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A thorough characterization of base materials is the prereq- uisite for further research. In this paper, the characterization data of the reference materials (CEM I 42.5 R, limestone pow- der, calcined clay and a mixture of these three components) used in the second funding phase of the priority program 2005 of the German Research Foundation (DFG SPP 2005) are presented under the aspects of chemical and min- eralogical composition as well as physical and chemical properties. The data were collected based on tests performed by up to eleven research groups involved in this cooperative program.
The effect of resting time on the rheological properties of cement suspensions is generally explained by early formed structure and overconsumption of polycarboxylate superplasticizers (PCEs). In this paper, we propose that the influence of resting time on the rheological properties is closely related to size variation of non-absorbed PCE. To identify this, glass bead suspensions were prepared with various amounts of PCE and ionic solution, and their rheological properties were evaluated at various times. We found that the yield stress increases with time at higher PCE concentrations and higher ionic strength solutions. Adsorbed PCE during resting tends to bridge the particles rather than disperse them. In addition, it was found that hydrodynamic radius of PCE increased with resting time, and depletion forces resulting from non-absorbed PCE size changes correlate well with the increased yield stress.
This study uses conventional 87Sr/86Sr and 143Nd/144Nd isotope and interelement ratios of Ca, Sr, K, Mn, Mg and Ti as fingerprints for provenancing ordinary Portland cements (OPC). Herein, the first database of Sr and Nd isotope ratios investigated in OPCs, stemming from 29 cement plants located worldwide, was created. The results show that the Sr isotope ratios of OPCs are higher than those of seawater from the observed geological period. The spread of 143Nd/144Nd in OPCs is not as large as the spread for 87Sr/86Sr isotope ratios. However, the combination of both Sr and Nd isotope ratios provides the potential for distinguishing between cements of different production sites. Most of the OPCs investigated have measurable differences in their 87Sr/86Sr and 143Nd/144Nd isotope ratios, which can be employed as a valuable analytical fingerprinting tool. In the case of equivocal results, divisive hierarchical clustering was employed to help overcome this issue. The construction of geochemical profiles allowed the computing of suitably defined distances between cements and clustering them according to their chemical similarity. By applying this methodology, successful fingerprinting was achieved in 27 out of the 29 ordinary Portland cements that were analysed.
Single reuse of asphalt is an approved practice, but its success highly depends on restoring the properties of the aged binder. Rejuvenators have become increasingly important for softening the binder because they make it possible to increase the amount of reclaimed asphalt pavement (RAP) while reducing the dependence on virgin bitumen. The vital questions to be investigated are how the rejuvenators affect the ageing properties of bitumen and if rejuvenators offer the possibility of cyclic bitumen reuse. The main objective of this publication is to present the current state of the art regarding the effects of rejuvenators on bitumen ageing. The results of laboratory life cycle simulations indicate that repetitive ageing and rejuvenation processes are possible, but reuse mainly depends on the rejuvenator type and its interaction with the respective bitumen sample. There are rejuvenators that have good rejuvenating properties but accelerate subsequent ageing, which is essential to consider when evaluating a rejuvenator. Bitumen rejuvenated with petroleum-based products, such as aromatic extracts, performs slightly better after subsequent ageing than when rejuvenated with bio-based products. As there are a limited number of studies simulating cyclic bitumen reuse, more studies are necessary to evaluate the general limits of bitumen reuse.
With 8% of man-made CO2 emissions, cement production is an important driver of the climate crisis. By using alkali-activated binders, part of the energy-intensive clinker production process can be dispensed. However, as numerous raw materials are involved in the manufacturing process here, the complexity of the materials increases by orders of magnitude. Finding a properly balanced binder formulation is like looking for a needle in a haystack. We have shown for the first time that artificial intelligence (AI)-based optimization of alkali-activated binder formulations can significantly accelerate research.
The "Sequential Learning App for Materials Discovery" (SLAMD) aims to accelerate practice transfer. With SLAMD, materials scientists have low-threshold access to AI through interactive and intuitive user interfaces. The value added by AI can be determined directly. For example, the CO2 emissions saved per ton of cement can be determined for each development cycle: the more efficient the AI optimization, the greater the savings.
Our material database already includes more than 120,000 data points of alternative binders and is constantly being expanded with new parameters. We are currently driving the enrichment of the data with a life cycle analysis of the building materials.
Based on a case study we show how intuitive access to AI can drive the adoption of techniques that make a real contribution to the development of resource-efficient and sustainable building materials of the future and make it easy to identify when classical experiments are more efficient.
The 87Sr/86Sr isotope ratio can, in principle, be used for provenancing of cement. However, while commercial cements consist of multiple components, no detailed investigation into their individual 87Sr/86Sr isotope ratios or their influence on the integral 87Sr/86Sr isotope ratio of the resulting cement was conducted previously. Therefore, the present study aimed at determining and comparing the conventional 87Sr/86Sr isotope ratios of a diverse set of Portland cements and their corresponding Portland clinkers, the major component of these cements. Two approaches to remove the additives from the cements, i.e. to measure the conventional 87Sr/86Sr isotopic fingerprint of the clinker only, were tested, namely, treatment with a potassium hydroxide/sucrose solution and sieving on a 11-µm sieve. Dissolution in concentrated hydrochloric acid/nitric acid and in diluted nitric acid was employed to determine the 87Sr/86Sr isotope ratios of the cements and the individual clinkers. The aim was to find the most appropriate sample preparation procedure for cement provenancing, and the selection was realised by comparing the 87Sr/86Sr isotope ratios of differently treated cements with those of the corresponding clinkers. None of the methods to separate the clinkers from the cements proved to be satisfactory. However, it was found that the 87Sr/86Sr isotope ratios of clinker and cement generally corresponded, meaning that the latter can be used as a proxy for the clinker 87Sr/86Sr isotope ratio. Finally, the concentrated hydrochloric acid/nitric acid dissolution method was found to be the most suitable sample preparation method for the cements; it is thus recommended for 87Sr/86Sr isotope analyses for cement provenancing.
Basic oxygen furnace slags (BOFS) are by-products of the steelmaking process. Several researchers have studied the production of Portland cement clinker and metallic iron from BOFS via a reductive treatment.
In this study, we applied a carbothermal reduction of BOFS in a technical-scale electric arc furnace and characterised the clinker-like products. Those clinker-like non-metallic products (NMPs) had a chemical and mineralogical composition comparable to clinker for ordinary Portland cement (OPC) and contained large elongated alite crystals as major component. The pure NMPs reacted more slowly and achieved a lower degree of hydration compared with commercial OPC.
If the reactivity of the products can be further increased by employing specific adaptations, it can be used as a full clinker substitute for OPC. Nevertheless, it is also an option to use the material without further modifications as a cement component or concrete addition, which contributes to the strength development in both cases.
Alkali-activated binders (AAB) can provide a clean alternative to conventional cement in terms of CO2 emissions. However, as yet there are no sufficiently accurate material models to effectively predict the AAB properties, thus making optimal mix design highly costly and reducing the attractiveness of such binders. This work adopts sequential learning (SL) in high-dimensional material spaces (consisting of composition and processing data) to find AABs that exhibit desired properties. The SL approach combines machine learning models and feedback from real experiments. For this purpose, 131 data points were collected from different publications. The data sources are described in detail, and the differences between the binders are discussed. The sought-after target property is the compressive strength of the binders after 28 days. The success is benchmarked in terms of the number of experiments required to find materials with the desired strength. The influence of some constraints was systematically analyzed, e.g., the possibility to parallelize the experiments, the influence of the chosen algorithm and the size of the training data set. The results show the advantage of SL, i.e., the amount of data required can potentially be reduced by at least one order of magnitude compared to traditional machine learning models, while at the same time exploiting highly complex information. This brings applications in laboratory practice within reach.
With the aim of identifying the origin and the manufacturer of a cement, a reliable procedure that provides unambiguous results is needed. Such procedure could resolve practical issues in damage research, liability issues and forensic investigations. A substantial number of attempts for fingerprinting of building materials, including cement, has already been carried out during the last decades. Most of them were based on concentration analysis of the main elements/components. This review provides an overview of provenance studies of cement and the main approaches commonly used. Provenance studies of cement via isotope techniques are also presented and discussed as representatives of the state-of-the-art in the field. Due to the characteristic properties and the occurrence of carefully selected isotope ratios, unique fingerprints of different kinds of materials can be provided by these methods. This property has largely been explored in various scientific fields such as geo- and cosmochemistry, food forensics, archaeology, geochronology, biomedical studies, and climate change processes. However, the potential of isotope techniques in cement and concrete research for provenance studies has barely been investigated.
Therefore, the review outlines a suitable approach using isotope ratios, which could lead to reliable provenancing of cementitious materials in the future.
Bitumen is a crucial building material in road construction, which is exposed to continuously higher stresses due to higher traffic loads and changing climatic conditions. Therefore, various additives are increasingly being added to the bitumen complicating the characterisation of the bituminous binder, especially concerning the reuse of reclaimed asphalt.
Therefore, this work aimed to demonstrate that the combination of Fourier transform infrared (FTIR) spectroscopy with attenuated total reflexion (ATR) technique and multivariate evaluation is a very wellsuited method to reliable identify and quantify additives in bituminous binders. For this purpose, various unmodified and modified binders, directly and extracted from laboratory and reclaimed asphalts, were investigated with FTIR-ATR spectroscopy. The determined spectra, pre-processed by standard normal variate (SNV) transformation and the determination of the 1st derivation, were evaluated using factor Analysis (FA), linear discriminant analysis (LDA) and partial least square regression (PLSR). With this multivariate evaluation, first, a significant model with a very high hit rate of over 90% was developed allowing for the identification of styrene-butadiene copolymers (SBC), ethylene-copolymer bitumen (ECB) and different waxes (e.g. amide and Fischer-Tropsch wax) even if the additives do not show any additional peaks or the samples are multi-modified. Second, a quantification of the content is possible for SBC, ECB, and Amide wax with a mean error of RMSE B 0.4 wt% and a
coefficient of determination of R2[90%. Based on these results, FTIR identification and quantification of additives in bituminous binders is a very promising method with a great potential.