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This data article introduces a dataset comprising 1630 alkali-activated concrete (AAC) mixes, compiled from 106 literature sources. The dataset underwent extensive curation to address feature redundancy, transcription errors, and duplicate data, yielding refined data ready for further data-driven science in the field of AAC, where this effort constitutes a novelty. The carbon footprint associated with each material used in the AAC mixes, as well as the corresponding CO2 footprint of every mix, were approximated using two published articles. Serving as a foundation for future expansions and rigorous data applications, this dataset enables the characterization of AAC properties through machine learning algorithms or as a benchmark for performance comparison among different formulations. In summary, the dataset provides a resource for researchers focusing on AAC and related materials and offers insights into the environmental benefits of substituting traditional Portland concrete with AAC.
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.
Titanium and its alloys are known to allow the straightforward laser-based manufacturing of ordered surface nanostructures, so-called high spatial frequency laser-induced periodic surface structures (HSFL). These structures exhibit sub-100 nm spatial periods – far below the optical diffraction limit. The resulting surface functionalities are usually enabled by both, topographic and chemical alterations of the nanostructured surfaces. For exploring these effects, multi-method characterizations were performed here for HSFL processed on Ti–6Al–4V alloy upon irradiation with near-infrared ps-laser pulses (1030 nm, ≈1 ps pulse duration, 1–400 kHz) under different laser scan processing conditions, i.e., by systematically varying the pulse repetition frequency and the number of laser irradiation passes. The sample characterization involved morphological and topographical investigations by scanning electron microscopy (SEM), atomic force microscopy (AFM), tactile stylus profilometry, as well as near-surface chemical analyses hard X-ray photoelectron spectroscopy (HAXPES) and depth-profiling time-of-flight secondary ion mass spectrometry (ToF-SIMS). This provides a quantification of the laser ablation depth, the geometrical HSFL characteristics and enables new insights into the depth extent and the nature of the non-ablative laser-induced near-surface oxidation accompanying these nanostructures. This allows to answer the questions how the processing of HSFL can be industrially scaled up, and whether the latter is limited by heat-accumulation effects.
Although the use of noble metal catalysts can increase the efficiency of hydrogen evolution reaction, the process is still limited by the characteristics of the metal-hydrogen (M−H) bond, which can be too strong or too weak, depending on the metal employed. Studies revealed that the hydrogen affinity for the metal surface (i.e. H absorption/desorption) is regulated also by the potential at the metal nanoparticles. Through controlled periodic illumination (CPI) of a series of metal/TiO2 suspensions, here we demonstrated that an increase of the HER efficiency is possible for those photodeposited metals which have a Tafel slope below 125 mV. Two possible explanations are here reported, in both of them the M−H interaction and the metal covering level play a prominent role, which also depend on the prevailing HER mechanism (Volmer-Heyrovsky or Volmer-Tafel).
Even after autoclaving for 2 weeks in the temperature range of 120 to 200 °C, CEM I paste with a water-to-cement ratio of 0.5 still contains some low-crystalline C-S-H. The conversion of low-crystalline C-S-H to crystalline is faster with increasing temperature. The observed low-crystalline and crystalline C-S-H phases (reinhardbraunsite, jaffeite) indicate that the sampleshave not reached equilibrium yet under these experimental conditions. However, there is a good agreement between experiment and thermodynamic modelling for the other solids indicating that the used datasets are suitable for this application.
This report summarizes findings from the first comprehensive study on digitalization in conformity assessment in Africa. The reults are based on data from a survey among conformity assessment bodies (CABs) conducted in 2023. It highlights the digital maturity of the organizations, the motives, benefits and obstacles of digital transformation as well as the actual technology trends.
This study is part of a global project that covers various other countries (see www.qi-fokus.de).
AbstractIn this study, we present a screening method based on molecular absorption spectrometry to study PFAS uptake and fate in plants. To evaluate the suitability of this method we analyzed plant extracts with molecular absorption spectrometry (MAS) as well as liquid chromatography–tandem mass spectrometry (LC–MS/MS) for mass balance studies (w(F)). French bean plants (Phaseolus vulgaris) were grown on soil spiked using eight PFAS substances that vary in chain length and functional group composition. Specifically, these include three short-chained (C4–C5), five long-chained (C7–C10) carboxylic acids, one sulfonic acid and one sulfonic amide moieties. To investigate substance-specific PFAS uptake systematically, PFAS were spiked as single substance spike. Additionally, we studied one mixture of the investigated substances in equal proportions regarding w(F) and four PFAS mixtures of unknown composition. After 6 weeks, the plants were separated into four compartments. We analyzed the four compartments as well as the soil for extractable organically bound fluorine (EOF) by high resolution-continuum source-graphite furnace-molecular absorption spectrometry (HR-CS-GFMAS) as well as for sum of ten target-PFAS by LC–MS/MS. All three short-chained PFAS perfluorobutanoic acid (PFBA), perfluorobutanoic sulfonic acid (PFBS) and perfluoropentanoic acid (PFPeA) were determined in high concentrations mainly in the fruits of the investigated plants while long-chained PFAS perfluorononanoic acid (PFNA) and perfluorodecanoic acid (PFDA) were mainly determined in roots. PFBS was determined in remarkably high concentrations in leaves compartment by both quantification methods. Overall, comprehensive results of single substance spikes were in good agreement for both methods except for a few cases. Hence, two phenomena were identified: for mixed PFAS spikes of unknown composition huge differences between EOF and sum of target PFAS were observed with systematically higher EOF values. Overall, both methods indicate comparable results with MS being more reliable for known PFAS contamination and MAS being more valuable to identify PFAS exposure of unknown composition.
Graphical Abstract
The degradation of a single-site atomically dispersed, model Fe–N–C powder catalyst with high activity is investigated using cryo-Mössbauer spectroscopy. The results indicate a degradation initiated by an Fe2+ to Fe3+ oxidation due to coordination of oxygen to tetrapyrrolic Fe–N4 sites at atmospheric conditions (change between characteristic doublets) before iron(III) oxide is formed (sextet). Thermal reactivation can be used to restore substantial catalytic activity of aged Fe–N–C powders.
The lack of traceability to meter of X-ray Computed Tomography (CT) measurements still hinders a more extensive acceptance of CT in coordinate metrology and industry. To ensure traceable, reliable, and accurate measurements, the determination of the task-specific measurement uncertainty is necessary. The German guideline VDI/VDE 2630 part 2.1 describes a procedure to determine the measurement uncertainty for CT experimentally by conducting several repeated measurements with a calibrated test specimen. However, this experimental procedure is cost and effort intensive. Therefore, the simulation of dimensional measurement tasks conducted with X-ray computed tomography can close these drawbacks. Additionally, recent developments towards a resource and cost-efficient production (“smart factory”) motivate the need for a corresponding numerical model of a CT system (“digital twin”) as well. As there is no standardized procedure to determine the measurement uncertainty of a CT system by simulation at the moment, the project series CTSimU was initiated, aiming at this gap. Concretely, the goal is the development of a procedure to determine the measurement uncertainty numerically by radiographic simulation. The first project (2019-2022), "Radiographic Computed Tomography Simulation for Measurement Uncertainty Evaluation - CTSimU" developed a framework to qualify a radiographic simulation software concerning the correct simulation of physical laws and functionalities. The most important outcome was a draft for a new guideline VDI/VDE 2630 part 2.2, which is currently under discussion in the VDI/VDE committee. The follow-up project CTSimU2 "Realistic Simulation of real CT systems with a basic-qualified Simulation Software" will deal with building and characterizing a digital replica of a specific real-world CT system. The two main targets of this project will be a toolbox including methods and procedures to configure a realistic CT system simulation and to develop tests to check if this replica is sufficient enough. The result will be a draft for a follow-up VDI/VDE guideline proposing standardized procedures to determine a CT system's corresponding characteristics and test the simulation (copy) of a real-world CT system which we call a "digital twin".
We show that mechanochemically driven polymorphic transformations can require extremely long induction periods, which can be tuned from hours to days by changing ball milling energy. The robust design and interpretation of ball milling experiments must account for this unexpected kinetics that arises from energetic phenomena unique to the solid state. Detailed thermal analysis, combined with DFT simulations, indicates that these marked induction periods are associated with processes of mechanical activation. Correspondingly, we show that the pre‐activation of reagents can also lead to marked changes in the length of induction periods. Our findings demonstrate a new dimension for exerting control over polymorphic transformations in organic crystals. We expect mechanical activation to have a much broader implication across organic solid‐state mechanochemistry.