Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
66
datasets available to search
ShareScore release 0.7.1
Dataset results
66 results for “ECC”
Burke and Gambhir, 2022_ECC_DATASET
<p>This dataset contains the Marginal abatement cost curve data for different Greenhouse Gas Removal Options for the journal article Burke and Gambhir, 2022 published in Energy and Climate Change</p>
REASSURE (H2020 731591) ECC Dataset
<p>Datasets collection for ECC (C25519) side-channel traces, as part of REASSURE H2020 731591 project.</p> <p>The set “REASSURE_c25519_arithm_6k + PatternExtract From 5997 traces + StaticAlign.trs” contains electromagnetic traces coming from 5997 executions of Curve25519 $\mu$NaCl Montgomery Ladder scalar multiplication:<br> <a href="https://eur03.safelinks.protection.outlook.com/?url=http%3A%2F%2Fmunacl.cryptojedi.org%2Fcurve25519-cortexm0.shtml&data=02%7C01%7Cdavide.bellizia%40uclouvain.be%7C8c9e51578a42428bd87008d80c926b2f%7C7ab090d4fa2e4ecfbc7c4127b4d582ec%7C0%7C0%7C637273171350333478&sdata=m8uJEnfiU%2BAw7s%2Bt%2BKX%2Fgf8RcJM849UH2p2%2B%2FGHJtOs%3D&reserved=0">http://munacl.cryptojedi.org/curve25519-cortexm0.shtml</a><br> running on the Pi\~{n}ata target:<br> <a href="https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.riscure.com%2Fproduct%2Fpinata-training-target%2F&data=02%7C01%7Cdavide.bellizia%40uclouvain.be%7C8c9e51578a42428bd87008d80c926b2f%7C7ab090d4fa2e4ecfbc7c4127b4d582ec%7C0%7C0%7C637273171350333478&sdata=39fNqShJ8l5BoZ4HMtHLgviylORABJyq4Ri1wOQGpOI%3D&reserved=0">https://www.riscure.com/product/pinata-training-target/</a><br> which is a 32-bit STM32F4 microcontroller with an ARM-based architecture, running at the clock frequency of 168 MHz.<br> <br> The implementation employs arithmetic-based conditional swap and is additionally protected with projective coordinate re-randomization and scalar randomization.<br> Each trace from the dataset represent a single iteration of the Montgomery Ladder scalar multiplication that is cut from the whole execution trace; such trace is labeled with the corresponding cswap condition bit.<br> Observe that a full scalar can be trivially recovered from the cswap condition bits used in the 255 Montgomery Ladder iterations.<br> Furthermore, all these cut traces (5997*255=1529235) are aligned to exploit the leakage efficiently.<br> Details about the implementation and how the traces are aligned are in:<br> <a href="https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Feprint.iacr.org%2F2016%2F923.pdf&data=02%7C01%7Cdavide.bellizia%40uclouvain.be%7C8c9e51578a42428bd87008d80c926b2f%7C7ab090d4fa2e4ecfbc7c4127b4d582ec%7C0%7C0%7C637273171350343476&sdata=i3GZpv26FuYFwvOSxGjtXm2EU%2Be5xy5XCHEw%2BkrDuKE%3D&reserved=0">https://eprint.iacr.org/2016/923.pdf</a><br> <br> The set “REASSURE_c25519_arithm_6k + PatternExtract From 100 traces + StaticAlign.trs” contains a part of the 5997 set, but limited to the first 100 full traces.<br> <br> The set “REASSURE_c25519_arithm_6k_100 full traces.trs” contains the full 100 traces (before division).<br> <br> Each traces is in the TRS format that is described under the following links:<br> <a href="https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2FRiscure%2Fpython-trsfile&data=02%7C01%7Cdavide.bellizia%40uclouvain.be%7C8c9e51578a42428bd87008d80c926b2f%7C7ab090d4fa2e4ecfbc7c4127b4d582ec%7C0%7C0%7C637273171350343476&sdata=v78Tofs4%2BWvvSYhtqF7dW2uaU1nanllTXA5RyGshjWU%3D&reserved=0">https://github.com/Riscure/python-trsfile</a><br> <a href="https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2FRiscure%2Fjava-trsfile&data=02%7C01%7Cdavide.bellizia%40uclouvain.be%7C8c9e51578a42428bd87008d80c926b2f%7C7ab090d4fa2e4ecfbc7c4127b4d582ec%7C0%7C0%7C637273171350353467&sdata=Nw%2FAamSU1RQaoCeIC80786IKn4f%2BuOl7wfyjNk5R1C4%3D&reserved=0">https://github.com/Riscure/java-trsfile</a><br> <a href="https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2FRiscure%2FJlsca&data=02%7C01%7Cdavide.bellizia%40uclouvain.be%7C8c9e51578a42428bd87008d80c926b2f%7C7ab090d4fa2e4ecfbc7c4127b4d582ec%7C0%7C0%7C637273171350353467&sdata=sVPz0gh96ivEqMNxUNN4C36RV9ulAE%2BOu5DQ0w44Pic%3D&reserved=0">https://github.com/Riscure/Jlsca</a><br> <br> Moreover, note that each trs file include a short description inside the file itself.</p>
ECC Cómics Products
<p>Dataset de dades simulades per la Pràctica 1: Web Scraping, de l'assignatura Tipologia i Cicle de Vida de les Dades.</p> <p>Simulated dataset for Tipologia i Cicle de Vida de les Dades' Project 1: Web Scraping.</p> <p>Universitat Oberta de Catalunya</p>
Development of Novel Ultra-High Performance Engineered Cementitious Composites (UHP-ECC) for Durable and Resilient Transportation Infrastructure
<p>The objective of this study was to develop novel UHP-ECC materials utilizing readily available ingredients in Region 6 for the construction and repair of transportation infrastructure. Phase one of this study focused on the development of ultra-high strength cementitious matrices by evaluating the effects of ingredient selection and mixture proportioning on the materials’ compressive strength. Variables evaluated included the mass ratios of silica fume to fly ash (SF/FA), supplementary cementitious materials to cement (SCMs/C), and ordinary sand to microsilica sand (OS/MS). Phase two of the study focused on the development of UHP-ECC materials. To this end, based on the knowledge gained from phase one, two ultra-high strength cementitious matrices (one with and one without SF) were formulated and their fracture properties were evaluated through fracture toughness test. Furthermore, fiber-bridging properties of ultra-high-molecular-weight (UHMW) polyethylene (PE) fiber in the developed cementitious matrices were evaluated through single crack tensile test (SCTT). Four different composites were produced by reinforcing the selected cementitious matrices with 1.5 and 2 vol.% UHMW PE fiber. Fresh and hardened properties of the developed composites were assessed by means of flowability test, compressive strength test, uniaxial tensile test, and flexural performance test. Results from phase one showed that SF/FA had the most relevant effect on compressive strength, followed by SCMs/C, and OS/MS. Furthermore, increments in SF/FA produced improvements in strength, whereas increments in SCMs/C and OS/MS reduced strength. Experimental results from phase two indicated that the use of SF and the increase in fiber content generally had a negative effect on the fresh and hardened properties of the composites. These observations were credited to a worsening fiber distribution when using silica fume and/or increasing fiber content. Three UHP-ECC materials utilizing readily available ingredients were successfully developed (i.e., mixtures FA25-f1.5, FA25-f2, and FA20SF5-f2). These materials simultaneously exhibited ultra-high compressive strength (>120 MPa) and ECC-like ductility (tensile strain capacity >2%). The average crack width for all mixtures ranged between 61-131 μm. Mixture FA25-f1.5, which displayed the best mechanical properties, exhibited a compressive strength of 133.1 MPa, flexural strength of 21.4 MPa, tensile strength of 10.3 MPa, tensile strain capacity of 4.3%, and an average crack width of 115.3 μm. Importantly, this mixture did not incorporate silica fume or microsilica sand and used low fiber content (i.e., 1.5 vol.%).</p>
Resilient 3D-Printed Infrastructure with Engineered Cementitious Composites (ECC)
<p>Conventional construction of reinforced concrete structures is slow, labor-intensive, and expensive. 3D printing holds great potential to assist engineers and architects in constructing fast and economical yet complex representational infrastructures. One of the most significant barriers to the broader adoption of concrete 3D printing in civil infrastructure is the difficulty of providing printed structural components with reinforcement to achieve sound structural performance under different loading conditions. Hence, it is essential to design concrete that can be utilized as a rebar-free material by considering strength and ductility. Recently, the development of Engineered Cementitious Composites (ECC) has neared the possibility to achieve both strength and ductility in the concrete structures without embedding steel reinforcement. ECC has been offered to enhance the problem related to the ductility and low tensile strength of traditional concrete and Fiber Reinforced Composite (FRC). As such, the implementation of intrinsically reinforced cementitious materials has the potential to address this barrier in the reinforcement of 3D-printed concrete and yields significant benefits such as an enhanced structural capacity, durability, and resiliency. This project proposes the development of ECC materials utilizing readily available ingredients in Region 6 with rheological characteristics tailored specifically for 3D printing applications. Furthermore, the project aims to conduct a comprehensive evaluation of the hardened properties of 3D-printed ECC specimens, including mechanical tests.</p>
Evaluation of the Performance and Cost-Effectiveness of Engineered Cementitious Composites (ECC) Produced from Region 6 Local Materials
<p>Corresponding data set for Tran-SET Project No. 17CLSU05. Abstract of the final report is stated below for reference:</p> <p>"The project objective is to develop cost-effective Engineered Cementitious Composites (ECC) with locally available ingredients in Region 6 to address the deficiencies observed in ordinary concrete materials. The study explored the utilization of two types of river sands (coarse and fine), two types of PVA fibers (long and short), four levels of cement replacement with Class F fly ash, and the implementation of recycled crumb rubber in the performance of ECC materials. A total of 24 mix designs were prepared and evaluated in compression, tension, and bending to assess its mechanical properties. Furthermore, the cracking characteristics of the materials produced were evaluated to assess the durability potential of these composites. Lastly, the cost of each mix design and the feasibility of ECC implementation in transportation infrastructure were assessed. The experimental results showed that implementing crumb rubber and/or increasing contents of fly ash in the mixtures produced a positive impact in the ductility of the materials. However, a tradeoff between ductility and strength was observed. Furthermore, the utilization of the different types of sand evaluated in this study produced minor effects in the mechanical properties of ECCs evaluated. The properties of the materials developed in this study were exceedingly superior than that of regular concrete. It was concluded that ECC materials are promising for the future of transportation infrastructure."</p>
Evaluation of Fresh and Hardened Properties of 3D-Printed Engineered Cementitious Composites (ECC) Designed for Sustainable and Resilient Infrastructure Systems
<p>3D concrete printing is a cutting-edge construction technique that has the potential to revolutionize the construction industry due to cost-saving in terms of labor and formwork costs, efficiency in construction, lower safety-related risks, and a higher degree of automation. However, several issues still make its adoption relatively slower on a large scale. Engineered cementitious composites (ECC), a class of ultra-high-strength concrete, can be a potential solution to some problems, such as reinforcement and durability. The preliminary phase of a Tran SET project focused on the design of 3D printable ECC, considering the concrete mix design proportions and their potential effects on fresh and hardened properties to achieve an optimized printable ECC mix. The type and content of various concrete ingredients such as cement, admixtures, aggregates, and fibers have considerable influence on the several properties in the fresh and hardened state. The replacement levels for cement were 0%, 50%, and 75% for mineral admixture, 10% for silica fume, and 0.4% for nano-clay by cement mass. Locally available fine aggregates were also used at 25% and 40% by mass of binder. In addition, the influence of fiber types and contents was also investigated. Two types of fibers, polyethylene (PE) and polyvinyl alcohol (PVA) fibers, were used at different levels, such as 0%, 1%, 1.5%, and 2% of the total volume of the mix. Moreover, four mixes, including FA50-MC, FA40SF10-MC, S50-MC, and FA40MK10-MC, were evaluated in terms of mechanical performance (flexural strength and direct tensile strength). The flowability of the ECC mixes was reduced with the incorporation of slag, metakaolin, higher aggregate content, and PE fibers. The 2% of both PVA and PE fibers had a reduction in compressive strength as compared to the low fiber content. Moreover, the PE-ECC exhibited superior tensile ductility as compared to the PVA-ECC due to the more fiber bridging by the PE fibers at the crack interface.</p>
ECC-LIPID17 POPC-POPG 50:50 MD simulation, Na+ counterions and 100mM CaCl2, 298K
<p>Simulation data and parameters of ECC-LIPID17 simulation of POPC:POPG 50:50 mixture with Na+ counterions and 100mM CaCl2 at 298K, ran for NMRlipidsIVb:</p> <p>https://github.com/NMRLipids/NMRlipidsIVPEandPG/blob/master/Manuscript/manuscriptPGPE.pdf</p> <p>ECC-ion parameters are from bitbucket.org/hseara/ions/src/master/</p>
ECC-LIPID17 POPC-POPG 50:50 MD simulation, Na+ counterions, 298K
<p>Simulation data and parameters of ECC-LIPID17 simulation of POPC:POPG 50:50 mixture with Na+ counterions at 298K, ran for NMRlipidsIVb:</p> <p>https://github.com/NMRLipids/NMRlipidsIVPEandPG/blob/master/Manuscript/manuscriptPGPE.pdf</p> <p>ECC-ion parameters are from bitbucket.org/hseara/ions/src/master/</p>
ECC-LIPID17 POPC-POPG 50:50 MD simulation, Na+ counterions and 1000mM CaCl2, 298K
<p>Simulation data and parameters of ECC-LIPID17 simulation of POPC:POPG 50:50 mixture with Na+ counterions and 1000mM CaCl2 at 298K, ran for NMRlipidsIVb:</p> <p>https://github.com/NMRLipids/NMRlipidsIVPEandPG/blob/master/Manuscript/manuscriptPGPE.pdf</p> <p>ECC-ion parameters are from bitbucket.org/hseara/ions/src/master/</p>
Simulations of the air-water interface at the presence of salt, ECC ions + SPCE water model
<p>Simulations of a water–air interface. There are ~20000 water molecules with various concentrations of NaCl or CaCl_2 in a simulation box of 12*12*22 nm^3. The SPCE water and the ions with scaled charges based on the electronic continuum correction (ECC) are used. The numbering in file names corresponds to the different concentrations, and data for a pure water–air interface "NOION" is also provided. GROMACS-compatible inputs are provided: simulation parameters (md.mdp), topologies (top), and index (ndx) files. Initial structure can be extracted from the tpr file using gmx editconf. The run input (tpr) is provided, as are the outputs: energy file (edr), trajectory (xtc), and final structure (gro). Surface tensions can be extracted by gmx energy.</p> <p>These values are reported in DOI: [ADD].</p> <p>Data for these ECC ions with OPC water is provided at DOI: 10.5281/zenodo.3888369 and for the full charge ions by Dang et al. in SPCE water at DOI: 10.5281/zenodo.3888436.</p>
POPC @ 310K, 450 mM of CaCl_2. Charmm36 with ECC-scaled ions
<p>Simulations of a POPC bilayer with 450 mM of CaCl_2. <br> The goal was to study the effect of salt on the order <br> parameters of the lipid head group and the glycerol <br> backbone for the NMRlipids project, see <br> http://nmrlipids.blogspot.fi for more information.</p> <p>A POPC bilayer consisting of 200 lipids (100 per leaflet) <br> is simulated in the presence of 450 mM CaCl_2. The Charmm36 <br> model is employed for lipids, the Charmm compatible variant <br> of the tip3p model for water, and the recent ion parameters <br> by Kohagen et al. [2] for CaCl_2.</p> <p>The Charmm36 force field parameters were obtained from<br> CHARMM-GUI [3] at http://www.charmm-gui.org</p> <p>The ion parameters are available at<br> https://bitbucket.org/hseara/ions/</p> <p>––––––––––––––––––––––––––––––––––––––––––––––––––––––</p> <p>The files are in GROMACS format. Trajectory (.xtc) is <br> 100 ns long with data saved every 100 ps. These data<br> were collected once the adsorption and desorption of <br> CaCl_2 to the surface has reached equilibrium, namely<br> after 700 ns of simulation. Additionally, the initial <br> structure (.gro), topology (.top), index file (.ndx), <br> simulation paremeter file (.mdp), binary run input file <br> for GROMACS v. 5.0–> (.tpr) and the energy output file <br> (.edr) are provided. </p> <p>––––––––––––––––––––––––––––––––––––––––––––––––––––––</p> <p>[1] Update of the CHARMM All-Atom Additive Force Field <br> for Lipids: Validation on Six Lipid Types<br> Jeffery B. Klauda, Richard M. Venable, J. Alfredo Freites, <br> Joseph W. O’Connor, Douglas J. Tobias, Carlos Mondragon-Ramirez, <br> Igor Vorobyov, Alexander D. MacKerell, Jr., and Richard W. Pastor<br> The Journal of Physical Chemistry B 2010 114 (23), 7830-7843<br> DOI: 10.1021/jp101759q</p> <p>[2] Accurate Description of Calcium Solvation in Concentrated Aqueous Solutions<br> Miriam Kohagen, Philip E. Mason, and Pavel Jungwirth<br> The Journal of Physical Chemistry B 2014 118 (28), 7902-7909<br> DOI: 10.1021/jp5005693</p> <p>[3] CHARMM-GUI Input Generator for NAMD, GROMACS, AMBER, OpenMM, <br> and CHARMM/OpenMM Simulations Using the CHARMM36 Additive Force Field<br> Jumin Lee, Xi Cheng, Jason M. Swails, Min Sun Yeom, Peter K. Eastman, <br> Justin A. Lemkul, Shuai Wei, Joshua Buckner, Jong Cheol Jeong, Yifei Qi, <br> Sunhwan Jo, Vijay S. Pande, David A. Case, Charles L. Brooks, III, <br> Alexander D. MacKerell, Jr., Jeffery B. Klauda, and Wonpil Im<br> Journal of Chemical Theory and Computation 2016 12 (1), 405-413<br> DOI: 10.1021/acs.jctc.5b00935</p>
POPC @ 310K, 450 mM of CaCl_2. Slipids with ECC-scaled ions
<p>Simulations of a POPC bilayer with 450 mM of CaCl_2. <br> The goal was to study the effect of salt on the order <br> parameters of the lipid head group and the glycerol <br> backbone for the NMRlipids project, see <br> http://nmrlipids.blogspot.fi for more information.</p> <p>A POPC bilayer consisting of 200 lipids (100 per leaflet) <br> is simulated in the presence of 450 mM CaCl_2. The Slipids <br> model [1–3] is employed for lipids, tip3p model for water, <br> and the recent ion parameters by Kohagen et al. [4] for <br> CaCl_2.</p> <p>The Slipids force field parameters were downloaded from<br> http://mmkluster.fos.su.se/slipids/</p> <p>The ion parameters are available at<br> https://bitbucket.org/hseara/ions/</p> <p>––––––––––––––––––––––––––––––––––––––––––––––––––––––</p> <p>The files are in GROMACS format. Trajectory (.xtc) is <br> 100 ns long with data saved every 100 ps. These data<br> were collected once the adsorption and desorption of <br> CaCl_2 to the surface has reached equilibrium, namely<br> after 500 ns of simulation. Additionally, the initial <br> structure (.gro), topology (.top), index file (.ndx), <br> simulation paremeter file (.mdp), binary run input file <br> for GROMACS v. 4.6–> (.tpr) and the energy output file <br> (.edr) are provided. </p> <p>––––––––––––––––––––––––––––––––––––––––––––––––––––––</p> <p>[1] Derivation and Systematic Validation of a Refined <br> All-Atom Force Field for Phosphatidylcholine Lipids<br> Joakim P. M. Jämbeck and Alexander P. Lyubartsev<br> The Journal of Physical Chemistry B 2012 116 (10), 3164-3179<br> DOI: 10.1021/jp212503e</p> <p>[2] An Extension and Further Validation of an All-Atomistic <br> Force Field for Biological Membranes<br> Joakim P. M. Jämbeck and Alexander P. Lyubartsev<br> Journal of Chemical Theory and Computation 2012 8 (8), 2938-2948<br> DOI: 10.1021/ct300342n</p> <p>[3] Another Piece of the Membrane Puzzle: Extending Slipids Further<br> Joakim P. M. Jämbeck and Alexander P. Lyubartsev<br> Journal of Chemical Theory and Computation 2013 9 (1), 774-784<br> DOI: 10.1021/ct300777p</p> <p>[4] Accurate Description of Calcium Solvation in Concentrated Aqueous Solutions<br> Miriam Kohagen, Philip E. Mason, and Pavel Jungwirth<br> The Journal of Physical Chemistry B 2014 118 (28), 7902-7909<br> DOI: 10.1021/jp5005693</p>
POPC with varying amounts of cholesterol, 450 mM of CaCl_2. Charmm36 with ECC-scaled ions
<p>Simulations of a POPC bilayer with varying amounts (0, 10, 20, and 30 mol-%) of cholesterol and 450 mM of CaCl_2 performed at 310 K. The POPC bilayer consists of 200 lipids (100 per leaflet) and on top of that there is 0 (0%), 22 (10%), 50 (20%), or 86 (30%) of cholesterol. The Charmm36 model [1,2] is employed for lipids, the Charmm compatible variant of the tip3p model for water, and the recent ion parameters by Kohagen et al. [3] for CaCl_2.</p> <p>The Charmm36 force field parameters were obtained Charmm-GUI [4], and the ion parameters are available at https://bitbucket.org/hseara/ions/ . IMPORTANT: The simulations are performed with version 1.7 obtained from Charmm-GUI, and this version is known to have an issue with the multiplicity of dihedrals in Gromacs output files, see http://www.charmm-gui.org/?doc=log . <br> ––––––––––––––––––––––––––––––––––––––––––––––––––––––<br> The files are in GROMACS format and named based on the amount of cholesterol present (in %) in the corresponding simulation. Trajectories (.xtc) are 800 ns long with data saved every 100 ps. Additionally, the final structure (.gro), topology (.top), index file (.ndx), energy output file (.edr), and binary run input files (for Gromacs 5.0->) (.tpr) are provided for each system. The common simulation parameter file (.mdp) is also provided.<br> ––––––––––––––––––––––––––––––––––––––––––––––––––––––<br> [1] Update of the CHARMM All-Atom Additive Force Field for Lipids: Validation on Six Lipid Types. Jeffery B. Klauda, Richard M. Venable, J. Alfredo Freites, Joseph W. O’Connor, Douglas J. Tobias, Carlos Mondragon-Ramirez, Igor Vorobyov, Alexander D. MacKerell, Jr., and Richard W. Pastor, The Journal of Physical Chemistry B 2010 114 (23), 7830–7843, DOI: 10.1021/jp101759q</p> <p>[2] Update of the Cholesterol Force Field Parameters in CHARMM. Joseph B. Lim, Brent Rogaski, and Jeffery B. Klauda, The Journal of Physical Chemistry B 2012 116 (1), 203–210, DOI: 10.1021/jp207925m</p> <p>[3] Accurate Description of Calcium Solvation in Concentrated Aqueous Solutions. Miriam Kohagen, Philip E. Mason, and Pavel Jungwirth, The Journal of Physical Chemistry B 2014 118 (28), 7902-7909, DOI: 10.1021/jp5005693</p> <p>[4] CHARMM-GUI Input Generator for NAMD, GROMACS, AMBER, OpenMM, and CHARMM/OpenMM Simulations Using the CHARMM36 Additive Force Field. Jumin Lee, Xi Cheng, Jason M. Swails, Min Sun Yeom, Peter K. Eastman, Justin A. Lemkul, Shuai Wei, Joshua Buckner, Jong Cheol Jeong, Yifei Qi, Sunhwan Jo, Vijay S. Pande, David A. Case, Charles L. Brooks, III, <br> Alexander D. MacKerell, Jr., Jeffery B. Klauda, and Wonpil Im, Journal of Chemical Theory and Computation 2016 12 (1), 405-413, DOI: 10.1021/acs.jctc.5b00935</p>
POPC with varying amounts of cholesterol, 450 mM of CaCl_2. Slipids with ECC-scaled ions
<p>Simulations of a POPC bilayer with varying amounts (0, 10, 20, and 30 mol-%) of cholesterol and 450 mM of CaCl_2 performed at 310 K. The POPC bilayer consists of 200 lipids (100 per leaflet) and on top of that there is 0 (0%), 22 (10%), 50 (20%), or 86 (30%) of cholesterol. Additionally, simulations with 0% cholesterol are repeated at 330 K, 350 K, and 370 K. The Slipids model [1–3] is employed for lipids, tip3p model for water, and the recent ion parameters by Kohagen et al. [4] for CaCl_2. The Slipids force field parameters are available at http://www.fos.su.se/~sasha/SLipids/ and the ion parameters are available at https://bitbucket.org/hseara/ions/<br> ––––––––––––––––––––––––––––––––––––––––––––––––––––––<br> The files are in GROMACS format and named based on the amount of cholesterol present (in %) in the corresponding simulation. Trajectories (.xtc) are 600 ns long (800 ns long for systems at elevated temperatures) with data saved every 100 ps. Additionally, the final structure (.gro), topology (.top), index file (.ndx), energy output file (.edr), and binary run input files (for Gromacs 4.6->) (.tpr) are provided for each system. The common simulation parameter file (.mdp) is also provided.<br> ––––––––––––––––––––––––––––––––––––––––––––––––––––––<br> [1] Derivation and Systematic Validation of a Refined All-Atom Force Field for Phosphatidylcholine Lipids. Joakim P. M. Jämbeck and Alexander P. Lyubartsev, The Journal of Physical Chemistry B 2012 116 (10), 3164-3179, DOI: 10.1021/jp212503e</p> <p>[2] An Extension and Further Validation of an All-Atomistic Force Field for Biological Membranes. Joakim P. M. Jämbeck and Alexander P. Lyubartsev, Journal of Chemical Theory and Computation 2012 8 (8), 2938-2948, DOI: 10.1021/ct300342n</p> <p>[3] Another Piece of the Membrane Puzzle: Extending Slipids Further. Joakim P. M. Jämbeck and Alexander P. Lyubartsev, Journal of Chemical Theory and Computation 2013 9 (1), 774-784, DOI: 10.1021/ct300777p</p> <p>[4] Accurate Description of Calcium Solvation in Concentrated Aqueous Solutions. Miriam Kohagen, Philip E. Mason, and Pavel Jungwirth, The Journal of Physical Chemistry B 2014 118 (28), 7902-7909, DOI: 10.1021/jp5005693</p>
POPC with varying amounts of cholesterol, 130 mM of NaCl. Slipids with ECC-scaled ions
<p>Simulations of a POPC bilayer with varying amounts (0, 10, 20, and 30 mol-%) of cholesterol and 130 mM of NaCl performed at 310 K. The POPC bilayer consists of 200 lipids (100 per leaflet) and on top of that there is 0 (0%), 22 (10%), 50 (20%), or 86 (30%) of cholesterol. The Slipids model [1–3] is employed for lipids, tip3p model for water, and the and the recent ion parameters by Kohagen et al. [4] for NaCl. The Slipids force field parameters are available at http://www.fos.su.se/~sasha/SLipids/ and the ion parameters are available at https://bitbucket.org/hseara/ions/<br> ––––––––––––––––––––––––––––––––––––––––––––––––––––––<br> The files are in GROMACS format and named based on the amount of cholesterol present (in %) in the corresponding simulation. Trajectories (.xtc) are 200 ns long with data saved every 100 ps. Additionally, the final structure (.gro), topology (.top), index file (.ndx), energy output file (.edr), and binary run input files (for Gromacs 4.6->) (.tpr) are provided for each system. The common simulation parameter file (.mdp) is also provided.<br> ––––––––––––––––––––––––––––––––––––––––––––––––––––––<br> [1] Derivation and Systematic Validation of a Refined All-Atom Force Field for Phosphatidylcholine Lipids. Joakim P. M. Jämbeck and Alexander P. Lyubartsev, The Journal of Physical Chemistry B 2012 116 (10), 3164-3179, DOI: 10.1021/jp212503e</p> <p>[2] An Extension and Further Validation of an All-Atomistic Force Field for Biological Membranes. Joakim P. M. Jämbeck and Alexander P. Lyubartsev, Journal of Chemical Theory and Computation 2012 8 (8), 2938-2948, DOI: 10.1021/ct300342n</p> <p>[3] Another Piece of the Membrane Puzzle: Extending Slipids Further. Joakim P. M. Jämbeck and Alexander P. Lyubartsev, Journal of Chemical Theory and Computation 2013 9 (1), 774-784, DOI: 10.1021/ct300777p</p> <p>[4] Accounting for Electronic Polarization Effects in Aqueous Sodium Chloride via Molecular Dynamics Aided by Neutron Scattering. Miriam Kohagen, Philip E. Mason, and Pavel Jungwirth, The Journal of Physical Chemistry B 2016 120 (8), 1454–1460, DOI: 10.1021/acs.jpcb.5b05221</p> <p> </p>
TPP binding to POPC membrane, CHARMM36-ProteinFF-ECC, 277 mM, 298 K
<p>System info in README.yaml, including basic analysis - headgroup OP, averaged APL and repead distance, analysis performed only from eqilibrated part of the simulation, marked as "BINDINGEQ"</p> <p>here:</p> <p>FILES:<br> xtc:<br> NAME: [name]<br> SIZE: [MB]<br> MODIFIED: [yyyy-mm-dd time]<br> LENGTH: [ps]<br> SAVING_FREQUENCY: [ps]<br> BEGIN: [ps] - how much of the simulation was simulated before and is excluded</p>
TPP binding to POPC membrane, CHARMM36-ProteinFF-ECC, 416 mM, 298 K
<p>System info in README.yaml, including basic analysis - headgroup OP, averaged APL and repead distance, analysis performed only from eqilibrated part of the simulation, marked as "BINDINGEQ"</p> <p>here:</p> <p>FILES:<br> xtc:<br> NAME: [name]<br> SIZE: [MB]<br> MODIFIED: [yyyy-mm-dd time]<br> LENGTH: [ps]<br> SAVING_FREQUENCY: [ps]<br> BEGIN: [ps] - how much of the simulation was simulated before and is excluded</p>
TPP binding to POPC membrane, CHARMM36-QMcharges-Literature-ECC, 277 mM, 298 K
<p>System info in README.yaml, including basic analysis - headgroup OP, averaged APL and repead distance, analysis performed only from eqilibrated part of the simulation, marked as "BINDINGEQ"</p> <p>here:</p> <p>FILES:<br> xtc:<br> NAME: [name]<br> SIZE: [MB]<br> MODIFIED: [yyyy-mm-dd time]<br> LENGTH: [ps]<br> SAVING_FREQUENCY: [ps]<br> BEGIN: [ps] - how much of the simulation was simulated before and is excluded</p>
TPP binding to POPC membrane, CHARMM36-QMcharges-Literature-ECC, 138 mM, 298 K
<p>System info in README.yaml, including basic analysis - headgroup OP, averaged APL and repead distance, analysis performed only from eqilibrated part of the simulation, marked as "BINDINGEQ"</p> <p>here:</p> <p>FILES:<br> xtc:<br> NAME: [name]<br> SIZE: [MB]<br> MODIFIED: [yyyy-mm-dd time]<br> LENGTH: [ps]<br> SAVING_FREQUENCY: [ps]<br> BEGIN: [ps] - how much of the simulation was simulated before and is excluded</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.