Laser-arc hybrid welding of wrought to selective laser molten stainless steel

Selective laser melting (SLM) is a successful tool-free powder additive technology. The success of this manufacturing process results from the possibility to create complex shape parts, with intrinsic engineered features and good mechanical properties. Joining SLM steel to similar or dissimilar steel can overcome some limitations of the product design like small dimension, undercut profile, and residual stress concentration. In this way, the range of applications of the SLM process can be broadened. In this paper, the hybrid laser welding of selective laser molten stainless steel was investigated. A high-power fiber laser was coupled to an electric arc and austenitic stainless steel wrought and SLM parts were welded together. The power and speed parameters were investigated. The joints were analyzed in terms of weld bead profile, microstructure, microhardness, and tensile test. The efficiency of the welding process was evaluated through the line energy input versus the weld molten area.     

Nano Ca(OH)2 synthesis using a cost‐effective and innovative method: Reactivity study

Ca(OH)₂ nanoparticles in hydro‐alcoholic dispersion (nanolime) are currently used for eco‐compatible treatments of carbonate‐based substrates in the field of Cultural Heritage conservation. Unfortunately, at present nanolime is synthesized by processes which present some drawbacks (considerable cost, multiple steps, low specific production yield), thus limiting the potential of its applications. We have developed a single‐step procedure, based on an ion exchange process, making it possible to produce pure and crystalline Ca(OH)₂ nanoparticles easily in water, at room temperature and ambient pressure, starting from cheap or renewable reactants. The simplicity of the process and its time‐ and energy‐saving aspects are very promising factors for extending the production from laboratory to industrial scale. The aim of this paper is to investigate the structural and morphological features of the nanoparticles produced and to analyze the influence of crucial parameters of the synthesis process (i.e., time, water usage, reagent concentration and reaction volume) on the nanoparticles’ characteristics. The nanolime produced is investigated by XRD, FTIR, TEM, and AFM techniques. The nanoparticle reactivity in the carbonation process is also investigated, by varying the suspension concentration, the solvent and relative humidity conditions. Pure, crystalline, and very reactive Ca(OH)₂ nanoparticles are obtained. The nanoparticles are constituted of thin lamellas, composed of primary hexagonal nanoparticles <10 nm, irrespective of time, water employed, reagents concentration, and reaction volume.     

Structural Upgrade Using Basalt Fibers for Concrete Confinement

This paper aims to appraise the opportunities provided by a new class of composites based on using basalt fibers bonded with a cement-based matrix as an innovative strengthening material for confinement of reinforced concrete members. The effectiveness of the proposed technique is assessed by comparing different confinement schemes on concrete cylinders: (1) uniaxial glass-fiber-reinforced polymer (FRP) laminates; (2) alkali-resistant fiberglass grids bonded with a cement-based mortar; (3) bidirectional basalt laminates preimpregnated with epoxy resin or latex and then bonded with a cement-based mortar; and (4) a cement-based mortar jacket. The study showed that confinement based on basalt fibers bonded with a cement-based mortar could be a promising solution to overcome some limitations of epoxy-based FRP laminates.     

Thermal stability of R-134a, R-141b, R-13I1, R-7146, R-125 associated with stainless steel as a containing material

An experimental apparatus for assessing the thermal stability threshold of refrigerant working fluids is described and results for R-134a (1,1,1,2-tetrafluoroethane), R141b (1,1-dichloro-1-fluoroethane), R-13I1 (trifluoromethyl iodide), R-7146 (sulphur hexafluoride), R-125 (pentafluoroethane) are presented. The information is a concern for the design of refrigeration systems, high temperature heat pumps and Organic Rankine Cycles (ORC), for which the above refrigerants are proposed. The method aims to identify a maximum temperature for plant operation in contact with stainless steel and involves the evaluation of four indicators: (1) pressure variation while the fluid is maintained at set temperature; (2) saturation pressure comparison after heat treatment; (3) chemical analysis; and (4) vessel visual inspection after the test session. The highest temperatures at which no evident degradation occured are: 368°C for R-134a; 102°C for R-13I1; 90°C for R-141b; 204°C for R-7146; and 396°C for R-125.     

A sensitivity-enhanced field-effect chiral sensor

Organic thin-film transistor sensors have been recently attracting the attention of the plastic electronics community for their potential exploitation in novel sensing platforms. Specificity and sensitivity are however still open issues: in this respect chiral discrimination-being a scientific and technological achievement in itself--is indeed one of the most challenging sensor bench-tests. So far, conducting-polymer solid-state chiral detection has been carried out at part-per-thousand concentration levels. Here, a novel chiral bilayer organic thin-film transistor gas sensor--comprising an outermost layer with built-in enantioselective properties-is demonstrated to show field-effect amplified sensitivity that enables differential detection of optical isomers in the tens-of-parts-per-million concentration range. The ad-hoc-designed organic semiconductor endowed with chiral side groups, the bilayer structure and the thin-film transistor transducer provide a significant step forward in the development of a high-performance and versatile sensing platform compatible with flexible organic electronic technologies.     

Evaluation of a machine learning classifier for metamodels

Modeling is a ubiquitous activity in the process of software development. In recent years, such an activity has reached a high degree of intricacy, guided by the heterogeneity of the components, data sources, and tasks. The democratized use of models has led to the necessity for suitable machinery for mining modeling repositories. Among others, the classification of metamodels into independent categories facilitates personalized searches by boosting the visibility of metamodels. Nevertheless, the manual classification of metamodels is not only a tedious but also an error-prone task. According to our observation, misclassification is the norm which leads to a reduction in reachability as well as reusability of metamodels. Handling such complexity requires suitable tooling to leverage raw data into practical knowledge that can help modelers with their daily tasks. In our previous work, we proposed AURORA as a machine learning classifier for metamodel repositories. In this paper, we present a thorough evaluation of the system by taking into consideration different settings as well as evaluation metrics. More importantly, we improve the original AURORA tool by changing its internal design. Experimental results demonstrate that the proposed amendment is beneficial to the classification of metamodels. We also compared our approach with two baseline algorithms, namely gradient boosted decision tree and support vector machines. Eventually, we see that AURORA outperforms the baselines with respect to various quality metrics.

     

Simplicity as a Route to Impact in Materials Research

Materials scientists and engineers desire to have an impact. In this Progress Report we postulate a close correlation between impact – whether academic, technological, or scientific – and simple solutions, here defined as solutions that are inexpensive, reliable, predictable, highly performing, “stackable” (i.e., they can be combined and compounded with little increase in complexity), and “hackable” (i.e., they can be easily modified and optimized). In light of examples and our own experience, we propose how impact can be pursued systematically in materials research through a simplicity‐driven approach to discovery‐driven or problem‐driven research.