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360 results for “cement”
Dataset: Environmental benchmarks for European Cement Industry
<p>This dataset contains the information relative to the article "Environemntal benchmarks for European cement industry".</p> <p><a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.spc.2024.01.020" target="_blank" rel="noopener">Reference paper</a></p> <p><a href="https://www.researchgate.net/publication/377796848_Environmental_benchmarks_for_the_European_cement_industry" target="_blank" rel="noopener">ResearchGate link</a></p>
Damage Localisation in Fresh Cement Mortar Observed via In Situ (Timelapse) X-ray uCT imaging.
<p>This is dataset to paper: Damage Localisation in Fresh Cement Mortar Observed via In Situ (Timelapse) X-ray uCT imaging.</p>
Nano-sized calcium carbonate particles in cement mortars (DS18)
<p>This dataset will provide the selection of the optimal mix-design of cement mortars, optimizing the characteristics of nanoCaCO3 particles (additional percentages, morphology, particle size distribution, crystal phase) according to their use in cement-based composites. These commercial nanoparticles have characteristics comparable with those of the synthesized particles used up to now in the RECODE project.</p>
Data for: Deriving early hydration cement paste phase assemblage, microstructure development and elastic properties using thermodynamic simulation and multi-scale material modeling
<h2>Description</h2> <p>DATA REPOSITORY FOR</p> <p>Title: Deriving early hydration cement paste phase assemblage, microstructure development and elastic properties using thermodynamic simulation and <br> multi-scale material modeling<br>By: Eva Jägle, Jithender J. Timothy, Daniel Jansen, Alisa Machner<br>Accepted by: Cement and Concrete Research</p> <p>This dataset presents the data of the paper 'Deriving early hydration cement paste phase assemblage, microstructure development and elastic properties using thermodynamic simulation and multi-scale material modeling' submitted to and accepted by Cement and Concrete Research. The dataset follows the structure of the paper such that the calculations described therein can be reproduced.</p> <p>Data is available on three types of cement: Two ordinary Portland cements of different grinding fineness (CEM I 42.5 R und CEM I 52.5 R) and one limestone-containing blended cement (CEM II/A-LL 42.5 R). The data refer to the first 24 hours of hydration and temperature conditions of 20°C (for CEM I 42.5 R, CEM I 52.5 R, CEM II/A-LL 42.5 R) and 35°C (for CEM I 52.5 R). All data were retrieved for cement pastes with a water-to-cement ratio of 0.45.</p> <p>The dataset contains raw and processed data from quantitative X-ray diffraction, 5PL cement dissolution fitting, thermodynamic simulation with GEMS, multi-scale material modeling, ultrasonic testing and Vicat penetration tests. The data is mainly available in .xlsx files together with short descriptions in ReadMe.txt files.</p>
Dataset of optimal cement-based panels enhanced with microencapsulated phase change material for EnergyPlus simulations
<p>This dataset includes:<br> - A series of EnergyPlus models of the BESTEST - Case 900 - from ANSI/ASHRAE Standard 140-2011 for the original (Baseline_Case900) and three enhanced designs (Opt-1, Opt-2, Opt-5) by using a cement-based panel containing microencapsulated phase change material.<br> - All the optimal solutions (parameters and corresponding performance) in XLSX format, which were obtained for two multiobjective optimization studies of the thermophysical properties (ParetoFront_CaseA and ParetoFront_CaseB).<br> - The typical meteorological year (TMY) of Sofia city employed to obtain the results, which is freely provided by Climate.One.Building.Org repository (https://climate.onebuilding.org/)</p>
Animation to visualize the effects of laser ablation on unhydrated cement clinker
<p>This animation illustrates the effect of the damage on the surface of unhydrated cement clinker caused by a pulsed laser for a LA-ICP-MS mapping. The dataset contains the raw data and the final animations.</p> <p>The images were acquired using a Thermofischer Scientific Helios G4 UX microscope at 2 kV/0.1 nA. The surface was tilted in two orientations by a few degree and an image was acquired after every tilt. The ablated area has a size of approx. 367 x 300 µm.</p> <p>A detailed description of the specimen and the parameters used for the analysis can be found in the <a href="https://doi.org/10.1016/j.cemconres.2022.106875">corresponding paper</a>.</p> <p><strong>Funding</strong></p> <p>The research was supported by the Deutsche Forschungsgemeinschaft (DFG), grant number <a href="https://gepris.dfg.de/gepris/projekt/344069666">344069666</a>.</p>
Industry - Chemical & Pharma., Cement, Motor systems, Excess heat recovery systems
<ul> <li>This file provides techno-economic data for energy efficiency measures applicable in Swiss industrial systems.</li> <li>Generalized indicators for measure-specific potential energy savings are not developed (except for cement industry) due to the unavailability of physical production data, ex-ante and ex-post data of the implemented measures and detailed statistics on energy use by application in Swiss industry.</li> <li>When using the data please consult and refer to the publications given in the Reference section.</li> </ul>
Data set for "Quantification of amorphous siliceous fly ash in hydrating blended cement pastes by X-ray powder diffraction"
<p>The main data is XRD patterns originally collected as xrdml and converted into rd format.</p> <p>The data set for the manuscript:</p> <p>Quantification of amorphous siliceous fly ash in hydrating blended cement pastes by X-ray powder diffraction</p> <p>Xuerun Li<sup>a</sup>, Ruben Snellings<sup>b</sup> and Karen L. Scrivener<sup>a</sup></p> <p><sup>a</sup>Laboratory of Construction Materials, Swiss Federal Institute of Technology in Lausanne (EPFL), Station 12, CH-1015 Lausanne, Switzerland</p> <p><sup>b</sup>Sustainable Materials Management, Flemish Institute of Technological Research (VITO), Boeretang 200, 2400 Mol, Belgium<br> </p>
Global CO2 emissions from cement production
<p><strong>GCP-CEM: The Global Carbon Project CEMent-process emissions dataset</strong></p> <p>This is an update of the dataset documented in:</p> <blockquote> <p>Andrew, R.M., 2019. Global CO2 emissions from cement production, 1928–2018. Earth System Science Data 11, 1675–1710. <a href="https://doi.org/10.5194/essd-11-1675-2019">https://doi.org/10.5194/essd-11-1675-2019</a>.</p> </blockquote> <p>Data in this release cover the period 1880–2024.</p> <p>Note that emissions from use of fossil fuels in cement production are not included in this dataset since they are usually included elsewhere in global datasets of fossil CO2 emissions. The process emissions in this dataset, which result from the decomposition of carbonates in the production of cement clinker, amounted to ~1.5 Gt CO2 in 2024 while emissions from combustion of fossil fuels to produce the heat required amounted to an additional ~0.9 Gt CO2 in 2024.</p> <p><strong>October 2025 release (251007): Changes</strong></p> <ul> <li>The 2025 editions of Annex 1 parties' reports to the UNFCCC have been included, as well as any Biennial Transparency Reports submitted by non-Annec 1 parties since the last update in February</li> <li>Various revisions to recent years' estimates based on newly published data</li> <li>New activity data sources for Egypt, Indonesia, Iran, Sri Lanka</li> <li>US emissions 1880-1924 are restored</li> </ul> <p><strong>The Cement Production dataset</strong></p> <p>Annual cement production data by country are assembled from a number of sources. Prioritisation is given to national sources, whether directly from statistical offices or activity data reported in official emissions reports submitted to the UNFCCC. Where official sources are not used, data are sourced from the USGS Minerals Yearbooks. Some data points in the USGS dataset are corrected based on either sense-checks or information from alternative sources. For data before 1990, USGS data are obtained via back-calculation from the 2019 edition of the CDIAC emissions dataset. The first year for most countries in the USGS data is 1928; where the combined dataset shows zeros before 1928 and non-zero data from 1928, these zeros are assumed to be artefacts and are set to NODATA. Using available data for some former Soviet states before the dissolution of the Soviet Union, Soviet states are disaggregated for all years before dissolution. Every data point in the cement production dataset has its source indicated in the accompanying source file. Blank cells should be interpreted as NODATA.</p> <p><strong>The Clinker Production dataset</strong></p> <p>Annual clinker production data by country are assembled from a number of sources. No such multi-country dataset exists elsewhere to our knowledge. Many countries report 'activity data' in their emissions reporting to the UNFCCC, and for the Cement Production sector (2.A.1), this is often clinker production. For all Annex 1 countries this is the case, and clinker production for these countries are obtained from their Excel-format reporting files (CRTs), although New Zealand (and Hungary in recent years) exceptionally has withheld these data for reasons of confidentiality. The new BTRs for non-Annex 1 countries also include CRTs, and these have been used where available. Many other countries report time-series of clinker production in their official emissions reporting, and for some countries data are available (sometimes with monthly frequency) from official websites. Every data point in the clinker production dataset has its source indicated in the accompanying source file. Blank cells should be interpreted as NODATA. Not all countries are present in the dataset.</p> <p><strong>Emissions calculation</strong></p> <ul> <li>Emissions for all UNFCCC Annex I ("developed") countries are taken directly from their official submissions to the UNFCCC (or EIONET) in Common Reporting Format (structured Excel files), for which data are available from 1990 (slightly earlier for some Economies in Transition). <ul> <li>Australia, Austria, Belgium, Bulgaria, Belarus, Canada, Switzerland, Cyprus, Czechia, Germany, Denmark, Spain, Estonia, Finland, France, United Kingdom, Greece, Croatia, Hungary, Ireland, Iceland, Italy, Japan, Kazakhstan, Liechtenstein, Lithuania, Luxembourg, Latvia, Malta, Netherlands, Norway, New Zealand, Poland, Portugal, Romania, Russia, Slovakia, Slovenia, Sweden, Turkey, Ukraine, United States of America.</li> </ul> </li> <li>Country-specific methods are used for Brazil, India, South Africa, Thailand, USA, Vietnam. <ul> <li>For Brazil, emissions are published from 1990, and clinker ratios are reported starting in 1970, allowing more accurate estimation before 1990.</li> <li>Little information is available about clinker production in India since the Cement Manufacturers' Association was forced to stop collecting these data. Various sources are used to estimate how the clinker ratio has changed over time in India.</li> <li>South Africa's reported emissions appear to be calculated assuming limestone sales statistics are cement production statistics. An alternative method is used here.</li> <li>For Thailand, cement production and clinker trade data are available from 1990, and these are used to estimate clinker production in the period 1990-2015.</li> <li>The US publishes clinker production data beginning in 1925, and cement production data from 1880.</li> <li>Vietnam is a significant producer but doesn't collect or publish clinker production data. High levels of exports mean that applying a clinker ratio to cement production would be inappropriate. Here we follow Vietnam's own method of using cement production combined with clinker trade data to estimate clinker production.</li> </ul> </li> <li>The combined_cement_data.xlsx file is used to overwrite emissions with superior data, in most cases as reported in official reporting to the UNFCCC, e.g. Biennial Update Reports, National Communications, and National Inventory Reports. Where more than one data source has been found for a country (e.g. subsequent reports), a comparison is automatically made of overlapping data, and they are combined only if they are in very close agreement (i.e., significant revisions mean that previous estimates will be ignored).</li> <li>Clinker production data have been obtained for some countries in addition to those available from Annex 1 parties' CRFs, either from reporting to the UNFCCC or directly from official agencies. The period available varies by country. Emissions for these countries are calculated directly from these clinker production data where official emissions estimates are not available. <ul> <li>Afghanistan, Argentina, Armenia, Bangladesh, Brazil, Chile, China, Spain, Jamaica, Japan, Moldova, Norway, Paraguay, Poland, Rwanda, Turkey, Saudi Arabia, South Korea, Taiwan, Thailand, Togo, Tunisia, Ukraine, United Kingdom, USA, Uzbekistan.</li> </ul> </li> <li>Some countries do not report time-series of emissions, but do supply some isolated estimates in their official reporting to the UNFCCC, and these are used in some cases to constrain estimates.</li> <li>A number of countries state in their official reporting to the UNFCCC that they have never produced clinker, so emissions are set to zero for all years for these countries. In other cases, statements are made that no clinker was produced before or after a certain year, and this information is also incorporated. <ul> <li>Never produced clinker: Mauritania, Sierra Leone, Côte d'Ivoire, Brunei Darussalam, Tuvalu, Papua New Guinea, Guinea, Andorra, Singapore, Réunion, Guadeloupe, French Guiana, Martinique, Mayotte, Macao.</li> <li>Stopped or started producing clinker: Cambodia, Estonia, Fiji, Ghana, Iceland, the Netherlands (see file zero_before_after.csv).</li> </ul> </li> <li>The information available usually covers a number of years, up to 3 decades. These are then extrapolated by combining available data and assumptions about historical developments in clinker ratios to produce longer time series of emissions based on the longer cement production dataset. More details on this method are given in the accompanying journal paper.</li> <li>For any non-Annex I countries for which time-series data of neither emissions or clinker are available, and cement production is non-zero, clinker ratios derived from the Getting the Numbers Right (GNR) cement sustainability initiative are applied to the cement production dataset to derive approximate clinker production by country, from which emissions are calculated using IPCC default factors.</li> <li>Where emissions are estimated from clinker (or apparent clinker) production data, IPCC default factors are used, with the exception of China and Argentina, for which officially reported factors are used. The factor for CO2 emitted per tonne of clinker exhibits only small variations between countries, so using the default factor introduces very little uncertainty.</li> </ul> <p>This dataset contributes to:</p> <ul> <li>The <a href="https://globalcarbonbudget.org">Global Carbon Budget</a> (republished by <a href="https://ourworldindata.org/grapher/annual-co2-cement">Our World in Data</a>)</li> <li>The <a href="https://www.energyinst.org/statistical-review">Energy Institute</a> Statistical Review of World Energy</li> <li>The <a href="https://doi.org/10.5281/zenodo.4479171">PRIMAP-hist </a>emissions dataset</li> <li>The <a href="https://github.com/JGCRI/CEDS/wiki/Release-Notes">CEDS</a> emissions dataset</li> </ul> <p>See also:</p> <ul> <li>"Monthly global cement production data": <a href="https://doi.org/10.5281/zenodo.10277408">https://doi.org/10.5281/zenodo.10277408</a></li> </ul> <p>You may contact the author here: <a href="https://forms.gle/jeuyvoeXqBQMnsGX8">https://forms.gle/jeuyvoeXqBQMnsGX8</a></p>
HyUSPRe Report & Data on 'New experimental data on reactions between H2 and well cement and effects on fluid flow and mechanical properties of well cement
<p>In this study, new experimental data is presented of the effects of H<sub>2</sub> exposure and cyclic loading on mechanical properties of oil well (class G) cement, relevant for underground hydrogen storage operations. Changes in mechanical properties (Young’s modulus, Poisson’s ratio and ultimate strength) have been analyzed using unconfined compressive strength (UCS) tests and confined cyclic loading tests on class G cement samples that were unreacted (cured for 3 days at 80°C) and exposed to lime-saturated brine and N<sub>2</sub> or H<sub>2</sub> for 1 and 2 months. Changes in cement mineralogy were analyzed by XRD analysis of the unreacted and exposed samples. The mechanical properties of elastic modulus and Poisson’s ratio are within the expected range of an oil well cement. Differences in Young’s modulus, Poisson’s ratio and ultimate strength are limited between unreacted, N<sub>2</sub>-exposed and H<sub>2</sub>-exposed samples, when comparing UCS tests or confined cyclic loading tests. Repeated UCS tests seem to indicate that the variation in Young’s modulus and ultimate strength increases after N<sub>2</sub> and H<sub>2</sub> exposure, but this observation needs to be confirmed in additional tests. During cyclic axial loading of confined cement samples, irreversible (plastic) deformation (compaction) occurs that affect static Young’s modulus. Also, effects of exceeding yield and failure strength on Young’s modulus are observed. Dynamic Young’s moduli and Poisson’s ratios derived from acoustic velocity measurements during confined cyclic tests show limited variation, in particular if static and dynamic Young’s modulus are compared. The mineralogical changes as identified using XRD analysis suggest minor changes between unexposed and H<sub>2</sub>- and N<sub>2</sub>-exposed samples, although XRD patterns indicate some minerals that could not be identified. The main conclusion is that effects of H<sub>2</sub> exposure and cyclic loading on mechanical properties and mineralogical changes of class G cement is limited compared to unreacted or N<sub>2</sub> exposed samples for the investigated conditions. There is no indication that changes in mechanical properties of cement are such that cement integrity of wells used for underground hydrogen storage will be significantly affected. It should be emphasized that this conclusion is based on experiments on one type of cement (class G) and a limited set of conditions. In particular, additional tests to assess the reproducibility of current results and tests on samples that were exposed longer to H<sub>2</sub> and N<sub>2</sub> are of interest. Detailed effects of changing properties for the durability and integrity of wells can be derived by performing a parameter sensitivity analysis with well integrity modelling for the range in mechanical properties measured in this study.</p>
Data of the characterisation of conventional 87Sr/86Sr isotope ratios in cement, limestone and slate reference materials based on an interlaboratory comparison study
<p>This dataset represents the electronic supplementary material (ESM) of the publication entitled "Characterisation of conventional <sup>87</sup>Sr/<sup>86</sup>Sr isotope ratios in cement, limestone and slate reference materials based on an interlaboratory comparison study", which is published in Geostandards and Geoanalytical Research under the DOI: 10.1111/GGR.12517. It consists of four files. 'ESM_Data.xlsx' contains all reported data of the participants, a description of the applied analytical procedures, basic calculations, the consensus values, and part of the uncertainty assessment. 'ESM_Figure-S1' displays a schematic on how measurements, sequences and replicates are treated for the uncertainty calculation carried out by PTB. 'ESM_Technical-protocol.pdf' is the technical protocol of the interlaboratory comparison, which has been provided to all participants together with the samples and which contains bedside others the definition of the measurand and guidelines for data assessment and calculations. 'ESM_Reporting-template.xlsx' is the Excel template which has been submitted to all participants for reporting their results within the interlaboratory comparison. Excel files with names of the the structure 'GeoReM_Material_Sr8786_Date.xlsx' represent the <em>R</em><sub>con</sub>(<sup>87</sup>Sr/<sup>86</sup>Sr) data for a specific reference material downloaded from GeoReM at the specified date, e.g. 'GeoReM_IAPSO_Sr8786_20221115.xlsx' contains all <em>R</em><sub>con</sub>(<sup>87</sup>Sr/<sup>86</sup>Sr) data for the IAPSO seawater standard listed in GeoReM until 15 November 2022.</p>
Global CO2 uptake of cement in 1930-2019
<p>This dataset is associated with the publication on Earth System Science Data, with the same title.</p> <p>It includes four sections including the model inputs of the estimation models, the simulation results of global CO<sub>2</sub> emission and uptake by year, the variables and ranges considered in the uncertainty analyses of the uptake estimation and the corresponding confidence intervals from the analyses. </p> <p>For detailed explanations of these datasets, one should should refer to the original manuscript. </p>
Data for Deciphering-the-CO2-emissions-and-emission-intensity-of-cement-sector-in-China-through-decomposition-analysis
<p>The dataset contains data for Figure 7-13 in our article "<em>Deciphering the CO<sub>2</sub> emissions and emission intensity of cement sector in China through decomposition analysis</em>", and data for part of<em> China Cement Industry Dataset (CCID)</em>. </p>
Raw data for: Portland and Belite cement hydration acceleration by C-S-H seeds with variable w/c ratios
<p>Raw data for: "Portland and Belite cement hydration acceleration by C-S-H seeds with variable w/c ratios".</p> <p>Includes: Calorimetry, TA, LXRPD and MIP data.</p> <p> </p> <p>doi: <a href="https://doi.org/10.3390/ma15103553">https://doi.org/10.3390/ma15103553</a></p>
Use of waste materials for 3D printing of cement-based materials
<p>Experimental results:</p> <p>PSD = Particle Size Distribution</p> <p>XRF = X-Ray Fluorescence - chemical composition</p> <p> </p>
Micro-CT Imaging Dataset on ex-vivo Ovine Functional Spinal Segments as Healthy, Injured and Treated with Cement Discoplasty
<p>General information:</p> <p>- This dataset contains micro-CT images and mechanical test data from ovine functional spinal units (FSU). <br> - The micro-CT data was produced using a Bruker SkyScan 1172. The settings for the scans are given in the '.log' files in each folder. <br> - The compression testing was conducted on an MTS 858 Mini Bionix T/II. The settings for each test can be found in test '.txt' files.<br> - In short, every FSU was mechanically tested in compression under different conditions. Before and after every test, the FSUs were scanned to ensure there was no damage<br> to the sample. More information can be found in the related publication: <br> - The mechanical testing data is arranged in folders with consecutive cycles. It is highly recommended to use the last three cycles for analysis. </p> <p>Data set notation:</p> <p>- All the datasets are noted by Sheep number. Sh7 = Sheep 7; Sh8 = Sheep 8; Sh9 = Sheep 9. In the publication, the numbers were switched to 1,2,3 respectively.<br> - files denoted with '_rec' contain the reconstruction of the projection images. <br> - 'Tested' or 'After test' files refers to the scan after mechanical testing. </p>
Supplementary information for D4.6 CEMCAP comparative techno-economic analysis of CO2 capture in cement plants
<p>Supplementary information for D4.6 CEMCAP comparative techno-economic analysis of CO2 capture in cement plants</p>
Text-fig. 6. Photo of cave lion lower premolar p4 root cut. The approximate age of individual is 9.5 years (No 3 in Tabs 6, 7). The thin layers on the edge of root are the dental cement increments; number 1 marks winter increment, number 2 marks summer increment. Photo by M. Nývltová Fišáková. in The Mammalian Fauna Of Barová Cave (Moravian Karst, The Czech Republic)
Text-fig. 6. Photo of cave lion lower premolar p4 root cut. The approximate age of individual is 9.5 years (No 3 in Tabs 6, 7). The thin layers on the edge of root are the dental cement increments; number 1 marks winter increment, number 2 marks summer increment. Photo by M. Nývltová Fišáková.
Text-fig. 6. a. Vertical section showing part of body-chamber of a Cenoceras in the top of the Main Cenoceras Bed associated with attached oysters below and stringers of crinoid debris below and stretching laterally. Coin 23 mm in diameter. b. Complete lateral half of conch showing intact and elastically deformed septa on which rests crinoid debris that spreads across the exposed septa and onto the adjacent substrate. Conch approximately 180 mm in diameter. c. Individual showing dispersed crinoid and molluscan debris within body-chamber and septa in the crushed inner whorls that have taken a sparite cement prior to, and after having undergone brittle deformation. 160 mm in diameter. d. Vertically embedded specimen showing the loss of septa in the inner whorls that are infilled with matrix mottled by bioturbation. Tape measure provides scale. in 'Cenoceras Islands' In The Blue Lias Formation (Lower Jurassic) Of West Somerset, Uk: Nautilid Dominance And Influence On Benthic Faunas
Text-fig. 6. a. Vertical section showing part of body-chamber of a Cenoceras in the top of the Main Cenoceras Bed associated with attached oysters below and stringers of crinoid debris below and stretching laterally. Coin 23 mm in diameter. b. Complete lateral half of conch showing intact and elastically deformed septa on which rests crinoid debris that spreads across the exposed septa and onto the adjacent substrate. Conch approximately 180 mm in diameter. c. Individual showing dispersed crinoid and molluscan debris within body-chamber and septa in the crushed inner whorls that have taken a sparite cement prior to, and after having undergone brittle deformation. 160 mm in diameter. d. Vertically embedded specimen showing the loss of septa in the inner whorls that are infilled with matrix mottled by bioturbation. Tape measure provides scale.
Synchrotron Radiation Pair Distribution Function Analysis of gels in cements
<p>Raw data for: Synchrotron Radiation Pair Distribution Function Analysis of Gels in Cements. doi: https://doi.org/10.3390/cryst7100317</p> <p> </p> <p>The analysis of atomic ordering in a nanocrystalline phase with small particle size, below »5 nm, is intrinsically complicated because of the lack of long range order. Furthermore, the presence of additional crystalline phase(s) may exacerbate the problem as it is the case in cement pastes. Here we use synchrotron pair distribution function (PDF) chiefly to characterize the local atomic order of the nanocrystalline phases, gels, in cement pastes. We have used a multi r-range analysis approach, where the ~4-7 nm r-range allows determining the crystalline phase contents; the ~1-2.5 nm r-range is used to characterize the atomic ordering in the nanocrystalline component; and the ~0.2-1.0 nm r-range give insights about additional amorphous components. Specifically, we have prepared four alite pastes, with variable water contents, and the analyses showed that a defective tobermorite, Ca<sub>11</sub>Si<sub>9</sub>O<sub>28</sub>(OH)<sub>2</sub><sup>.</sup>8.5H<sub>2</sub>O, gave the best fits. Furthermore, the PDF analyses suggest that the calcium silicate hydrate gel is composed of this tobermorite and amorphous calcium hydroxide. Finally, this approach has been used to study alternative cements. The hydration of monocalcium aluminate and ye'elimite pastes yield aluminum hydroxide gels. PDF analyses show that these gels are constituted by nanocrystalline gibbsite and the particle size can be as small as 2.5 nm.</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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International Brain Laboratory public data
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OpenNeuro
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