TY - JOUR A1 - Costabel, S. A1 - Hiller, Thomas A1 - Dlugosch, R. A1 - Kruschwitz, Sabine A1 - Müller Petke, M. T1 - Evaluation of single-sided nuclear magnetic resonance technology for usage in geosciences N2 - Because of its mobility and ability to investigate exposed surfaces, single-sided (SiS) nuclear magnetic resonance (NMR) technology enables new application fields in geosciences. To test and assess its corresponding potential, we compare longitudinal (T1) and transverse (T2) data measured by SiS NMR with those of conventional geoscientific laboratory NMR. We use reference sandstone samples covering a broad range of pore sizes. Our study demonstrates that the lower signal-to-noise ratio of SiS NMR data generally tends to slightly overestimated widths of relaxation time distributions and consequently pore size distributions. While SiS and conventional NMR produce very similar T1 relaxation data, unbiased SiS NMR results for T2 measurements can only be expected for fine material, i.e. clayey or silty sediments and soils with main relaxation times below 0.05s. This limit is given by the diffusion relaxation rate due to the gradient in the primary magnetic field associated with the SiS NMR. Above that limit, i.e. for coarse material, the relaxation data is strongly attenuated. If considering the diffusion relaxation time of 0.2 s in the numerical data inversion process, the information content >0.2s is blurred over a range larger than that of conventional NMR. However, our results show that principle range and magnitudes of the relaxation time distributions are reconstructed to some extent. Regarding these findings, SiS NMR can be helpful to solve geoscientific issues, e.g. to assess the hydro-mechanical properties of the walls of underground facilities or to provide local soil moisture data sets for calibrating indirect remote techniques on the regional scale. The greatest opportunity provided by the SiS NMR technology is the acquisition of profile relaxation data for rocks with significant bedding structures at the µm scale. With this unique feature, SiS NMR can support the understanding and modeling of hydraulic and diffusional anisotropy behavior of sedimentary rocks. KW - Single-sided NMR KW - Geosciences KW - Nuclear magnetic resonance PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-561676 DO - https://doi.org/10.1088/1361-6501/ac9800 SN - 0957-0233 VL - 34 IS - 1 SP - 1 EP - 13 PB - IOP Publishing AN - OPUS4-56167 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Kruschwitz, Sabine A1 - Oesch, T. A1 - Mielentz, Frank A1 - Meinel, Dietmar A1 - Spyridis, P. T1 - Non-Destructive Multi-Method Assessment of Steel Fiber Orientation in Concrete N2 - Integration of fiber reinforcement in high-performance cementitious materials has become widely applied in many fields of construction. One of the most investigated advantages of steel Fiber reinforced concrete (SFRC) is the deceleration of crack growth and hence its improved sustainability. Additional benefits are associated with its structural properties, as fibers can significantly increase the ductility and the tensile strength of concrete. In some applications it is even possible to entirely replace the conventional reinforcement, leading to significant logistical and environmental benefits. Fiber reinforcement can, however, have critical disadvantages and even hinder the Performance of concrete, since it can induce an anisotropic material behavior of the mixture if the fibers are not appropriately oriented. For a safe use of SFRC in the future, reliable non-destructive testing (NDT) methods need to be identified to assess the fibers’ orientation in hardened concrete. In this study, ultrasonic material testing, electrical impedance testing, and X-ray computed tomography have been investigated for this purpose using specially produced samples with biased or random Fiber orientations. We demonstrate the capabilities of each of these NDT techniques for fiber orientation measurements and draw conclusions based on these results about the most promising areas for future research and development. KW - Spectral induced polarization KW - Steel fiber reiniforced concrete KW - Fiber orientation KW - Non-destructive testing KW - Micro-computed tomography KW - Ultrasound PY - 2022 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-543520 DO - https://doi.org/10.3390/app12020697 VL - 12 IS - 2 SP - 1 EP - 14 PB - MDPI CY - Basel Switzerland AN - OPUS4-54352 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Moreno Torres, Benjamí A1 - Völker, Christoph A1 - Munsch, Sarah Mandy A1 - Hanke, T. A1 - Kruschwitz, Sabine ED - Tosti, F. T1 - An Ontology-Based Approach to Enable Data-Driven Research in the Field of NDT in Civil Engineering N2 - Although measurement data from the civil engineering sector are an important basis for scientific analyses in the field of non-destructive testing (NDT), there is still no uniform representation of these data. An analysis of data sets across different test objects or test types is therefore associated with a high manual effort. Ontologies and the semantic web are technologies already used in numerous intelligent systems such as material cyberinfrastructures or research databases. This contribution demonstrates the application of these technologies to the case of the 1H nuclear magnetic resonance relaxometry, which is commonly used to characterize water content and porosity distri-bution in solids. The methodology implemented for this purpose was developed specifically to be applied to materials science (MS) tests. The aim of this paper is to analyze such a methodology from the perspective of data interoperability using ontologies. Three benefits are expected from this ap-proach to the study of the implementation of interoperability in the NDT domain: First, expanding knowledge of how the intrinsic characteristics of the NDT domain determine the application of semantic technologies. Second, to determine which aspects of such an implementation can be improved and in what ways. Finally, the baselines of future research in the field of data integration for NDT are drawn. KW - Ontology Engineering KW - Interoperability KW - Data-integration KW - NMR relaxometry KW - materials informatics PY - 2021 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-529716 DO - https://doi.org/10.3390/rs13122426 SN - 2072-4292 N1 - Geburtsname von Munsch, Sarah Mandy: Nagel, S. M. - Birth name of Munsch, Sarah Mandy: Nagel, S. M. VL - 13 IS - 12 SP - 2426 PB - Multidisciplinary Digital Publishing Institute (MDPI) CY - Basel, Switzerland AN - OPUS4-52971 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Völker, Christoph A1 - Firdous, R. A1 - Kruschwitz, Sabine A1 - Stephan, D. T1 - Sequential learning to accelerate discovery of alkali-activated binders N2 - 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. KW - Alkali-activated binders KW - Machine learning KW - Sequential learning KW - Materials by design KW - Materials informatics PY - 2021 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-531376 DO - https://doi.org/10.1007/s10853-021-06324-z SN - 0022-2461 SN - 1573-4803 VL - 56 SP - 15859 EP - 15881 PB - Springer CY - Dordrecht AN - OPUS4-53137 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Klewe, Tim A1 - Strangfeld, Christoph A1 - Ritzer, Tobias A1 - Kruschwitz, Sabine T1 - Combining Signal Features of Ground-Penetrating Radar to Classify Moisture Damage in Layered Building Floors N2 - To date, the destructive extraction and analysis of drilling cores is the main possibility to obtain depth information about damaging water ingress in building floors. The time- and costintensive procedure constitutes an additional burden for building insurances that already list piped water damage as their largest item. With its high sensitivity for water, a ground-penetrating radar (GPR) could provide important support to approach this problem in a non-destructive way. In this research, we study the influence of moisture damage on GPR signals at different floor constructions. For this purpose, a modular specimen with interchangeable layers is developed to vary the screed and insulation material, as well as the respective layer thickness. The obtained data set is then used to investigate suitable signal features to classify three scenarios: dry, damaged insulation, and damaged screed. It was found that analyzing statistical distributions of A-scan features inside one B-scan allows for accurate classification on unknown floor constructions. Combining the features with multivariate data analysis and machine learning was the key to achieve satisfying results. The developed method provides a basis for upcoming validations on real damage cases. KW - Radar KW - Material Moisture KW - Non-destructive testing KW - Signal Features KW - Civil Engineering KW - Machine Learning PY - 2021 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-533606 DO - https://doi.org/10.3390/app11198820 VL - 11 IS - 19 SP - 8820 PB - MDPI AN - OPUS4-53360 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Völker, Christoph A1 - Kruschwitz, Sabine A1 - Ebell, Gino T1 - Datengesteuerte Multisensor-Fusion zur Korrosionsprüfung von Stahlbetonbauteilen N2 - Potentialfeldmessung (PM) ist die beliebteste Methode der Zerstörungsfreien Prüfung (ZfP) zur Lokalisierung von aktiver Betonstahlkorrosion. PM wird durch Parameter wie z. B. Feuchtigkeits- und Chloridgradienten im Bauteil beeinflusst, so dass die Sensitivität gegenüber der räumlich sehr begrenzten, aber gefährlichen Lochkorrosion gering ist. Wir zeigen in dieser Studie, wie zusätzliche Messinformationen mit Multisensor-Datenfusion genutzt werden können, um die Detektionsleistung zu verbessern und die Auswertung zu automatisieren. Die Fusion basiert auf überwachtem maschinellen Lernen (ÜML). ÜML sind Methoden, die Zusammenhänge in (Sensor-) Daten anhand vorgegebener Kennzeichnungen (Label) erkennen. Wir verwenden ÜML um „defekt“ und „intakt“ gelabelte Bereiche in einem Multisensordatensatz zu unterscheiden. Unser Datensatz besteht aus 18 Messkampagnen und enthält jeweils PM-, Bodenradar-, Mikrowellen-Feuchte- und Wenner-Widerstandsdaten. Exakte Label für veränderliche Umweltbedingungen wurden in einer Versuchsanordnung bestimmt, bei der eine Stahlbetonplatte im Labor kontrolliert und beschleunigt verwittert. Der Verwitterungsfortschritt wurde kontinuierlich überwacht und die Korrosion gezielt erzeugt. Die Detektionsergebnisse werden quantifiziert und statistisch ausgewertet. Die Datenfusion zeigt gegenüber dem besten Einzelverfahren (PM) eine deutliche Verbesserung. Wir beschreiben die Herausforderungen datengesteuerter Ansätze in der zerstörungsfreien Prüfung und zeigen mögliche Lösungsansätze. T2 - DGZfP Jahrestagung 2018 CY - Leipzig, Germany DA - 07.05.2018 KW - Maschinelles Lernen KW - Datenfusion KW - ZfP KW - Beton KW - Korrosion PY - 2018 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-444852 UR - http://www.ndt.net/?id=23106 SN - 1435-4934 VL - 23 IS - 9 SP - 1 EP - 9 PB - NDT.net CY - Kirchwald AN - OPUS4-44485 LA - deu AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Kruschwitz, Sabine A1 - Halisch, M. A1 - Dlugosch, R. A1 - Prinz, Carsten T1 - Toward a better understanding of low-frequency electrical relaxation - An enhanced pore space characterization N2 - Relaxation phenomena observed in the electrical low-frequency range (approximately 1 mHz-10 kHz) of natural porous media like sandstones is often assumed to be directly related to the dominant (modal) pore throat sizes measured, for instance, with mercury intrusion porosimetry. Attempts to establish a universally valid relationship between pore size and peak Spectral Induced Polarization (SIP) relaxation time have failed, considering sandstones from very different origins and featuring great variations in textural and chemical compositions as well as in geometrical pore space properties. In addition working with characteristic relaxation times determined in Cole-Cole or Debye decomposition fits to build the relationship have not been successful. In particular, samples with narrow pore throats are often characterized by long SIP relaxation times corresponding to long “characteristic length scales” in these media, assuming that the diffusion coefficients along the electrical double layer were constant. Based on these observations, three different types of SIP relaxation can be distinguished. We present a new way of assessing complex pore spaces of very different sandstones in a multi-methodical approach to combine the benefits of mercury intrusion porosimetry, micro-computed tomography, and nuclear magnetic resonance. In this way, we achieve much deeper insight into the pore space due to the different resolutions and sensitivities of the applied methods to both pore constrictions (throats) and wide pores (pore bodies). We experimentally quantify pore aspect ratios and volume distributions within the two pore regions. We clearly observe systematic differences between three SIP relaxation types identified previously and can attribute the SIP peak relaxation times to measured characteristic length scales within our materials. We highlight selected results for a total of nine sandstones. It seems that SIP relaxation behavior depends on the size difference of the narrow pore throats to the wide pore bodies, which increases from SIP Type 1 to Type 3. KW - µ-CT KW - Spectral induced polarization KW - Nuclear magnetic resonance KW - Pore space PY - 2020 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-509763 DO - https://doi.org/10.1190/GEO2019-0074.1 SN - 0016-8033 VL - 85 IS - 4 SP - MR257 EP - MR270 PB - Society of Exploration Geophysicists AN - OPUS4-50976 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Völker, Christoph A1 - Kruschwitz, Sabine A1 - Ebell, Gino T1 - A machine learning‑based data fusion approach for improved corrosion testing N2 - This work presents machine learning-inspired data fusion approaches to improve the non-destructive testing of reinforced concrete. The principal effects that are used for data fusion are shown theoretically. Their effectiveness is tested in case studies carried out on largescale concrete specimens with built-in chloride-induced rebar corrosion. The dataset consists of half-cell potential mapping, Wenner resistivity, microwave moisture and ground penetrating radar measurements. Data fusion is based on the logistic Regression algorithm. It learns an optimal linear decision boundary from multivariate labeled training data, to separate intact and defect areas. The training data are generated in an experiment that simulates the entire life cycle of chloride-exposed concrete building parts. The unique possibility to monitor the deterioration, and targeted corrosion initiation, allows data labeling. The results exhibit an improved sensitivity of the data fusion with logistic regression compared to the best individual method half-cell potential. KW - Corrosion KW - Potential mapping KW - Machine learning PY - 2019 DO - https://doi.org/10.1007/s10712-019-09558-4 SN - 1573-0956 SN - 0169-3298 VL - 41 IS - 3 SP - 531 EP - 548 PB - Springer Nature AN - OPUS4-48799 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Munsch, Sarah Mandy A1 - Strangfeld, Christoph A1 - Kruschwitz, Sabine ED - Kärger, J. ED - Heitjans, P. T1 - Determining the pore size distribution in synthetic and building materials using 1D NMR N2 - NMR is gaining increasing interest in civil engineering applications for the use of microstructure characterization as e.g. pore size determination and monitoring of moisture transport in porous materials. In this study, the use of NMR as a tool for pore size characterization was investigated. For our study we used screed and synthetic materials at partial and full saturation. A successful determination could be achieved when having a reference or calibration method, although partly diffusion effects have been registered. Due to these diffusion effects, for the determination of pore size distributions of synthetic materials another NMR device was needed. Finally, the determination of the surface relaxivity of screed (50 μm/s) led to a higher value than first expected from literature. T2 - 14th International Bologna Conference on Magnetic Resonance in Porous Media CY - Gainesville, FL, USA DA - 18.02.2018 KW - NMR relaxometry KW - Pore size distribution KW - Building materials KW - Porous materials KW - Surface relaxivity PY - 2019 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-483680 UR - https://diffusion.uni-leipzig.de/pdf/volume31/diff_fund_31(2019)02.pdf SN - 1862-4138 N1 - Geburtsname von Munsch, Sarah Mandy: Nagel, S. M. - Birth name of Munsch, Sarah Mandy: Nagel, S. M. VL - 31 IS - 2 SP - 1 EP - 9 PB - University of Leipzig CY - Leipzig AN - OPUS4-48368 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Klewe, Tim A1 - Strangfeld, Christoph A1 - Kruschwitz, Sabine T1 - Review of moisture measurements in civil engineering with ground penetrating radar – Applied methods and signal features N2 - When applying Ground Penetrating Radar (GPR) to assess the moisture content of building materials, different medium properties, dimensions, interfaces and other unknown influences may require specific strategies to achieve useful results. Hence, we present an overview of the various approaches to carry out moisture measurements with GPR in civil engineering (CE). We especially focus on the applied Signal features such as time, amplitude and frequency features and discuss their limitations. Since the majority of publications rely on one single feature when applying moisture measurements, we also hope to encourage the consideration of approaches that combine different signal features for further developments. KW - Ground Penetrating Radar KW - Moisture KW - Civil engineering KW - Signal features PY - 2021 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-520684 DO - https://doi.org/10.1016/j.conbuildmat.2021.122250 VL - 278 SP - 122250 PB - Elsevier Ltd. AN - OPUS4-52068 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Munsch, Sarah Mandy A1 - Strangfeld, Christoph A1 - Kruschwitz, Sabine T1 - Application of 1H proton NMR relaxometry to building materials - A review N2 - Since nuclear magnetic resonance with focus on 1H protons is highly sensitive to pore filling fluids, it is nowadays often applied for the investigation of porous media. Mainly in materials research and especially in the field of non-destructive testing in civil engineering it is increasingly used. Scientific questions about and based on NMR meanwhile cover a broad spectrum. To give an overview, we have reviewed various studies dealing with the determination of moisture contents and parameters such as the pore-size distribution, surface relaxivity, porosity, etc. In some papers, the monitoring of moisture transport in connection with degradation processes or admixtures was the main objective. In other papers, NMR was used for pore space analysis or even applied on site to assess the state of conservation of cultural heritage. Building materials that have been investigated in the presented studies are for example cement, concrete, woods, sandstones etc. In this paper, short descriptions and the significant results of the reviewed articles are summarized and their measurement problems and discrepancies are pointed out. A special feature of this review article is the concise tabular compilation of determined 𝑇1 and 𝑇2 relaxation times, as well as of surface relaxivity values for various materials and components. Finally, relevant aspects are summed up and conclusions about the increasing potential of NMR relaxometry for investigations of porous building materials are drawn, followed by an outlook about future applications and the need for technical development. KW - NMR relaxometry KW - Building materials KW - Natural stones KW - Relaxation times KW - Surface relaxivities KW - Moisture KW - Pore space characterization PY - 2021 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-521888 DO - https://doi.org/10.1016/j.jmro.2021.100012 N1 - Geburtsname von Munsch, Sarah Mandy: Nagel, S. M. - Birth name of Munsch, Sarah Mandy: Nagel, S. M. VL - 6-7 SP - 100012 PB - Elsevier Inc. CY - Amsterdam AN - OPUS4-52188 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Millar, Steven A1 - Gottlieb, Cassian A1 - Sankat, Nina A1 - Wilsch, Gerd A1 - Kruschwitz, Sabine T1 - Chlorine determination in cement-bound materials with Laser-induced Breakdown Spectroscopy (LIBS) – A review and validation N2 - The determination of chloride is still one of the main tasks for the evaluation of reinforced concrete structures. The corrosion of the reinforcement induced by the penetrating chlorides is the dominant damage process affecting the lifetime of concrete structures. In the recent years different research groups demonstrated that LIBS can be a fast and reliable method to quantify chlorine in cement-bound materials. Because chlorine in concrete can only occur as solved ions in the pore solution or bound in salts or hydrated cement phases, the detected emission of chlorine can be correlated with the chloride concentration determined e.g. with potentiometric titration. This work inter alia describes the production of reference samples and possible side effects during the production process. Due to transport processes in the porous matrix of the cement a misinterpretation of the concentrations is possible. It is shown how to overcome these effects and higher precisions of the single measurements can be realised. Using the calibration method, blank sample method and noise method, three different ways of calculating the limit of detection (LOD) and limit of quantification (LOQ) are compared. Due to the preparation of the reference samples a precision of the whole calibration model of sx0 = 0.023 wt% is determined. The validation of the model is based on different test sets, which are varying in their composition (different Cl-salts, water-to-cement ratios and additives). The determined mean error of the validation is 0.595 ± 0.063 wt%, which is comparable to standardised methods like potentiometric titration, direct potentiometry or photometry (0.40 ± 0.06 wt%) [1]. KW - LIBS KW - Chlorine KW - Cement KW - Calibration KW - Validation PY - 2018 DO - https://doi.org/10.1016/j.sab.2018.05.015 SN - 0584-8547 VL - 147 IS - September SP - 1 EP - 8 PB - Elsevier B.V. CY - Amsterdam AN - OPUS4-46558 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Millar, Steven A1 - Kruschwitz, Sabine A1 - Wilsch, Gerd T1 - Determination of total chloride content in cement pastes with laser-induced breakdown spectroscopy (LIBS) N2 - The presented work discusses the accuracy of Laser Induced Breakdown Spectroscopy (LIBS) in determining the total chloride content in cement pastes. LIBS as an emission spectroscopy method is used to detect simultaneously several elements present in cement-based materials. By scanning surfaces the variability in the spatial distribution of elements can be visualised. However, for a quantification of the results, studies are necessary to characterise possible influences due to the wide variation of the chemical compositions in which cement can occur. It is shown how the calibration can be done, how the calibration samples were produced, and which statistical parameters are necessary to describe the precision of the regression. The performance of LIBS is estimated by detecting chloride in validation samples. Therefore, 55 samples and 7 ets with changing mix ompositions were produced. The presented study deals with possible influences of different mix compositions, ncluding different cations of chloride, varying w/c-ratios and the artial replacement of Portland cement with last furnace slag (50% BFS) and limestone (30% LS). Comparing the LIBS results with otentiometric titration, n accuracy of±0.05 wt%/total has been determined. KW - Spectroscopy KW - LIBS KW - Chloride KW - Quantification KW - Cement PY - 2019 DO - https://doi.org/10.1016/j.cemconres.2018.12.001 SN - 0008-8846 VL - 117 IS - March SP - 16 EP - 22 PB - Elsevier CY - Amsterdam AN - OPUS4-47059 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Zhang, Z. A1 - Kruschwitz, Sabine A1 - Weller, A. A1 - Halisch, M. T1 - Enhanced pore space analysis by use of µ-CT, MIP, NMR, and SIP N2 - We investigate the pore space of rock samples with respect to different petrophysical parameters using various methods, which provide data on pore size distributions, including micro computed tomography (µ-CT), mercury Intrusion porosimetry (MIP), nuclear magnetic resonance (NMR), and spectral-induced polarization (SIP). The resulting cumulative distributions of pore volume as a function of pore size are compared. Considering that the methods differ with regard to their limits of resolution, a multiple-length-scale characterization of the pore space is proposed, that is based on a combination of the results from all of these methods. The approach is demonstrated using samples of Bentheimer and Röttbacher sandstone. Additionally, we compare the potential of SIP to provide a pore size distribution with other commonly used methods (MIP, NMR). The limits of Resolution of SIP depend on the usable frequency range (between 0.002 and 100 Hz). The methods with similar Resolution show a similar behavior of the cumulative pore volume distribution in the verlapping pore size range. We assume that µ-CT and NMR provide the pore body size while MIP and SIP characterize the pore throat size. Our study Shows that a good agreement between the pore radius distributions can only be achieved if the curves are adjusted considering the resolution and pore volume in the relevant range of pore radii. The MIP curve with the widest range in Resolution should be used as reference. KW - Pore space KW - Induced polarization KW - Mercury intrusion porosimetry KW - µ-CT KW - NMR PY - 2018 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-465071 DO - https://doi.org/10.5194/se-9-1225-2018 SN - 1869-9510 SN - 1869-9529 VL - 9 IS - 6 SP - 1225 EP - 1238 PB - Copernicus Publications CY - Göttingen AN - OPUS4-46507 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Kruschwitz, Sabine A1 - Zhang, Z. A1 - Weller, A. A1 - Nordsiek, S. T1 - Effect of evaporative drying on complex conductivity spectra of sandstones N2 - Dehydration is a common process occurring in natural environments, rocks, and building materials. Suitable methods for monitoring the changing moisture content should be identified. We have investigated the impact of dehydration of sandstones on complex conductivity spectra. Spectral induced polarization measurements were performed on five sandstone samples during evaporative drying. The complex conductivity spectra indicate considerable changes with decreasing saturation. The relationship between conductivity and saturation can be described by a power law known as the second empirical Archie equation. Separate saturation exponents have been determined for the real and imaginary parts of conductivity. The imaginary part of conductivity indicates higher saturation exponents for the investigated sandstones compared to the real part. Obviously, the saturation exponents depend on the method used for changing water saturation. Evaporative drying, which is used in our experiments, causes an increase of pore-water salinity and results in lower saturation exponents for the real part of conductivity but higher exponents for the imaginary part in comparison with the classical imbibition/Drainage technique. We evaluate a theoretical approach that considers the influence of pore water salinity on the saturation exponents of the real and imaginary parts of conductivity. The complex conductivity spectra are processed by a Debye decomposition procedure. The resulting integrating parameters such as direct current resistivity, total chargeability, normalized chargeability, and mean relaxation time indicate a power law dependence on saturation. Our experiments indicate that the imaginary part of conductivity and normalized chargeability have a high sensitivity related to the drying process of rocks and might be suitable indicators to Monitor the changes of moisture content in sandstones. KW - Saturation KW - Spectral induced polarization KW - Sandstones KW - Evaporative drying PY - 2019 DO - https://doi.org/10.1190/GEO2018-0054.1 SN - 0016-8033 VL - 84 IS - 1 SP - MR61 EP - MR72 PB - SEG - Society of Exploration Geophysicists CY - Tulsa, Okla. AN - OPUS4-47499 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Völker, Christoph A1 - Moreno Torres, Benjami A1 - Rug, Tehseen A1 - Firdous, Rafia A1 - Zia, Ghezal Ahmad A1 - Lüders, Stefan A1 - Lisdero Scaffino, Horacio A1 - Höpler, Michael A1 - Böhmer, Felix A1 - Pfaff, Matthias A1 - Stephan, Dietmar A1 - Kruschwitz, Sabine T1 - Data driven design of alkali-activated concrete using sequential learning N2 - This paper presents a novel approach for developing sustainable building materials through Sequential Learning. Data sets with a total of 1367 formulations of different types of alkali-activated building materials, including fly ash and blast furnace slag-based concrete and their respective compressive strength and CO2-footprint, were compiled from the literature to develop and evaluate this approach. Utilizing this data, a comprehensive computational study was undertaken to evaluate the efficacy of the proposed material design methodologies, simulating laboratory conditions reflective of real-world scenarios. The results indicate a significant reduction in development time and lower research costs enabled through predictions with machine learning. This work challenges common practices in data-driven materials development for building materials. Our results show, training data required for data-driven design may be much less than commonly suggested. Further, it is more important to establish a practical design framework than to choose more accurate models. This approach can be immediately implemented into practical applications and can be translated into significant advances in sustainable building materials development. KW - Sustainable building materials KW - Sequential learning KW - Data-driven materials design KW - Alkali-activated building materials PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-584376 UR - https://www.sciencedirect.com/science/article/pii/S095965262302379X DO - https://doi.org/10.1016/j.jclepro.2023.138221 SN - 0959-6526 SN - 1879-1786 VL - 418 SP - 1 EP - 13 PB - Elsevier CY - Amsterdam AN - OPUS4-58437 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Völker, Christoph A1 - Moreno Torres, Benjami A1 - Zia, Ghezal Ahmad A1 - Rug, Tehseen A1 - Firdous, Rafia A1 - Böhmer, Felix A1 - Stephan, Dietmar A1 - Kruschwitz, Sabine T1 - Presenting SLAMD – A Sequential Learning Based Software for the Inverse Design of Sustainable Cementitious Materials N2 - In recent decades, the number of components in concrete has grown, particularly in formulations aimed at reducing carbon footprints. Innovations include diverse binders, supplementary cementitious materials, activators, concrete admixtures, and recycled aggregates. These developments target not only the enhancement of material properties but also the mitigation of the ecological and economic impacts of concrete — the most extensively used material by humankind. However, these advancements also introduce a greater variability in the composition of raw materials. The material’s behavior is significantly influenced by its nanoscale properties, which can pose challenges in accurate characterization. Consequently, there’s an increasing need for experimental tuning of formulations. This is accompanied by a more inconsistent composition of raw materials, which makes an experimental tuning of formulations more and more necessary. However, the increased complexity in composition presents a challenge in finding the ideal formulation through trial and error. Inverse design (ID) techniques offer a solution to this challenge by allowing for a comprehensive search of the entire design space to create new and improved concrete formulations. In this publication, we introduce the concept of ID and demonstrate how our open-source app “SLAMD” provides all necessary steps of the workflow to adapt it in the laboratory, lowering the application barriers. The intelligent screening process, guided by a predictive model, leads to a more efficient and effective data-driven material design process resulting in reduced carbon footprint and improved material quality while considering socio-economic factors in the materials design. KW - Sustainable concrete KW - Machine learning optimization KW - Inverse design techniques KW - Scientific software KW - Data-driven material design PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-589993 DO - https://doi.org/10.17756/nwj.2023-s2-032 VL - 9 SP - 180 EP - 187 AN - OPUS4-58999 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Klewe, Tim A1 - Völker, Tobias A1 - Landmann, Mirko A1 - Kruschwitz, Sabine T1 - LIBS‐ConSort: Development of a sensor‐based sorting method for construction and demolition waste N2 - AbstractA joint project of partners from industry and research institutions approaches the challenge of construction and demolition waste (CDW) sorting by investigating and testing the combination of laser‐induced breakdown spectroscopy (LIBS) with near‐infrared (NIR) spectroscopy and visual imaging. Joint processing of information (data fusion) is expected to significantly improve the sorting quality of various materials like concrete, main masonry building materials, organic components, etc., and may enable the detection and separation of impurities such as SO3‐cotaining building materials (gypsum, aerated concrete, etc.)Focusing on Berlin as an example, the entire value chain will be analyzed to minimize economic / technological barriers and obstacles at the cluster level and to sustainably increase recovery and recycling rates.The objective of this paper is to present current progress and results of the test stand development combining LIBS with NIR spectroscopy and visual imaging. In the future, this laboratory prototype will serve as a fully automated measurement setup to allow real‐time classification of CDW on a conveyor belt. T2 - 21st Ibausil - International Conference on Building Materials CY - Weimar, Germany DA - 13.09.2023 KW - NDT KW - Material cassification KW - Recycling KW - LIBS KW - Data fusion KW - Construction and demolition waste KW - Circular economy PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-590734 DO - https://doi.org/10.1002/cepa.2866 SN - 2509-7075 VL - 6 IS - 6 SP - 973 EP - 976 PB - Ernst & Sohn GmbH AN - OPUS4-59073 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Jablonka, Kevin Maik A1 - Ai, Qianxiang A1 - Al-Feghali, Alexander A1 - Badhwar, Shruti A1 - Bocarsly, Joshua D. A1 - Bran, Andres M. A1 - Bringuier, Stefan A1 - Brinson, L. Catherine A1 - Choudhary, Kamal A1 - Circi, Defne A1 - Cox, Sam A1 - de Jong, Wibe A. A1 - Evans, Matthew L. A1 - Gastellu, Nicolas A1 - Genzling, Jerome A1 - Gil, María Victoria A1 - Gupta, Ankur K. A1 - Hong, Zhi A1 - Imran, Alishba A1 - Kruschwitz, Sabine A1 - Labarre, Anne A1 - Lála, Jakub A1 - Liu, Tao A1 - Ma, Steven A1 - Majumdar, Sauradeep A1 - Merz, Garrett W. A1 - Moitessier, Nicolas A1 - Moubarak, Elias A1 - Mouriño, Beatriz A1 - Pelkie, Brenden A1 - Pieler, Michael A1 - Ramos, Mayk Caldas A1 - Ranković, Bojana A1 - Rodriques, Samuel G. A1 - Sanders, Jacob N. A1 - Schwaller, Philippe A1 - Schwarting, Marcus A1 - Shi, Jiale A1 - Smit, Berend A1 - Smith, Ben E. A1 - Van Herck, Joren A1 - Völker, Christoph A1 - Ward, Logan A1 - Warren, Sean A1 - Weiser, Benjamin A1 - Zhang, Sylvester A1 - Zhang, Xiaoqi A1 - Zia, Ghezal Ahmad A1 - Scourtas, Aristana A1 - Schmidt, K. J. A1 - Foster, Ian A1 - White, Andrew D. A1 - Blaiszik, Ben T1 - 14 examples of how LLMs can transform materials science and chemistry: a reflection on a large language model hackathon N2 - Large-language models (LLMs) such as GPT-4 caught the interest of many scientists. Recent studies suggested that these models could be useful in chemistry and materials science. To explore these possibilities, we organized a hackathon. This article chronicles the projects built as part of this hackathon. Participants employed LLMs for various applications, including predicting properties of molecules and materials, designing novel interfaces for tools, extracting knowledge from unstructured data, and developing new educational applications. The diverse topics and the fact that working prototypes could be generated in less than two days highlight that LLMs will profoundly impact the future of our fields. The rich collection of ideas and projects also indicates that the applications of LLMs are not limited to materials science and chemistry but offer potential benefits to a wide range of scientific disciplines. KW - Large Language model KW - Hackathon KW - Concrete KW - Prediction KW - Inverse Design KW - Orchestration PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-589961 DO - https://doi.org/10.1039/d3dd00113j VL - 2 IS - 5 SP - 1233 EP - 1250 PB - Royal Society of Chemistry (RSC) AN - OPUS4-58996 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Kruschwitz, Sabine A1 - Munsch, Sarah A1 - Telong, Melissa A1 - Schmidt, Wolfram A1 - Bintz, Thilo A1 - Fladt, Matthias A1 - Stelzner, Ludwig T1 - The NMR core analyzing TOMograph: A multi-functional tool for non-destructive testing of building materials N2 - NMR is becoming increasingly popular for the investigation of building materials as it is a non-invasive technology that does not require any sample preparation nor causes damage to the material. Depending on the specific application it can offer insights into properties like porosity and spatial saturation degree as well as pore structure. Moreover it enables the determination of moisture transport properties and the (re-)distribution of internal moisture into different reservoirs or chemical phases upon damage and curing. However, as yet most investigations were carried out using devices originally either designed for geophysical applications or the analysis of rather homogeneous small scale (< 10 mL) samples. This paper describes the capabilities of an NMR tomograph, which has been specifically optimized for the investigation of larger, heterogeneous building material samples (diameters of up to 72 mm, length of up to 700 mm) with a high flexibility due to interchangeable coils allowing for a high SNR and short echo times (50 - 80 m s). KW - Fire spalling KW - Moisture transport KW - Concrete KW - Cement hydration KW - Sensitivity KW - Supplementary cementitous materials KW - Frost salt attack PY - 2023 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-573755 DO - https://doi.org/10.1016/j.mrl.2023.03.004 SN - 2097-0048 VL - 3 IS - 3 SP - 207 EP - 219 PB - Elsevier B.V. AN - OPUS4-57375 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -