizing the role of topology in the classification of complex states of condensed matter. Recent impressive demonstrations of control of individual nanometer-scale skyrmions—including their creation, detection, manipulation and deletion—have raised expectations for their use in future spintronic devices, including magnetic memories and logic gates. From a materials perspective, it is remarkable that skyrmions can be stabilized in ultrathin transition metal films, such as Fe—one of the most abundant elements on earth—if these are in contact with materials that exhibit high spin-orbit coupling. At present, research in this field is focused on the development of transition-metal-based magnetic multilayer structures that support skyrmionic states at room temperature and allow for precise control of skyrmions by spin-polarized currents and external fields.</p>
Supplementary information for "Anharmonic origin of large thermal displacements in the metal-organic framework UiO-67"
<p>Supplementary information for DOI: 10.1021/acs.jpcc.7b04757</p> <p>POSCAR-XXX: DFT optimised structures</p> <p>Phonons-XXX.zip: Folders containing the force constants (FORCE_SETS), the resulting phonon frequencies (mesh.yaml), phonon partial density of states (partial_dos.dat), animations of all phonon modes (anime.ascii) e.g. to be visualized in VMD and gifs of selected phonon modes. </p> <p>XDATCAR-XXX: MD trajectories</p>
The Sonora Substellar Atmosphere Models. IV. Elf Owl: Atmospheric Mixing and Chemical Disequilibrium with Varying Metallicity and C/O Ratios (T- type Models)
<ul> <li><strong>Overview of V2: "The Sonora Substellar Atmosphere Models. V: A Correction to the Disequilibrium Abundance of CO2 for Sonora Elf Owl"</strong></li> </ul> <p> Version 2 of the Sonora Elf Owl Models updates the CO2 and PH3 abundances and spectra. As described in the Wogan et al. (2024) research note (URL OF NOTE GOES HERE), Version 1 of the models did not apply the CO2 quench approximation properly resulting in predicted CO2 abundances that were too small by several orders of magintude in some cases. Version 2 fixes this mistake, updating CO2 abundances and the emission spectra to reflect the new CO2 abundances. Version 2 also removes all spectra contributions of PH3 because Version 1 consistently contained too much PH3 absorption when compared to JWST data (Veiler et al. 2024, <a href="http://doi.org/10.3847/1538-4357/ad6759" target="_blank" rel="noopener noreferrer">http://doi.org/10.3847/1538-4357/ad6759</a>).</p> <p> </p> <ul> <li><strong>Overview of V1</strong></li> </ul> <p> The Sonora Elf Owl Models is a successor to the <a href="../records/5063476#:~:text=This%20particular%20set%20of%20model,g%20are%200.25%20or%200.5.">Sonora Bobcat</a> and <a href="../records/4450269">Sonora Cholla</a> models. The Sonora Elf Owl model grid includes cloud-free radiative-convective equilibrium model atmospheres with vertical mixing induced disequilibrium chemistry with sub-solar to super-solar atmospheric metallicities and Carbon-to-Oxygen ratio. The atmospheric models have been computed using the open-source radiative-convective equilibrium model <a href="https://natashabatalha.github.io/picaso/">PICASO</a>. The parameters included within this grid are effective temperature (<strong><em>Teff</em></strong>), gravity (<strong><em>log(g)</em></strong>), vertical eddy diffusion coefficient (<strong><em>log(Kzz)</em></strong>), atmospheric metallicity (<strong><em>[M/H]</em></strong>), and Carbon-to-Oxygen ratio (<strong><em>C/O</em></strong>).</p> <p>The ranges and increments of these parameters are described in the published paper.<br><br></p> <ul> <li><strong>Three grids available on three links</strong></li> </ul> <p><strong> The model grid has been presented using three Zenodo repositories. This repository has all the models between 575 to 1200 K (applicable for T- type objects). The models for Teff between 275 to 550 K (applicable for Y- type objects) are available in the Zenodo DOI :- <a href="../records/10381250">https://zenodo.org/records/10381250</a>. The models for Teff between 1300 to 2400 K (applicable for L- type objects) are available in the Zenodo DOI :- <a href="../records/10385987">https://zenodo.org/records/10385987</a>.</strong></p> <p> </p> <ul> <li><strong> File types and how to use them</strong></li> </ul> <p> The models have been presented in the Xarray format so that all the atmospheric properties including the T(P) profile, atmospheric chemistry, and thermal emission spectra can be accessed within the same files. A python based Jupyter notebook named "Reading and plotting Elf Owl Models.ipynb" has been also supplied which demonstrates how to open and use these files.</p> <ul> <li> <strong>Spectra</strong></li> </ul> <p> The emission spectra for each atmospheric model has been computed between 0.6 to 15 microns. The reported flux is in the units of erg/s/cm<sup>2</sup>/cm. Note that these fluxes need to be multiplied with R<sup>2</sup>/D<sup>2</sup> before comparing them with the typically observed flux of brown dwarfs/exoplanets. R is the radius of the object, and D is the distance here.</p> <div> </div> <div> <ul> <li><strong>Note on CH4</strong></li> </ul> </div> <p> As stated in <a href="https://ui.adsabs.harvard.edu/abs/2023ApJ...942...71M/abstract">Mukherjee et al. 2023 </a>our CH4 opacity is derived using the <a href="https://iopscience.iop.org/article/10.3847/1538-4365/ab7a1a">Hargreaves et al. 2020</a> HITEMP line list and computed using the HAPI code (<a href="https://www.sciencedirect.com/science/article/abs/pii/S0022407315302466">Kochanov et al. 2016</a>). HAPI automatically pre-weights the isotopologues according to earth abundances that are listed on the HITRAN website (<a href="https://hitran.org/lbl/2?6=on" target="_blank" rel="noopener noreferrer">see here for CH4</a>). Therefore, users should note that there will be minor features of CH3D included in the models. Given the general absence of deuterated molecules in brown dwarfs (Teff>~300) we will include a second posting of models which includes the Elf Owl grid with <strong>only</strong> the major CH4 isotopologue (12C-H4).</p> <div> <ul> <li><strong>Note on PH3</strong></li> </ul> </div> <p> PH3 abundance is treated separately from the general disequilibrium scheme. This is because of the current non-detection of PH3 in many brown dwarf atmospheres (see citations in paper). The current PH3 treatment uses the chemical equilibrium treatment described in Visscher et al. However, after publishing this grid and using the model for analysis of high precision JWST data, we noticed that even the simple chemical equilibrium treatment which reduces the abundance, introduces a noticeable PH3 feature. Therefore in our v2 of this model grid we will further diminish the abundance.</p>
The Sonora Substellar Atmosphere Models. IV. Elf Owl: Atmospheric Mixing and Chemical Disequilibrium with Varying Metallicity and C/O Ratios (L- type Models)
<ul> <li><strong>Overview of V2: "The Sonora Substellar Atmosphere Models. V: A Correction to the Disequilibrium Abundance of CO2 for Sonora Elf Owl"</strong></li> </ul> <p> Version 2 of the Sonora Elf Owl Models updates the CO2 and PH3 abundances and spectra. As described in the Wogan et al. (2024) research note (URL OF NOTE GOES HERE), Version 1 of the models did not apply the CO2 quench approximation properly resulting in predicted CO2 abundances that were too small by several orders of magintude in some cases. Version 2 fixes this mistake, updating CO2 abundances and the emission spectra to reflect the new CO2 abundances. Version 2 also removes all spectra contributions of PH3 because Version 1 consistently contained too much PH3 absorption when compared to JWST data (Veiler et al. 2024, <a href="http://doi.org/10.3847/1538-4357/ad6759" target="_blank" rel="noopener noreferrer">http://doi.org/10.3847/1538-4357/ad6759</a>).</p> <p> </p> <ul> <li><strong>Overview of V1</strong></li> </ul> <p> The Sonora Elf Owl Models is a successor to the <a href="../records/5063476#:~:text=This%20particular%20set%20of%20model,g%20are%200.25%20or%200.5.">Sonora Bobcat</a> and <a href="../records/4450269">Sonora Cholla</a> models. The Sonora Elf Owl model grid includes cloud-free radiative-convective equilibrium model atmospheres with vertical mixing induced disequilibrium chemistry with sub-solar to super-solar atmospheric metallicities and Carbon-to-Oxygen ratio. The atmospheric models have been computed using the open-source radiative-convective equilibrium model <a href="https://natashabatalha.github.io/picaso/">PICASO</a>. The parameters included within this grid are effective temperature (<strong><em>Teff</em></strong>), gravity (<strong><em>log(g)</em></strong>), vertical eddy diffusion coefficient (<strong><em>log(Kzz)</em></strong>), atmospheric metallicity (<strong><em>[M/H]</em></strong>), and Carbon-to-Oxygen ratio (<strong><em>C/O</em></strong>).</p> <p>The ranges and increments of these parameters are described in the published paper.<br><br></p> <ul> <li><strong>Three grids available on three links</strong></li> </ul> <p><strong> The model grid has been presented using three Zenodo repositories. This repository has all the models between 1300 to 2400 K (applicable for L- type objects). The models for Teff between 275 to 550 K (applicable for Y- type objects) are available in the Zenodo DOI :- <a href="../records/10381250">https://zenodo.org/records/10381250</a>. The models for Teff between 575 to 1200 K (applicable for T- type objects) are available in the Zenodo DOI :- <a href="../records/10385821">https://zenodo.org/records/10385821</a>.</strong></p> <p> </p> <ul> <li><strong> File types and how to use them</strong></li> </ul> <p> The models have been presented in the Xarray format so that all the atmospheric properties including the T(P) profile, atmospheric chemistry, and thermal emission spectra can be accessed within the same files. A python based Jupyter notebook named "Reading and plotting Elf Owl Models.ipynb" has been also supplied which demonstrates how to open and use these files.</p> <ul> <li> <strong>Spectra</strong></li> </ul> <p> The emission spectra for each atmospheric model has been computed between 0.6 to 15 microns. The reported flux is in the units of erg/s/cm<sup>2</sup>/cm. Note that these fluxes need to be multiplied with R<sup>2</sup>/D<sup>2</sup> before comparing them with the typically observed flux of brown dwarfs/exoplanets. R is the radius of the object, and D is the distance here.</p> <div> </div> <div> <ul> <li><strong>Note on CH4</strong></li> </ul> </div> <p> As stated in <a href="https://ui.adsabs.harvard.edu/abs/2023ApJ...942...71M/abstract">Mukherjee et al. 2023 </a>our CH4 opacity is derived using the <a href="https://iopscience.iop.org/article/10.3847/1538-4365/ab7a1a">Hargreaves et al. 2020 </a>HITEMP line list and computed using the HAPI code (<a href="https://www.sciencedirect.com/science/article/abs/pii/S0022407315302466">Kochanov et al. 2016</a>). HAPI automatically pre-weights the isotopologues according to earth abundances that are listed on the HITRAN website (<a href="https://hitran.org/lbl/2?6=on" target="_blank" rel="noopener noreferrer">see here for CH4</a>). Therefore, users should note that there will be minor features of CH3D included in the models. Given the general absence of deuterated molecules in brown dwarfs (Teff>~300) we will include a second posting of models which includes the Elf Owl grid with <strong>only</strong> the major CH4 isotopologue (12C-H4).</p> <div> <ul> <li><strong>Note on PH3</strong></li> </ul> </div> <p> In v1, PH3 abundance was treated separately from the general disequilibrium scheme. This is because of the current non-detection of PH3 in many brown dwarf atmospheres (see citations in paper). The current PH3 treatment uses the chemical equilibrium treatment described in Visscher et al. However, after publishing this grid and using the model for analysis of high precision JWST data, we noticed that even the simple chemical equilibrium treatment which reduces the abundance, introduces a noticeable PH3 feature. In v2 we completely remove the contribution of PH3. </p>
Metal Arc Welding
<h2>Predictive Quality Arc Welding Dataset</h2> <p>The dataset comprises various current and voltage time series. Both currents and voltages are synchronously sampled at a frequency 100 kHz, with a maximum permissible error of 0.5%.</p> <p> </p> <h3>Preprocessed Data</h3> <p>Column Name Description</p> <p>------------ -------------------------------------------------------------</p> <p>labels Quality label (0: bad weld quality | 1: good weld quality | -1: no label)</p> <p>exp_ids ID of the experiment run</p> <div> <div>welding_run_id : ID of the welding run</div> </div> <p>V_000 Voltage at the beginning of the cycle (t_0)</p> <p>... Voltage from (t_1) to (t_198)</p> <p>V_199 Voltage at the end of the cycle</p> <p>I_000 Current at the beginning of the cycle (t_0)</p> <p>... Current from (t_1) to (t_198)</p> <p>I_199 Current at the end of the cycle<br><br></p> <h3>Code Sample Reading the Data</h3> <pre><code>import numpy as np import pandas as pd def convert_to_np(data: pd.DataFrame) -> tuple[np.ndarray, np.ndarray, np.ndarray]: """ Convert DataFrame to numpy arrays, separating labels, experiment IDs, and features. Args: data (pd.DataFrame): Input DataFrame containing 'labels', 'exp_ids', and feature columns. Returns: tuple: A tuple containing: - labels (np.ndarray): Array of labels - exp_ids (np.ndarray): Array of experiment IDs - data (np.ndarray): Combined array of current and voltage features """ logging.info(f"Converting data to numpy array") labels, exp_ids, welding_run_ids = data["labels"].values, data["exp_ids"].values, df["welding_run_id"].values data = data.drop(columns=["labels", "exp_ids"]) cols_v = data.columns[data.columns.str.startswith("V")] cols_i = data.columns[data.columns.str.startswith("I")] current_data = data[cols_i].values voltage_data = data[cols_v].values data = np.stack([current_data, voltage_data], axis=2) return labels, exp_ids, welding_run_ids, data data_path = "" data = pd.read_csv(data_path) labels, exp_ids, welding_run_ids, data = convert_to_np(data)</code></pre> <p> </p>
Data for "Impact of Ligand Substitution and Metal Node Exchange in the Electronic Properties of Scandium Terephthalate Frameworks"
<p>The AiiDA archives of the high-throughput calculations presented in the paper "Impact of Ligand Substitution and Metal Node Exchange in the Electronic Properties of Scandium Terephthalate Frameworks".</p><p>The file "MOF_workflows.aiida" contains the actual calculation data and the files with suffix "*.yaml" contain configuration files of the workflows.</p>
Tomography Data for: Three-dimensional Nanoscale Metal, Metal Oxide and Semiconductor Frameworks through DNA-programmable Assembly and Templating
<p>This is data collected at the 3-ID Hard X-ray Nanoprobe beamline. This repository supports the following research article: </p><p>Data provided is the aligned dataset and reconstruction using a FISTA algorithm. Angles Collected -90 to +45 at 1 degree steps. </p><p><strong>Three-dimensional Nanoscale Metal, Metal Oxide and Semiconductor Frameworks through DNA-programmable Assembly and Templating</strong></p><p>By Aaron Michelson. </p><p> </p>
Mapping the core of the Tarantula Nebula with VLT-MUSE. III. A template for metal-poor starburst regions in the visual and far-ultraviolet
<p>Cumulative optical (VLT/MUSE) and far-ultraviolet (mix of HST empirical and ULLYSES templates) spectrum of NGC2070 (2x2 arcmin^2) presented in Figures 2 and 4, respectively, of Crowther & Castro (MNRAS in press, https://arxiv.org/abs/2311.07642) which should be cited if either dataset is used. </p><p>Contents:</p><p>MUSE.dat (ascii format, column 1 wavelength in Angstrom, column 2 flux in erg/s/cm^2/Ang). Further details of MUSE dataset is described in N. Castro et al. (2018 A&A 614 A147)</p><p>ULLYSES.dat (ascii format, column 1 wavelength in Angstrom, column 2 flux in erg/s/cm^2/Ang, some detector gaps). Further details of ULLYSES survey is described in R. Roman-Duval et al. (2020, Research Notes of AAS, 4, 205)</p>
Metal on Ceramic Friction Surfacing Data for Printing Electronics
<p>This repository is for data for an upcoming paper that presents work using micro friction surfacing for applying in-situ maskless metallizations and robust seed layers for electroless plating on demand to substrates like, aluminum oxide, aluminum nitride, and as fired LTCC, for fabrication of next generation power module and other high reliability electronic substrates. </p> <p>An adjoining youtube playlist, with unique video identifiers that correspond to data in the provided excel data sheets, of all raw video footage of the friction surfacing process can be found <a title="Metal on Ceramic Friction Surfacing playlist" href="https://youtube.com/playlist?list=PLxlbqMdRe6OVbtT3ehHzCJgsyfsY8-2mJ&si=QhrZ0YftJCpKQ3uq" target="_blank" rel="noopener">here:</a><br><br></p> <p>New generation power modules provide compact form factors while achieving multi kilovolt drive potentials at kiloamp currents.[1] However, their typical packaging and substrate metallization methods, such as thick film, direct bond copper, and active metal braze, limits attachment options and other manufacturing process requirements while incurring large processing costs and extended lead times for researchers and industry.[2]–[5] High speed micro friction surfacing allows for directly writing pure metal conductors and integrated passives, onto common insulating high reliability electronics substrates, supports additional layers of metallization and provides direct device interconnect before or after die fabrication and bonding, without bulk thermal annealing and without damaging the underlying substrate. Thus, making the next generation of power devices more tenable at the prototype level, and with further process refinements, at industrial scale.[6]–[13] This work highlights the importance of rapid and flexible prototyping for next generation power modules and high reliability electronics, and how finding new ways to use existing tooling can enhance fabrication options and potentially shore up semiconductor prototyping supply chain stability</p> <h2>1. Introduction</h2> <p>Current generation power modules and high-reliability electronics require rapid and flexible prototyping, but current fabrication methods using thin and thick film, ultrasonic soldering, direct oxide bonding and active metal brazing, have limitations due to exotic interface metallization, atmosphere control, and thermal cycling requirements during fabrication and deployment [2], [3], [5]. These limitations particularly apply to silicon carbide devices, where typical wire bondable aluminum, active metal brazed gold-titanium and direct bond copper substrate metallization schemes incur large fabrication costs and lead times while inhibiting rework of as fabricated substrates due to deep vacuum/ high temperature requirements and a substantial need for skilled manual labor [14], [15]. </p> <p>In this work, High Speed Micro-Friction Surfacing(HSMFS) is used to metallize substrates of aluminum oxide, aluminum nitride, and as fired LTCC, with millimetric to sub-millimeter, traces made of, copper, and gold. HSMFS enables relatively automated, single step fabrication of single layer electronic circuits with bond strengths that exceed thin and thick film methods and ultrasonic soldering, at a cost and lead time 20-50X less, without need for skilled labor. HSMFS is a downscaled extension of a broader class of methods known as "friction surfacing" wherein a rod or powder of a material to be coated onto a substrate, is stirred by rotating a tool, or "mechtrode" against the substrate, trapping the material to be deposited between the mechtrode and substrate surfaces.[1]–[3] The mechtrode can be either a wire of material that is consumed as deposition proceeds, or a non-consumable tool made of a hard material that resists wear during deposition. Heat is generated due to friction between mechtrode and substrate, and forging pressure is applied from a CNC motion platform. The combination of heat from friction, mechano-chemical activation, and forging pressure induced plastic deformation results in the shearing, viscoplastic flow and chemical and mechanical bonding of material from the mechtrode to the substrate being coated. </p> <p>While there have been previous examples of friction surfacing metals onto ceramic substrates[4], [5], none have been used in electronics applications, and no characterization of relevant electro-thermal properties and endurance has been carried out. Additionally, the typically centimeter or larger deposit size scale of the mechtrode and consequently large supporting machinery in previous work has meant that the technique would be unsuitable for fabricating modern electronics. This large mechtrode scale results in excessive, evolved heat at the interface and thus high probability of heat shock damage to ceramic materials. Further, the relatively low mechtrode rotational speeds used in most prior works, results in very high forging pressures (hundreds of MPa), which typically far exceed the fracture toughness of common ceramic substrates. We have overcome these limitations and managed to obtain near bulk metallic electronic properties in as deposited track widths as small as 0.5mm, and metallization thicknesses from nanometers to 10's of microns on frangible substrates without damaging the substrate or compromising its electro-thermo-mechanical endurance. </p> <h2>2. Materials and Methods</h2> <p> </p> <h2>2.1 Materials and tools</h2> <p>For this study the raw materials used to produce the printed prototype as fired circuits were provided by Tommy's Watch and Jewelry via Stuller Precious Metals, (1.6mm copper, #43-6421:100000:T and 0.6mm gold wire, #WIRE:9698:P) and The University of Arkansas High Density Electronics Center (HiDEC), (Dupont 1mm thick 951 LTCC, Stellar Industries 0.5mm thick 99% aluminum nitride, and 0.5mm thick 96% alumina ceramics). </p> <p>The process parameters for printing tracks of copper and gold on the three substrates of interest were explored using a genmitsu 1610 minimill with a Dremel "multipro" 30,000 RPM rotary tool as it's spindle, and a 26 gauge 1070 spring steel sheet covering the mill bed between the aluminum t-slotbed and the ceramic substrate being printed on, purchased on amazon. Each substrated was held in place with a set of binder clips to keep it firmly in position nad flat against the spring steel sheet during deposition. Each deposition process was recorded in thermal video(Flir-T300) (courtesy of Dr. Darin Nutter) with a microscope camera(Opti-Tekscope OT-HD) and in real time macro video (Nikon D750). Subsequent profilometry (Dektak3030) electrical resistance (Fluke 77), current handling testing, taklife and ACS723 current sensor, and Flir-T300 camera (courtesy of Dr. Darin Nutter), and film strength (Kapton pull tests) measurements were performed with tooling available at HiDEC. <br>Temperature data were extraced via optical character recognition using the script here:<br>https://github.com/mahydraal/OCRDataExtractor<br>it deploys tesseract OCR and relatively simple python script with tkinter to provide a graphical user interface to select a region of a video, scrub it for noise, convert it to black and white, and then read character data from the user selected region. </p> <h2>2.2 Determination of printing parameters</h2> <p>Metals, copper and gold, were deposited on substrates of 96% alumina, 99% aluminum nitride(Al-N) and fired 951 LTCC, from wires of 1.6mm and 0.6mm OD respectively, via high speed micro friction surfacing (HSMFS). Spindle RPM was set open-loop constant to 30K RPM, and surface feed velocity was varied between 15, 45 and 75 mm/minute at a constant ratio of X-Z feed distance of 80 to approximate a constant normal force at the stall torque of the Z axis motor of the motion frame in open loop mode. Each surface feed velocity set point was tested 3 times for each metal substrate combination. Each metal and substrate combination were cleaned with 90% IPA and 90% Acetone and Di rinsed then blown dry with nitrogen before deposition.</p> <p>Friction surfacing is a solid-state joining process that involves rubbing two surfaces together at high speeds under pressure, creating a bond between the two surfaces without melting them, stereotypically shown in figure. The process can be used to join similar or dissimilar metals and alloys, metals and ceramics, and organics, and is particularly useful for joining materials with high melting points, such as titanium and nickel-based alloys without obtaining fusion and melting temperatures and without protective atmosphere. This process generates significant waste heat from friction and plastic deformation, which is useful for monitoring and controlling deposition consistency, thus real time thermographic videos during each test were collected using a FLIR T-300 thermal camera, and optical character recognition on it's display to obtain insight into the deposition temperature trends at the substrate-feedstock interface and better tune the surface feed-velocity at constant RPM to obtain electronic continuity in the as deposited metallic tracks on each ceramic substrate type. Real time macro videography was performed on each test to provide post-facto analysis and record any anomalies that would not be representative of typical performance. </p> <p>An appropriate spindle speed for deposition must be selected as well as appropriate vertical and linear feeds and speeds for the mini mill in micro friction surfacing. This is generally due to the need for a specific surface energy threshold associated with frictional heating and mechanical surface activation to be obtained between the feedstock and the substrate. This surface energy must exceed the free energy of reaction for diffusion and bonding to occur between the atoms of the substrate and those of the feedstock. A list of energies of formation for various transition metal carbides and oxides, necessary for bonding of metals to carbide and nitride sub-states by friction surfacing is shown. </p> <p>In short, by controlling spindle speed surface feed rate, and providing a constant down force by constant Z-X feed rate ratio on the minimill, it is possible to set a constant rate of heat evolved at the friction interface between the feedstock and substrate. If this heat evolved exceeds the heat of formation of a bonding compound of interest for long enough, the reaction of interest can proceed and a tenacious bond between metal and substrate can form. The details of accurately modeling heat evolved in friction surfacing, given the details of a specific deposition system and feed stock geometry are elucidated well elsewhere, [29], [30] so we will not go into them here. The primary point being that one can approximate appropriate deposition parameters for almost any material combination, knowing the free energy of formation of an appropriate bonding phase, and or the pressure-temperature phase diagram for the material pair of interest.</p> <h2>2.3 Characterization and measurement of test films</h2> <p>Bond strength of the HSMFS deposited films of copper and gold were tested initially by simple kapton tape pull testing, thereby assigning a minimum failure stress on film bond strengths. Temperature trends recorded during the deposition via thermography were correlated with resultant film resistivities and average height profiles and cycling performance for each set of parameters, each metal and each substrate; the most consistent and robust parametrization results were used in subsequent experiments to fabricate basic current carrying tracks with a mix of soldered and wire bonded terminals to demonstrate feasibility of HSMFS for rapid prototyping of electronics. </p> <h3>2.3.1 Electrical resistivity extraction and profilometry</h3> <p>Each material deposition was followed by profilometry (Dektak3030) at 3 points along each track, averaging the resultant maximum heights to determine film thickness and calculate sheet resistivity from resistance measurements on the multimeter(Fluke 77).</p> <h3>2.3.2 Maximum ampacity testing</h3> <p>Each printed specimen was terminated with copper tape, and soldered/wire bonded respectively. A taklife DC benchtop power supply was used to supply DC 31 volt power at up to 11 amps of current. An Arduino and high current shunt resistor current sensor measured the current flowing through the printed track, and acted to provide automatic control of current ramp up time. The current through the printed track was stepped up by the Arduino in steps of 25 milliamps every 60 seconds to provide time for thermal equilibration and avoid substrate fracture. This process continued until the track failed due to shorting, thermal breakdown, or electromigration failure. </p>
Dynamical Parameters and Clustering Results for Four-hundred Very Metal-Poor Stars Studied with LAMOST and Subaru
<p>This is the data associated with the paper "Four-hundred Very Metal-Poor Stars Studied with LAMOST and Subaru. III. Dynamically Tagged Groups and Chemodynamical Properties" by Zhang, Matsuno, Li et al. 2024. Table "LSVMP_HRdata_dynamics.csv" contains the dynamical parameters and clustering results of the HR sample in this paper. File "readme.txt" describes the meaning of each column in the table and the notes for the flag of stars. </p> <p>This sample is obtained by the LAMOST/Subaru joint project. See our paper I (DOI: 10.3847/1538-4357/ac6515) for detailed descriptions of target selection and observations, paper II (DOI: 10.3847/1538-4357/ac6514) for the chemical abundance analysis, and paper III (DOI: 10.3847/1538-4357/ad31a6) for clustering and chemodynamical analysis.</p> <p>If you have any questions about this data, please contact lhn@nao.cas.cn or rz.richie.zhang@gmail.com for more information.</p>
Fig 1 in Different responses of epigeic beetles to heavy metal contamination depending on functional traits at the family level
Fig 1. Diagram of non-metric multidimensional scaling of beetle assemblages classified to three groups of contamination (square- almost uncontaminated sites, circle- moderately contaminated sites, diamond- highly contaminated sites)
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