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1,542 results for “Degradation”
Enhanced degradability of thiol-ene composites through the inclusion of isosorbide-based polycarbonates
<p><span>Open reduction internal fixation (ORIF) metal plates and screws remain the established standard-of-care for complex fracture fixation. They however have drawbacks such as limited customization, soft-tissue adhesions and a lack of degradation. Bone cements and composites are being developed as alternative fixation techniques in order to overcome these issues. One such composite is a strong, stiff and shapeable hydroxyapatite-containing material consisting of 1,3,5-triazine-2,4,6-trione (TATO) monomers which cures through high energy visible (HEV) light induced thiol-ene coupling (TEC) chemistry. Previous human cadaver and <em>in vivo</em> studies have shown that patches of this composite provide sufficient fixation for healing bone fractures; however, the composite lacks degradability. To promote degradation through hydrolysis, new allyl-functionalized isosorbide-based polycarbonates have been added into the composite formulation and their impact has been evaluated. Three polycarbonates with allyl functionalities, located at termini (aPC1 and aPC2) or in the backbone (aPC3), were synthesized. Composites containing 1, 3 and 5 wt% of aPCs 1-3 were formulated and evaluated with regards to mechanical properties, water absorption, hydrolytic degradation and cytotoxicity. Allyl-functionalized polycaprolactone (aPCL) was synthesized and used as a comparison. When integrated into the composite, aPC3 significantly impacted the material’s properties, with the 5wt% aPC3 formulation showing a significant increase in degradation of 469 %, relative to the formulation not containing any aPCs after 8 weeks’ immersion in PBS, along with a modest decrease in modulus of 28 % to 4.01 (0.3) GPa. Osteosyntheses combining the aPC3 3 and 5 wt% formulations with screws on synthetic bones with ostectomies matched or outperformed the ones made with previously studied neat composite with regards to bending stiffness and strength in 4-point monotonic bending before and after immersion in PBS. The favorable mechanical properties, increased degradation, and non-toxic characteristics of the materials present aPC3 as a promising additive for the TATO composite formulations. This combination resulted in stiff composites with long-term degradation suitable for bone fracture repair. </span></p>
Photographic record of land degradation and resilience in Dogu'a Tembien after the shock of the Tigray war (northern Ethiopia)
<p><span>Following two years of combat, blockade, and power outage, the Tigray war in northern Ethiopia has had a substantial negative impact on the environment (2020–2022). This photographic dataset, part of a rare study carried out by the same research team before and after a war, compares 26-year legacy data on land degradation, with post-war observations at 56 sites in the Dogu'a Tembien district of Tigray (13°39'N, 39°30'E), at elevations ranging from 1600 to 2800 meters.</span></p> <p><span>With 30 years of environmental research experience in Tigray, we remained as a lone research team after the start of the war and collected ground data at previous research sites during the war. This culminated in international partners returning to the Dogu'a Tembien district in 2023 after they had been absent for four years due to coronavirus restrictions and the Tigray War. We visited 56 previously investigated sites—which have been documented in 45 prior publications—through transect walks, where we mostly made qualitative observations and discussions regarding the processes of land degradation and recovery. This included degradation processes like sheet and rill erosion</span><span>, gully erosion</span><span>, landslides</span><span></span><span>, deforestation</span><span>, as well as the most common rehabilitation approaches, i.e. stone bunds</span><span>, check dams</span><span>, exclosures</span><span>, improved hydrological cycle</span><span>, and integrated catchment management</span><span>. Local farmers and other village residents, along with experts who either reside in or have a good understanding of the research area, participated in the group observations.</span></p>
Plasmid Maps for a Nuclear Transformation Vector in Chlamydomonas reinhardtii for the Expression and Secretion of the Plastic-Degrading Enzyme (PHL7)
<p><strong>pJP32PHL7 Vector:</strong></p> <ul> <li> <p><strong>Size:</strong> 5692 bp</p> </li> <li> <p><strong>Key Features:</strong></p> <ul> <li><strong>HSP70 Promoter:</strong> A heat shock protein promoter fused with the <em>rbcS2</em> promoter to drive expression of downstream genes.</li> <li><strong>Ble Resistance Gene:</strong> Confers resistance to bleomycin, useful for selection in <em>Chlamydomonas reinhardtii</em>.</li> <li><strong>PHL7 Gene:</strong> Encodes the plastic-degrading enzyme PHL7, inserted downstream of the <em>F2A</em> site for expression in the host.</li> <li><strong>Intron Sequences:</strong> Contains multiple <em>rbcS2</em> introns for enhancing expression in <em>Chlamydomonas</em>.</li> <li><strong>Selectable Marker (AmpR):</strong> Confers ampicillin resistance for selection in <em>E. coli</em>.</li> <li><strong>Replication Origin:</strong> Includes <em>ori</em> and <em>F1 ori</em> for replication in <em>E. coli</em>.</li> </ul> <p> </p> </li> <li> <p><strong>Applications:</strong> This vector is designed for nuclear transformation in <em>Chlamydomonas reinhardtii</em>, enabling the expression and secretion of the plastic-degrading enzyme (PHL7) under the control of a hybrid <em>HSP70</em>rbcS2 promoter.</p> </li> </ul> <p><strong>pJP32PHL7dg Vector:</strong></p> <ul> <li> <p><strong>Size:</strong> 5692 bp</p> </li> <li> <p><strong>Key Features:</strong></p> <ul> <li><strong>HSP70 Promoter:</strong> Retains the HSP70 and <em>rbcS2</em> fusion promoter for gene expression.</li> <li><strong>LacZ Alpha Fragment:</strong> Includes a LacZ alpha fragment for blue/white screening.</li> <li><strong>PHL7 Gene:</strong> Encodes the plastic-degrading enzyme PHL7, linked downstream of the <em>F2A</em> site, allowing for expression in the host.</li> <li><strong>Ble Resistance Gene:</strong> Also confers bleomycin resistance for selection in <em>Chlamydomonas</em>.</li> <li><strong>Selectable Marker (AmpR):</strong> Confers ampicillin resistance for selection in <em>E. coli</em>.</li> <li><strong>Intron Sequences:</strong> Contains <em>rbcS2</em> introns for optimizing gene expression in the host organism.</li> </ul> <p> </p> </li> <li> <p><strong>Applications:</strong> The pJP32PHL7dg vector is similarly designed for nuclear transformation in <em>Chlamydomonas reinhardtii.</em> It also facilitates the expression and secretion of the plastic-degrading enzyme PHL7, driven by the hybrid <em>HSP70</em>rbcS2 promoter, but without glycosilation sites.</p> </li> </ul>
Size-dependent effects of oxo-degradable plastic contamination on soil quality and Zea mays L. performance
<p><span>Agricultural plastic mulch films represent a significant source of microplastic contamination in soils, raising concerns about soil health and food security. Oxo-degradable plastics (ODPs) have emerged as a potentially more eco-friendly alternative to conventional plastic mulch films, however, uncertainty remains around the degradation rate of ODPs in soil and their impacts on soil quality and crop health. Using a controlled mesocosm experiment, we evaluated the behaviour and impact of different concentrations of oxo-biodegradable macro- (>10 mm) or micro-plastic (<5 mm) (0.01, 0.1, 1, and 10% w/w) on the performance of <em>Zea mays</em> L. grown in an agricultural soil over a 6-week period. Contrary to expectation, no major fragmentation or degradation of ODP was observed during the experimental period, however, FTIR revealed the formation of carbonyl groups indicative of oxidation. Overall, our results showed that typical levels of plastic contamination (0.01% w/w) had very little effect on soil physicochemical properties, microbial activity or plant performance. However, higher levels of plastic contamination resulted in significant changes in soil pH, EC, NO<sub>3</sub><sup>-</sup>, bulk density, and soil moisture. At extreme plastic loading rates (10% Can you write w/w), both micro- and macro-sized ODPs caused significant reductions in plant height and foliar chlorophyll content, with microplastic treatments showing consistently greater effects than macroplastics. None of the plastic loading rates had an effect on shoot and root biomass or soil NH<sub>4</sub><sup>+</sup> and P concentrations or microbial community structure in comparison to the unamended controls. Our findings indicate that at realistic field concentrations, ODPs are likely to have little effect on agroecosystem functioning but that they may persist in soil for long periods of time leading to their progressive accumulation in agricultural soils if used over repeated cropping cycles. Further research is needed to evaluate the longer-term impacts of ODPs on soil quality and crop health under field conditions.</span></p>
Dataset: Utilization of Novel (KNbO3)1-x(Ba2FeNbO6)x (x = 0.1, 0.2, 0.3) Solid Solutions for Efficient Photo-assisted Fenton Degradation of Methylene Blue Dye
<p>Supplemental information containing the inputs and outputs of all DFT calculations performed as part of this work.</p> <p>This archive contains the following scripts:</p> <ul> <li>defects_workup.py: a Python script for processing all calculations in a given folder. It extracts the total energy, estimated SCF accuracy (for non-converged results), and convergence status (true/false) for all cases found in each subfolder. For converged calculations, the mean Ba-Ba distance and its standard deviation as well as the mean Ba-Fe distance and its standard deviation is calculated. </li> <li>bands_plotter.ipynb: a Jupyter notebook for band structure analysis.</li> <li>ase_rdf.ipynb: a Jupyter notebook for bond distance vs energy analysis</li> </ul> <p>Furthermore, the following data is included:</p> <ul> <li>3x2x2.json: the output json file generated for the 3x2x2 dataset using defect_workup.py</li> <li>3x2x2.7z: a compressed folder containing the 3x2x2 dataset with QE input and output files.</li> <li>3x2x2-v2.7z: a compressed dataset containing some supplementary calculations used in band plotting.</li> </ul>
Source data for Synthetic dynamic hydrogels promote degradation-independent in vitro organogenesis
<p>Source data and statistical analysis results for Synthetic dynamic hydrogels promote degradation-independent in vitro organogenesis</p>
Supplementary Data for "Substrate-Assisted Mechanism for the Degradation of N-glycans by a Gut Bacterial Mannoside Phosphorylase"
<p>This dataset contains atomic coordinates of the molecular dynamics simulations described in "Substrate-Assisted Mechanism for the Degradation of N-glycans by a Gut Bacterial Mannoside Phosphorylase" by M. Alfonso-Prieto, I. Cuxart, G. Potocki-Véronèse, I. André and C. Rovira, published in ACS Catalysis (https://doi.org/10.1021/acscatal.3c00451). Further details on the setup of the simulations can be found in the Supplementary Information of the article. </p> <p>If you use this dataset, please cite this zenodo upload (https://doi.org/10.5281/zenodo.7704778), as well as the the original journal article (https://doi.org/10.1021/acscatal.3c00451). </p> <p>This dataset is organized in the following folders:</p> <p><strong>Snapshots_Figures_Main_Text.zip</strong>, that contains a README.txt file and:</p> <p><strong>- Figure_3</strong> contains representative structures (atomic coordinates) of the hexameric form of UhgbMP in complex with 3 different disaccharide molecules, Man-b-(1,4)-GlcNAc, Man-b-(1,4)-Glc and Man-b-(1,4)-Man.</p> <p><strong>- Figure_4</strong> contains representative structures (atomic coordinates) of the hexameric form of UhgbMP at the three minima observed along the reaction coordinate corresponding to phosphorolysis of the disaccharide Man-b-(1,4)-GlcNAc: Michaelis complex (MC), transition state (TS) and product (P) complex.</p> <p>Files in this dataset are in PDB format. For all structures, the solvation box (water and ions) has been stripped to reduce file size. See README.txt inside <a href="https://zenodo.org/api/files/f3836540-b7b6-4820-87b3-7fa5dff7840c/Snapshots_Figures_Main_Text.zip">Snapshots_Figures_Main_Text.zip </a>for more information.</p>
Dataset for 'Organic Electrochemical Transistors Printed from Degradable Materials as Disposable Biochemical Sensors'
<p>This data set contains the data collected during the FNS project Green Piezo (Grant no. 179064) in association with the publication entitled “Organic Electrochemical Transistors Printed from Degradable Materials as Disposable Biochemical Sensors”.</p> <p>This work aims to study the fabrication of organic electrochemical transistors using more environmentally-friendly materials, in particular carbon contacts and polylactic acid (PLA) as substrate. Organic electrochemical transistors (or OECTs) offer applications in biosensing, for example for point-of-care devices. We use a combination of additive manufacturing methods (screen printing and inkjet printing) to manufacture these transistors and solve the issues with fabricating them on a low-temperature substrate such as PLA. We also assess these transistors as disposable sensors for the detection of various ion concentrations as well as glucose. The data that was collected in the frame of this work is present in this repository. More information about the contents of the dataset is present in the included README files.</p>
Voltage-based strategies for preventing battery degradation under diverse fast-charging conditions
<p>Here are the simulated datasets for the work 'Voltage-based strategies for preventing battery degradation under diverse fast-charging conditions', published in ACS Energy Letters, September 2023. The utilization of these datasets is demonstrated in the associated GitHub project folder https://github.com/zachkonz/Voltage-based-plating-prevention.</p>
Comparison of polyphenol degrading enzyme activities between forest types and soil horizons from 2003 to 2004
In the southern Appalachians Rhododendron maximum thickets suppress conifer and hardwood regeneration. While there has been research on the effects of R. maximum on physical and chemical environment, the functioning of R. maximum ericoid mycorrhizas has been unexplored. The litter of ericaceous plants tends to be rich in phenolic compounds. These compounds can form recalcitrant complexes with various forms of organic N, and may be responsible for lowering decomposition and N mineralization rates. While polyphenol-organic N complexes are highly recalcitrant, some fungi, particularly ericoid mycorrhizal fungi, have the ability to access this sequestered N. Since the litter of ericaceous plants is rich in phenolic compounds and ericoid mycorrhizal fungi are equipped to degrade phenolic compounds, polyphenol-organic N complexing may represent an N cycling strategy that prevents non-ericaceous plants from accessing sources of organic N. We propose to examine the activities of polyphenol degrading enzymes in the soil of R. maximum thickets and neighboring hardwood forests.
Mesocoms investigation of seaweed fragment degradation and skinking rates
<p>This dataset provides the results of a 35 day investigation of macroalgal fragment degradation and sinking rates, that took place in late summer and autumn of 2017, in Plymouth Marine Laboratory, UK. Specimens were collected by hand, from the shore at Rame Head (50°18' 41.9″ N 4°13' 15.9″ W). Sinking rates were estimated in a stationary seawater column in the laboratory, and are provided against fragment weight for 3 species of macroalgae, at the beginning and end of incubations. Experimental conditions are described.</p>
A dataset of 3D fly (Drosophila melanogaster) flight trajectories to study the role of neuropeptide degradation in visuo-motor behaviors.
<p>As part of a wide study on the role of neuropeptides in the visuo-motor behavior of Drosophila melanogaster, we exposed three fly strains with impaired neuropeptide degradation function, and corresponding controls, to different visual stimuli.</p> <p>Find further details in the provided README.</p>
Dataset for: "Additively manufactured degradable piezoelectric microsystems for sensing and actuating"
<h2>Dataset for "Additively manufactured degradable piezoelectric microsystems for sensing and actuating"</h2><p><strong>Morgan Monroe1,2, Nicolas Fumeaux1, L. Guillermo Villanueva2, and Danick Briand1</strong></p><p><strong>1Soft Transducers Laboratory (LMTS), EPFL, Switzerland</strong></p><p><a href="mailto:morgan.monroe@epfl.ch">morgan.monroe@epfl.ch</a>, <a href="mailto:danick.briand@epfl.ch">danick.briand@epfl.ch</a></p><p><strong>2Advanced NEMS Laboratory (A-NEMS), EPFL, Switzerland</strong></p><p> </p><p>This data set contains the data collected during the FNS project Green Piezo (Grant no. 179064) in association with the recent publication entitled "Additively manufactured degradable piezoelectric microsystems for sensing and actuating" </p><p><strong>DOI: 10.1002/admt.202300745</strong></p><p>-------------------------------------------------------------------------------------------------------------------------------</p><h3><strong>Manuscript Abstract: </strong></h3><p>The increasing global overabundance of electronic waste and concerns regarding the energy and material-intensive processes associated with traditional electronics manufacturing is driving the development of solution processed, degradable electronics. In particular, solution processed, degradable piezoelectrics have widespread potential in sustainable electronics, due to their diverse use in both sensing and actuating applications and the current industry predominance of lead-based materials. Yet current eco-friendly multi-material printing processes are limited by both the conventional challenges of multilayer process integration as well as the low-temperature thermal constraints of biodegradable materials. In this study, we present a novel approach to the fabrication of additively manufactured and sustainable piezoelectric devices made with degradable electrode materials on paper substrates. The screen-printed, eco-friendly KNbO3 piezoelectric transducers are combined with degradable carbon- or zinc-based conductive inks. We evaluate the physical, dielectric, and piezoelectric properties of the devices, assessing the influence of electrode material on device performance. We report on effective piezoelectric coefficients as high as 4.6 pC N-1 and 5.1 pC N-1 for printed piezoelectric devices on paper substrates with carbon and zinc electrodes respectively. We then demonstrate the applicability of the developed technology in both sensing and actuating applications. Thus, we present the first instance of sustainable fully additively manufactured piezoelectric force sensors and acoustic speakers. By demonstrating entirely printable piezoelectric devices compatible with various green electrode materials, we work to develop more complex sustainable printed piezoelectric technologies in the future.</p><p> </p><h3>The data set consists of the following folders:</h3><ul><li>Device design files</li><li>Physical characterization data</li><li>Dielectric characterization data</li><li>Force Sensor Demonstrator data</li><li>Speaker Demonstrator data</li></ul><p>Below is a detailed description of the data types and contents of each folder. In many files, the naming convention includes one of two key material indicators. In reference to ink properties, the term "Ink Active Material" indicates the primary ingredient in the ink being characterized. This is either KNbO3, Zinc, or Carbon. The specific ink compositions can be found in the Methods portion of the associated manuscript. In reference to devices being characterized, the term "Electrode Material" indicates the primary component of the printed or deposited electrode layers of the devices (as the piezoelectric layer is always the printed KNbO3 film). The electrode materials are either "Gold" (referring to thermally evaporated Gold of approximately 100nm thickness) which was used as a reference electrode material, "Zinc" (referring to screen printed zinc ink as described in the manuscript), or "Carbon" (Referring to screen printed carbon ink as described in the manuscript).</p><p>-------------------------------------------------------------------------------------------------------------------------------</p><h3><strong>Data types</strong></h3><p>There are 13 file types in this data set: .pdf, .png, .tif, .txt, .dat, .csv, .svg, .stl, .py, .vi, .dwf3work, .aup3, .wav</p><ul><li><strong>.pdf files </strong><ul><li>pdf files in this repository contain summaries of images used in physical characterization, aggregated for ease of visualization. These are exported from Photoshop files and thus include full image information.</li></ul></li><li><strong>.png and .tif files </strong><ul><li>These files contain scanning electron microscopy images of the printed samples on silicon, in cross-section.</li></ul></li><li><strong>.txt, .csv, and .dat files </strong><ul><li>These files contain raw data from device characterization. These file types are comma delimited and the files can be opened with text editors such as Notepad++. Column headers elaborate on the data contained within each file. </li></ul></li><li><strong>.svg files </strong><ul><li>These files contain vector data displaying the full designs of devices fabricated in this study. This data can be opened with a vector graphics editor such as InkScape. The various layers of each file denote a different layer of the device design, and can be treated individually as masks for the relevant layers.</li></ul></li><li><strong>.stl files </strong><ul><li>These files contain design information for 3D components. These files can be opened with any 3D design software such as FreeCAD. All .stl files included in this repository are reproduced from Shannon Ley (<a href="https://pinshape.com/items/36134-3d-printed-3d-printed-headphones">https://pinshape.com/items/36134-3d-printed-3d-printed-headphones</a>).</li></ul></li><li><strong>.py files </strong><ul><li>These files contain python scripts used to process the raw data after collection. These scripts can be opened and edited with standard python scripting interfaces. Each script is commented with descriptions of the overall file as well as in-line comments for user orientation. </li></ul></li><li><strong>.vi files </strong><ul><li>These files contain LabVIEW scripts used to collect raw data during measurements. These scripts can be opened and edited with LabVIEW from version 2020. The script is commented with descriptions of the overall file as well as in-line comments for user orientation. Only one file in this dataset is of this filetype.</li></ul></li><li><strong>.dwf3work files</strong><ul><li>These files contain Digilent Waveforms workspaces used to collect raw data during measurements. These scripts can be opened using the opensource Digilent Waveforms software (<a href="https://digilent.com/shop/software/digilent-waveforms/">https://digilent.com/shop/software/digilent-waveforms/</a>) to view the recorded data and all relevant recording parameters at time of measurement. </li></ul></li><li><strong>.aup3 files </strong><ul><li>These files contain Audacity workspaces used to collect and process audio data during speaker characterization measurements. These files can be opened using the opensource Audacity software (<a href="https://www.audacityteam.org/">https://www.audacityteam.org/</a>).</li></ul></li><li><strong>.wav files </strong><ul><li>These files are audio files of the data exported from Audacity during speaker device characterization and can be opened with any audio processing software.</li></ul></li></ul><p>-------------------------------------------------------------------------------------------------------------------------------</p><h3><strong>01 Characterization Device Design</strong></h3><p>This folder contains the design files associated with the fabrication of the basic printed devices used for characterization studies.</p><h4><strong>01 CapacitorsALL.svg</strong></h4><p>A vector file containing the whole-device design of the capacitor style devices used in primary characterization. Each layer of the file is a layer of the device, and was used for the ordering and fabrication of associated screen printing meshes and shadowmasks.</p><h4><strong>02 BottomElectrode.svg</strong></h4><p>A vector file containing the design of solely the bottom electrode layer for devices used in primary characterization. This design was used for the ordering and fabrication of associated screen printing meshes and shadowmasks.</p><h4><strong>03 PiezoelectricLayer.svg</strong></h4><p>A vector file containing the design of solely the piezoelectric layer for devices used in primary characterization. This design was used for the ordering and fabrication of associated screen printing meshes and shadowmasks.</p><h4><strong>04 TopElectrode.svg</strong></h4><p>A vector file containing the design of solely the top electrode layer for devices used in primary characterization. This design was used for the ordering and fabrication of associated screen printing meshes and shadowmasks.</p><p>-------------------------------------------------------------------------------------------------------------------------------</p><h3><strong>02 Physical Characteristics</strong></h3><p>This folder contains all the data associated with characterizing the physical properties of the piezoelectric devices in this manuscript.</p><h4><strong>01 Particle Size Analysis</strong></h4><p><strong>01 Images</strong>: A folder of SEM images as .png files. These images are cross-sectional SEM images of samples used to evaluate the particle size distribution for the KNbO3, Zinc, and carbon powders using in device fabrication. A second set of images with an appended filename ("traces") in the same folder portrays the sizing lines used to randomly sample particles for sizing.</p><p><strong>02 ParticleSizeDistribution_RAW.csv</strong>: A data file containing the raw measurements collected using the above images in tandem with ImageJ processing software. Data was used to produce histograms of particle size distributions for the KNbO3, Zinc, and Carbon particles.</p><p> </p><h4><strong>02 Profilometry</strong></h4><p><strong>01 Profilometry Data</strong>: A folder of raw data collected as profilometry measurements in the form of .dat files. Data files are labelled using the convention "Profile_[Electrode Material]_DeviceStack_Sample[#].dat" (Ex: "Profile_Carbon_DeviceStack_Sample2.dat"). All measurements begin with a measure of the paper substrate as reference before approaching the sample, where it crosses all 3 layers of the sample before returning to the paper substrate, creating a series of layer-cake-like steps from which layer thicknesses can be determined.</p><p><strong>02 ProfilometeryDataPlotter.py</strong>: a python script to batch import and plot the above collected raw profilometry data. </p><p> </p><h4><strong>03 Cross-section Optical Images</strong></h4><p>A folder containing optical microscopy images of the printed devices in cross-section when printed on paper substrates. The naming convention used is "Optical_[Electrode Material]_[microscope Magnification]_[Image number in that condition].tif" (Ex: "Optical_Carbon_x50_01.tif").</p><p> </p><h4><strong>04 Cross-section SEM Images</strong></h4><p>A folder containing scanning electron microscopy ("SEM") images of the printed devices in cross-section when printed on silicon substrates. The naming convention used is "SEM_[Electrode Material]_[microscope Magnification]_[Image number in that condition].tif" (Ex: "SEM_Carbon_1k_01.tif").</p><p> </p><h4><strong>05 Ink Rheology </strong></h4><p>Summary data collected during rheological measurements of the KNbO3, Zinc, and Carbon inks, as .txt files. The naming convention is "Viscosity_[Ink Primary Component]Ink.txt" (Ex: "Viscosity_ZincInk.txt")</p><p> </p><h4><strong>06 Degradation Study </strong></h4><p><strong>01 DegradationStudy_MassChange.csv</strong>: A data file containing the raw measurements collected during the degradation studies. Data includes the specific samples under test and their measured mass at specific dates, as measured after drying.</p><p><strong>02 Degradation Study Images.pdf</strong>: a .pdf file containing the raw degradation images used in this study, correlated to the dates of imaging and text conditions. </p><p>-------------------------------------------------------------------------------------------------------------------------------</p><h3><strong>03 Electrical Characteristics</strong></h3><p>This folder contains all the data associated with characterizing the dielectric and piezoelectric properties of the piezoelectric devices in this paper.</p><h4><strong>01 Impedance Data</strong></h4><p><strong>01</strong> <strong>ImpedanceDataAnalysis.py </strong></p><p>The python analysis script used to batch analyze and plot the raw impedance data collected for these samples. Takes the files in the associated folder as input and outputs arrays of measured capacitance and permittivity values for the data analyzed, as well as plots of the processed impedance data as a function of frequency.</p><p><strong>02 Raw Impedance Data</strong></p><p>The raw impedance data used to evaluate the dielectric properties of the devices, including two file types: </p><p><strong>".csv"</strong>: Impedance data collected for capacitor style devices of each electrode type, in the after exporting the relevant impedance, phase, and capacitance data from the raw collection file format. Naming convention is "Impedance_[electrode material]_ALL.csv" (Ex: "Impedance_Carbon_ALL.csv").</p><p><strong> ".dwf3work"</strong>: Raw Impedance data collected for capacitor style devices of each electrode type, in the original files as collected using Digilent Waveforms Software (open source). Data is split into two files based on the size of the capacitors being measured, (either 5 and 10 mm2 devices, or 20 and 30mm2 devices). The naming convention used is "Impedance_[Electrode Material]__[capacitor surface areas tested].dwf3work" (Ex: "Impedance_Zinc_5&10mm2.dwf3work").</p><p> </p><h4><strong>02 Berlincourt Data</strong></h4><p>This folder contains all the data associated with characterizing the piezoelectric properties of the devices in this manuscript. It includes 3 files, sorted by the electrode material of the devices under test, and reports the average d33,eff values (over 3 repetitions) measured for those devices based on the applied poling Voltage and field. The naming convention used is "BerlincourtData_[Electrode Material].csv" (Ex: "BerlincourtData_Carbon.csv").</p><p>-------------------------------------------------------------------------------------------------------------------------------</p><h3><strong>04 Force Sensor Demonstrator</strong></h3><p>This folder contains all the data associated with force sensor demonstrator reported on in the associated manuscript.</p><h4><strong>01 TouchGrid.svg</strong></h4><p>A vector file containing the whole-device design of the force sensor device used in this sensing demonstration. Each layer of the file is a layer of the device, and was used for the ordering and fabrication of associated screen printing meshes.</p><p> </p><h4><strong>02 VoltageMeasurement.vi</strong></h4><p>A LabView script file used for recording the output voltage of the piezoelectric devices as a function of time. To be used in combination with an Agilent 34410A or 34411A Multimeter. Outputs Voltage response as a function of time from the initiation of the recorded measurement.</p><p> </p><h4><strong>03 Single Force Data</strong></h4><p>This folder contains data associated with characterizing the force sensor demonstrators reported on in this manuscript. It includes 3 sub-folders, sorted by the electrode material of the devices under test. The naming convention used for the sub-folders is "SingleForce_[Electrode Material]" (Ex: "SingleForce_Zinc"). Within each sub-folder is a series of data files (.csv) detailing the test and data conditions. Each sample was compressed with a set force in a series of pulses. The naming convention used for the files in the sub-folders is "[Electrode Material]_[Max Applied Force]_[MeasuredData].csv" (Ex: "Gold_12.5N_MM.csv"), where the measured data is either "_F" or "_MM" for Force data or Multimeter data respectively.</p><p><strong>"_F.csv": </strong>The files include data recorded by the Instron Pull tester of the force applied to the sample as a function of time. This data is associated with the measured voltage in the paired "_MM.csv" file. </p><p><strong>"_MM.csv": </strong>The files include data recorded by a LabVIEW script in tandem with an Agilent multimeter of the voltage produced by the sample associated with the incident force in the paired "_F.csv" file. </p><p> </p><h4><strong>04 Stepped Force Data</strong></h4><p>This folder contains data associated with characterizing the force sensor demonstrators reported on in this manuscript. It includes 3 sub-folders, sorted by the electrode material of the devices under test. The naming convention used for the sub-folders is "SteppedMeasurements_[Electrode Material]" (Ex: "SteppedMeasurements_Gold"). Within each sub-folder is a series of data files (.csv) detailing the test and data conditions. Each sample was compressed with a series of pulses successively increasing in applied force. The naming convention used for the files in the sub-folders is "[Electrode MaterialSteppedSweep[#]_[MeasuredData].csv" (Ex: "Carbon_SteppedSweep1_F.csv"), where the measured data is either "_F" or "_MM" for Force data or Multimeter data respectively, and the # indicates the repetition number of that specific measurement. Other details are the same as those described above for the subfolder data of 03 Single Force Data.</p><p>-------------------------------------------------------------------------------------------------------------------------------</p><h3><strong>05 Speaker Demonstrator</strong></h3><p>This folder contains all the data associated with speaker demonstrator reported on in the associated manuscript.</p><h4><strong>01 Speaker Design</strong></h4><p><strong>01</strong> <strong>SpeakersBuzzers.svg </strong></p><p>A vector file containing the design of the components used to fabricate the piezoelectric buzzer for the speaker demonstrator. This includes a baseplate onto which the piezoelectric devices were adhered, two rings as standoffs, and two long traces used for the "contact wires". All components were lasercut from cardboard or cardstock components.</p><p><strong>02</strong> <strong>3D Design Files </strong></p><p>A folder containing the design files (.stl) for 3D printing of the headphone chassis, including the headband, ear cans, and baffles. All designs were provided open source by Shannon Ley (https://pinshape.com/items/36134-3d-printed-3d-printed-headphones).</p><p> </p><h4><strong>02 Speaker Data</strong></h4><p><strong>01</strong> <strong>RawAudioRecordings </strong></p><p>A folder containing the raw audio recordings used in speaker characterization, in the form of .aup3 files, directly from the recording software (Audacity). File naming convention is "[Electrode Material]_[Device Size used]_[Recording sampling rate]_RAW.aup3" (Ex: "Zinc_5x30mm2_44.1khz_RAW.aup3").</p><p><strong>02</strong> <strong>Exported Audio </strong></p><p>A folder containing the exported audio recordings used in speaker characterization after trimming to a consistent length of 15s, and exporting from the recording software (Audacity) in the form of .wav files. Each sub-folder has naming convention of "[Electrode Material]_[Device Size used]_[Recording sampling rate]_export" (Ex: "Zinc_5x30mm2_44.1khz_export"), and contains a number of files. Each file within these folders is labelled with the frequency at which the speaker was actuated for that recording data. These files were then imported into Origin, where an FFT was used to extract the amplitude of the recorded data at that specific actuating frequency.</p><p> </p><h4><strong>03 Speaker LDV</strong></h4><p>A folder containing the laser doppler vibrometry data collected for speakers with either Zinc or Carbon-electroded piezoelectric actuators. The data comes in two formats: as-produced from Digilent Waveforms (.dwf3work), or exported (.csv) files. The naming convention for the raw data is "[Electrode Material]_[Speaker active area]_LDV_Raw.dwf3work" (Ex: "Zinc_5x30mm2_LDV_Raw.dwf3work"). The naming convention for the exported data is "[Electrode Material]_[Speaker active area]_LDV_Export.csv" (Ex: "Zinc_5x30mm2_LDV_Export.csv").</p>
Underlying dataset for battery pack degradation - Understanding aging in parallel-connected lithium-ion batteries under thermal gradients
<p>This record constitutes the raw data underlying the paper "<i>Battery pack degradation - Understanding aging in parallel-connected lithium-ion batteries under thermal gradients</i>" (<a href="https://www.researchsquare.com/article/rs-2535223/v1">preprint link</a>)</p><p>The dataset contains all raw data, processed data and analysis codes used to generate figures in the publication. Abstract is as follows:</p><blockquote><p>Practical lithium-ion battery systems require parallelisation of tens to hundreds of cells, however understanding of how pack-level thermal gradients influence lifetime performance remains a research gap. Here we present an experimental study of surface cooled parallel-string battery packs (temperature range 20-45 °C), and identify two main operational modes; convergent degradation with homogeneous temperatures, and (the more detrimental) divergent degradation driven by thermal gradients. We attribute the divergent case to the, often overlooked, cathode impedance growth. This was negatively correlated with temperature and can cause positive feedback where the impedance of cells in parallel diverge over time; increasing heterogeneous current and state-of-charge distributions. These conclusions are supported by current distribution measurements, decoupled impedance measurements and degradation mode analysis. From this, mechanistic explanations are proposed, alongside a publicly available aging dataset, which highlights the critical role of capturing cathode degradation in parallel-connected batteries; a key insight for battery pack developers.</p></blockquote>
Data for "Host starvation and in hospite degradation of algal symbionts shape the heat stress response of the Cassiopea-Symbiodiniaceae symbiosis"
<p>Raw data associated with the publication "Host starvation and in hospite degradation of algal symbionts shape the heat stress response of the Cassiopea-Symbiodiniaceae symbiosis". Temperature profile, daily measurements, physiological measurements, elemental analysis, NanoSIMS data, and cell density data are included as individual tabs in the Excel file. </p>
The influence of corrosion processes on the degradation of concrete cover
<p>It is a dataset for the paper that analyzes the impact of the accelerated corrosion process of reinforcing steel on the type of destruction of the concrete cover. In this work, two methods were used to accelerate corrosion. In the first method, in order to initiate corrosion processes, chloride ions were injected into the concrete using the migration method. The moment of initiation of the corrosion process was monitored using an electrochemical method of measuring polarization resistance. In the next step, the corrosion process was accelerated in the electrolysis process. Changes on the sample surface were also monitored by using a camera with which photos were taken at certain intervals. In the second method, the corrosion process of the reinforcing bar was accelerated thanks to the use of the electrolysis process but the source of chloride ions was the electrolyte in the form of a 3% NaCl solution.</p>
InSAR measured permafrost degradation of palsa peatlands in northern Sweden Datasets
<p>Datasets used in the writing of "InSAR measured permafrost degradation of palsa peatlands in northern Sweden" published in The Cryosphere. </p> <p>The processed interferometric data and deformation maps are commercially sensitive and<br>may be made available upon reasonable request (by email) from the corresponding author.</p>
SDADDS-Guelma : A Multi-purpose Dataset for Synthetic Degraded Arabic Documents
<h1><strong>SDADDS-Guelma : A Multi-purpose Dataset for Synthetic Degraded Arabic Documents </strong></h1> <h2><strong>Description:</strong></h2> <p>This is a partial release of the SDADDS-Guelma dataset.</p> <p>SDADDS-Guelma (Synthetic Degraded Arabic Document DataSet of the University of Guelma) is a database of synthetic noisy or degraded Arabic document images. It was created by Dr. Abderrahmane Kefali and his team to support research on preprocessing, analysis, and recognition of degraded Arabic documents, where having a large set of images for training and testing is essential. This dataset is made publicly available to researchers in the field of document analysis and recognition, with the hope that it will be useful and contribute to their research endeavors.</p> <p>In this first release of the dataset, 84 handwritten images and 120 printed images have been used, along with 25 images of historical backgrounds, forming a total of 26316 synthetic images of degraded Arabic documents along with their corresponding ground-truth files.</p> <p>This release is separated into two parts to facilitate upload and use: one for the handwritten documents and the second for the printed documents.</p> <h2><strong>Composition of the dataset:</strong></h2> <p>Each of the parts of the SDADDS-Guelma dataset is organized into directories as follows:</p> <ul> <li>TXT_Files: Contains texts in UTF-8 format. </li> <li>IMG: Contains images of printed and handwritten Arabic text constructed from the text files. </li> <li>Bin_IMG: Contains binary images corresponding to the original images. </li> <li>BG_IMG: Contains images of empty old document backgrounds used for the generation of synthetic historical document images. </li> <li>GT_Files: Contains XML annotation files corresponding to the text images.</li> <li>Degraded_IMG: This directory contains synthetically generated degraded images, separated into sub-directories based on noise types such as Local_Noise, Show_through, Rotation, Curvature, Comb_IMG, etc.</li> </ul> <h2><strong>Ground-truth information:</strong></h2> <p>Ground truth information is essential for a document dataset, as it annotates documents and represents their essential characteristics. Our dataset is designed to be a large-scale and multipurpose dataset. As such, our methodology ensures that ground truth information is provided at three levels: text level (character codes), pixel level (binary and cleaned image), and document physical structure and other annotation information level.</p> <ul> <li>Textual Ground Truth: these are identical to the original texts. </li> <li>Pixel-level ground truth: presented in the form of binary images.</li> <li>Ground truth at the document structure level: the structure of each document image, alongside the textual transcription of the words and PAWs, is recorded in a corresponding XML annotation file. The XML format utilized resembles that employed in similar works with adjustments made according to the specific characteristics of Arabic texts, including the presence of PAWs. </li> </ul> <p>Consequently, each original text image in our dataset is associated to an XML file detailing the entire ground truth and associated metadata. </p> <h3><em><strong>Structure of XML file:</strong></em></h3> <p>Each XML annotation file contains metadata about the document image and text content within the image, including the language, number of lines, and font attributes. It also provides detailed information about each text line, word, and Part of Arabic Words (PAWs), including their bounding boxes and textual transcriptions.</p> <p>Thus, each ground truth file takes the following form:</p> <pre><code><DOCUMENT imageName="PR1Kufi_bin.png" height="2631" width="1860" nbTextLines="8" language="Arabic" fontName="Kufi" fontSize="34"> <TEXTLINE id="0" nbWords="3" boundingBox="215,481,355,1379"> <WORD id="0" nbPAWs="2" boundingBox="217,1065,341,1379" transcription="خصائص"> <PAW id="0" nbCCs="2" boundingBox="217,1206,322,1379" transcription="خصا"> <CC id="0" nbPixels="4110" pixels="(217,1206,1206);(218,1206,1207);(219,1206,1208);(220,1206,1208);(221,1206,1211);(222,1206,1211);..."> </CC> <CC id="1" nbPixels="80" pixels="(263,1330,1336);(264,1329,1336);(265,1328,1337);(266,1328,1337);(267,1328,1337);(268,1328,1337);(269,1328,1337);...."> </CC> </PAW> .... </WORD> <WORD id="1" nbPAWs="2" boundingBox="215,817,338,1044" transcription="التفسير"> <PAW id="0" nbCCs="1" boundingBox="215,1030,322,1044" transcription="ا"> <CC id="0" nbPixels="1037" pixels="(215,1030,1030);(216,1030,1030);(217,1030,1031);..."></CC> .... </PAW> .... </WORD> </TEXTLINE> .... </DOCUMENT></code></pre> <h1><strong>Contact:</strong></h1> <p>Name: Dr. Abderrahmane Kefali<br>Affiliation: University of 8 May 1945-Guelma, Algeria<br>Email: kefali.abderrahmane@univ-guelma.dz</p>
LC-MS/MS, PSM and BLG properties data from "Benchmarking the identification of a single degraded protein to explore optimal search strategies for ancient proteins"
<p>This dataset contains the data analyzed in:</p> <p>Rodriguez Palomo I, Nair B, Chang Y, Dartigues B, Dekker K, Mackie M, Evans M, Macleod R, Olsen JV, Collins MJ. (2023) "<em>Benchmarking the identification of a single degraded protein to explore optimal search strategies for ancient proteins"</em></p> <p>It contains the following data:</p> <ul> <li>raw_files.zip Thermo RAW files for the 0, 4 and 128 days samples</li> <li>benchmark_results.zip PSMs data from the analysis of the RAW files <ul> <li>Data from runs in Mascot, Fragpipe, pFind, Metamorpheus, MaxQuant and DeNovoGUI</li> <li>Parameters and workflow files for MaxQuant and Fragpipe</li> </ul> </li> <li>bovin_blg_prop.zip BLG properties files: amyloid formation, 3D structure and solvent accessibility</li> <li>benchmark_table.csv Table with runs settings for benchmarking</li> <li>parameters_table.xlsx Spreadsheet with software parameters, derived from files used to run each software</li> </ul> <p> </p>
Progressive degradation of acetylated wood by the brown rot fungi Coniophora puteana and Rhodonia placenta
<p>This dataset contains measurement data from the following publication: Belt, T.; Awais, M. (2025) Progressive degradation of acetylated wood by the brown rot fungi <em>Coniophora puteana</em> and <em>Rhodonia placenta</em>. Wood Science and Technology 59:13. https://doi.org/10.1007/s00226-024-01620-8. The experimental methods are described in brief below; further details can be found in the publication.</p> <p>Scots pine sapwood samples were acetylated in neat acetic anhydride to 9% or 18% weight percent gain (WPG) or left untreated to act as reference. The samples were exposed to brown rot decay in a stacked-sample decay test conducted in test tubes. Each replicate tube received 6 reference or acetylated samples stacked on top of each other (sample positions 1-6 from top to bottom) over nutrient agar inoculated with <em>Coniophora puteana</em> (N = 7) or <em>Rhodonia placenta</em> (N = 5). The different wood-fungus combinations were incubated for different durations until the visible fungal mycelium reached the top of the topmost block in one replicate tube. The samples were weighed before modification, after modification, at the end of the decay test, and after the decay test to determine their WPG, moisture content at the end of the decay test, and mass loss due to decay. After decay, 15 samples from every wood-fungus combination were selected for acetyl content measurement and FTIR spectroscopy.</p> <p>Acetyl contents were measured on powdered samples by saponification followed by HPLC quantification of the liberated acetic acid. FTIR spectra were measured in the 400-4000 cm<sup>-1</sup> spectral range in triplicate on powdered samples using an ATR accessory. For further analysis, the spectra were cut to 800-1800 cm<sup>-1</sup> range, baseline corrected (third degree polynomial subtraction), smoothed (Savitzky-Golay procedure with a second-order polynomial and a 15-point window), and normalised (unit vector normalisation).</p> <p>The "Mass data and acetyl content.csv" -file gives the sample identifiers (ID, sample type, test fungus, tube number, sample position) and measured mass data of all samples, and the acetyl contents of the selected samples. Masses m<sub>init</sub>, m<sub>mod</sub>, m<sub>wet</sub>, and m<sub>dec</sub> are the initial unmodified dry mass, the modified dry mass, the decaying wet mass, and the decayed dry mass, respectively. Acetyl contents (%) are given on a decayed wood basis.</p> <p>The “Unprocessed FTIR spectra_reference”, “Unprocessed FTIR spectra_9%”, and “Unprocessed FTIR spectra_18%” -files contain the unprocessed FTIR spectra of the reference, 9% WPG and 18% WPG samples (see the "Mass data and acetyl content.csv" -file for sample identifiers). The “Preprocessed FTIR spectra_reference”, “Preprocessed FTIR spectra_9%”, and “Preprocessed FTIR spectra_18%” -files in turn contain the preprocessed FTIR spectra of reference, 9% WPG and 18% WPG samples.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.