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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.
2D evaluation of spectral LIBS data derived from heterogeneous materials using cluster algorithm
(2017)
Laser-induced Breakdown Spectroscopy (LIBS) is capable of providing spatially resolved element maps in regard to the chemical composition of the sample. The evaluation of heterogeneous materials is often a challenging task, especially in the case of phase boundaries. In order to determine information about a certain phase of a material, the need for a method that offers an objective evaluation is necessary. This paper will introduce a cluster algorithm in the case of heterogeneous building materials (concrete) to separate the spectral information of non-relevant aggregates and cement matrix. In civil engineering, the information about the quantitative ingress of harmful species like Cl−, Na+ and SO2−4 is of great interest in the evaluation of the remaining lifetime of structures (Millar et al., 2015; Wilsch et al., 2005). These species trigger different damage processes such as the alkali-silica reaction (ASR) or the chloride-induced corrosion of the reinforcement. Therefore, a discrimination between the different phases, mainly cement matrix and aggregates, is highly important (Weritz et al., 2006). For the 2D evaluation, the expectation-maximizationalgorithm (EM algorithm; Ester and Sander, 2000) has been tested for the application presented in this work. The method has been introduced and different figures of merit have been presented according to recommendations given in Haddad et al. (2014). Advantages of this method will be highlighted. After phase separation, non-relevant information can be excluded and only the wanted phase displayed. Using a set of samples with known and unknown composition, the EM-clustering method has been validated regarding to Gustavo González and Ángeles Herrador (2007).
Alkali-silica reaction (ASR) is a chemical reaction within concrete which can lead over time to cracking and spalling. Due to the complexity of the problem, it still causes damage to concrete constructions worldwide.
The publication aims to illustrate the interdisciplinary research of the German Federal Institute for Materials Research and Testing (BAM) within the last 20 years, considering all aspects of ASR topics from the macro to the micro level. First, methods for characterization and assessment of ASR risks and reaction products used at BAM are explained and classified in the international context. Subsequently the added value of the research approach by combining different, preferably nondestructive, methods across all scales is explained using specific examples from a variety of research projects. Aspects covered range from the development of new test-setups to assess aggregate reactivity, to analysis of microstructure and reaction products using microscopical, spectroscopical and X-ray methods, to the development of a testing methodology for existing concrete pavements including in-depth analysis of the visual damage indicator and the de-icing salt input using innovative testing techniques. Finally, research regarding a novel avoidance strategy that makes use of internal hydrophobization of the concrete mix is presented.
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.
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.
Welcome to the 2nd International Conference on Advances in Cement and Concrete Technology in Africa (ACCTA 2016), January 27– 29, 2016, held at White Sands Hotel, Dar es Salaam, Tanzania.
The first ACCTA conference that took place in January 2013 in Johannesburg was a result of an African-European collaborative research project. Due to the success of this conference, it was announced that a triennial international conference is necessary, with the next conference scheduled to take place once again in Johannesburg. Within the organisation of the conference, unfortunately some unforeseeable events arose, which would lead to either a delay of the conference in Johannesburg until 2018 or a change of venue. The great response from the international scientific community supported the option to maintain the originally scheduled date. With the support of the local organisation committee from the University of Dar es Salaam and the contributions from the University of the Witwatersrand and the University of Zagreb the conference was shifted to Dar es Salaam.
Despite the new boundary framework, we are extremely happy that it was possible to arrange an outstanding and excellent scientific programme. Therefore we would like to thank in particular the keynote speakers and all members of the international scientific community, as well as other delegates that supported the conference by their contributions and attendance. This shows us how significantly important the African cement and concrete market is for the entire global community.
Africa can become a spearhead for the future of construction with cement and concrete. The continent exhibits an enormous construction potential and due to the relatively short history of building with these materials, innovations can be adopted and adapted unbiased and without influence of stakeholders, traditions, and complicated networks of regulations. This is a fertile ground for the existing promising generation of engineers and decision makers for re-inventing cement and concrete in the best possible way.
There is no global optimum solution for concrete. The best solution in Africa is not the best solution in Europe or another part of the world, and the best solution in one particular African country is diverging from the best solution in another African country depending upon resources, supply chains, infrastructure, construction needs, traditions, available manpower, skills and technologies. Nevertheless, we can globally support our objectives to build future oriented and sustainable construction solutions by mutually learning from each other. In order to tackle the future challenges and build more sustainably and innovatively with concrete, we need to enhance interdisciplinary and cross-national skills and create networks between experts and decision makers globally.
ACCTA offers this kind of platform, and we are happy to announce that the conference reaches a high impact in the world. Delegates and speakers come from more than 40 countries in the world originating from all continents. Besides the technical content there will be plenary discussions on the most relevant topics of future binder technologies and standards and product safety with outstanding expert panellists.
We want to wish all delegates a successful conference and hope that this book can be a significant contribution for a future oriented and better concrete technology; in Africa and the entire world. Welcome to Dar es Salaam, Tanzania.
A significant number of German concrete motorway pavements have shown damage only a few years after construction. The alkali-silica-reaction (ASR) is often one of the reasons for this damage. German guidelines and regulations focus on the optimisation of the concrete composition to avoid damage due to ASR. Moreover, diverse research projects have dealt with the development and optimisation of ASR performance test methods with and without external alkali supply.
However, the influence of other parameters on the occurrence and intensity of a damaging ASR had not yet been taken into account. Such parameters include, e.g., insufficient curing and the modifications of concrete’s porosity due to the use of slip form pavers. Likewise, the increased traffic loading had not yet been considered. The Federal Institute for Materials Research and Testing (BAM) assesses these parameters and processes in a number of projects. These projects aim primarily to increase the durability of the concrete pavements, in particular by improving preventive measures that may be taken before or after the construction of concrete pavements. This paper gives a short overview of BAM’s projects concerning ASR in concrete pavements. Furthermore, results regarding the influence of the cyclic traffic loading on ASR are presented.
Amplitudes variation of GPR rebar reflection due to the influence of concrete aggregate scattering
(2015)
Dense GPR measurements of rebar reflection amplitudes Show relative variations, which can be in the order of more than 10% - 20%. Former investigations demonstrated that these variations are caused by the heterogeneity of concrete, i.e. due to the inclusion of aggregates in concrete. These amplitude variations make it difficult to analyse single reflection amplitudes in order to determine the rebar diameter or to estimate the concrete deterioration state. In a systematic study we have quantified the statistical variation of the rebar reflection amplitude for concrete covers of 6 cm, 9 cm, 12 cm, 15 cm and 18 cm, for two different grading curves and for the rebar diameters 12 mm and 28 mm. Also the influence of the wavelength has been investigated by using antennas with different centre frequencies in relation to the aggregate size. The results are discussed with regard to a quantitative amplitude evaluation of GPR measurements and also the potential of using these variations for a characterization of concrete material properties.
In this talk the basics of X-ray computed tomography (XCT) are presented, together with a description of complementary techniques such as Laminography and Stereoradiography.
A overview of the common reconstruction approach and of the artifacts that can occur during reconstruction or acquisition of XCT images is also given.
Finally, application examples in the field of construction materials are given, whereby several experimental techniques (Region of Interest Approach) and data analysis methods (e.g. Digital volume correlation) are explained. Such techniques and algorithms are used to extract quantitative information from ex- and in-situ experiments.
Algal biofilm façades are an alternative to traditional green façades which can help to improve biodiversity and air quality within cities. They present a low maintenance approach in which subaerial algae are grown directly on concrete substrates. The intrinsic bioreceptivity of the substrate is a critical factor in successful facade colonisation. Existing research has identified several environmental and material properties which influence concrete bioreceptivity, however a consensus has yet to be made on which properties are most influential and how the interaction between properties may promote algal biofilm growth under specific conditions.