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A liquid marble is a liquid droplet coated usually with hydrophobic particles that can hold a very small liquid volume without wetting the adjacent surface. This combination gives rise to a set of unique properties such as resistance to contamination, low-friction mobility and flexible manipulation, making them appealing for a myriad of engineering applications including miniature reactors, gas sensing and drug delivery. Despite numerous experimental studies, numerical modelling investigations of liquid marbles are currently underrepresented in the literature, although such investigations can lead to a better understanding of their overall behaviour while overcoming the use of cost- and time-intensive experimental-only procedures. This paper therefore evaluates the capabilities of three well-established and widely-used particle-based numerical frameworks, namely Smoothed Particle Hydrodynamics (SPH)-based approaches, Coarse-Grained (CG)-based approaches and Lattice Boltzmann Method (LBM)-based approaches, to investigate liquid-marble properties and their key applications. Through a comprehensive review of recent advancements, it reveals that these numerical approaches demonstrate promising capabilities of simulating complex multiphysical phenomena involved with liquid-marble systems such as their floatation, coalescence and surface-tension-surface-area relationship. The paper further elaborates on the perspective that benefiting from particle-based numerical and computational techniques, liquid marbles can become an even more effective and exciting platform for many cutting-edge large-scale engineering applications.

In this paper, we have developed a linear stability analysis to predict the formation of necking instabilities in porous ductile plates subjected to dynamic biaxial stretching. The mechanical behavior of the material is described with the Gurson–Tvergaard–Needleman constitutive relation for progressively cavitating solids (Gurson 1977; Tvergaard 1981, 1982; Tvergaard and Needleman 1984) which considers the voids to be spherical and the matrix material isotropic with yielding defined by the von Mises (1928) criterion. The analytical model is formulated in a two-dimensional framework in which the multiaxial stress state that develops inside the necked region is approximated with the Bridgman (1952) correction factor, superimposing a hydrostatic stress state to the uniform stress field that develops in the plate before localization. As opposed to the linear stability models published so far to model dynamic necking in ductile plates, which consider the material to be fully dense and incompressible, the approach developed in this paper provides new insights into the interplay between porosity and inertia on plastic localization. In addition, the predictions of the theoretical model for the critical strain leading to necking formation have been compared with unit-cell finite element calculations performed in ABAQUS/Explicit (2019). Satisfactory quantitative and qualitative agreement has been found between the theoretical and the computational approach for loading paths ranging from plane strain tension to nearly equibiaxial tension, loading rates varying from 100 to $$10{,}000~\text {s}^{-1}$$ , and different values of the initial void volume fraction ranging from 0.01 to 0.1. Both analytical and finite element results suggest that the influence of porosity on necking localization increases, due to voids coalescence, as the loading rate increases and the loading path approaches equibiaxial tension. The original formulation developed in this paper serves as a basis for analytically modeling the dynamic formability of porous ductile plates, and it can be readily extended to consider more complex porous plasticity theories, e.g. constitutive models which consider the anisotropy of the material (Benzerga and Besson 2001) and/or voids with different shapes (Gologanu et al. 1993; Monchiet et al. 2008).

This paper introduces ROmodel, an open source Python package extending the modeling capabilities of the algebraic modeling language Pyomo to robust optimization problems. ROmodel helps practitioners transition from deterministic to robust optimization through modeling objects which allow formulating robust models in close analogy to their mathematical formulation. ROmodel contains a library of commonly used uncertainty sets which can be generated using their matrix representations, but it also allows users to define custom uncertainty sets using Pyomo constraints. ROmodel supports adjustable variables via linear decision rules. The resulting models can be solved using ROmodels solvers which implement both the robust reformulation and cutting plane approach. ROmodel is a platform to implement and compare custom uncertainty sets and reformulations. We demonstrate ROmodel’s capabilities by applying it to six case studies. We implement custom uncertainty sets based on (warped) Gaussian processes to show how ROmodel can integrate data-driven models with optimization.

In light of the potential long-term societal and economic benefits of novel nano-enabled products, there is an evident need for research and development to focus on closing the gap in nano-materials (NMs) safety. Concurrent reflection on the impact of decision-making tools, which may lack the capability to assist sophisticated judgements around the risks and benefits of the introduction of novel products (or pilot production lines), is essential. This paper addresses the potential for extant decision support tools to default to a precautionary principle position in the face of uncertainty. A more utilitarian-based approach could be facilitated by adding simple methods to formulate realistic hypotheses, which would assist non-specialists to make more nuanced decisions in terms of managing the risks of introducing new NMs. A decision support analytical framework is applied to identify the potential risks and benefits of novel nano-enabled products such as textiles with in-built enhanced antimicrobial activity for the prevention of nosocomial infections produced by spray or sonochemical coating possesses. While the results demonstrate valuable societal and environmental benefits compared to conventional products, due to uncertainty regarding the possible hazard to humans, sizable risks were identified in some cases due to the precautionary principle.

Nowadays, the role of hybridization within the wider manufacturing ecosystem gains significant momentum with multiple commercial solutions already available on the market. Despite the very promising benefits of combining and selectively exploiting the advantages of additive and subtractive technologies on the same machine, hybrid additive manufacturing is far from reaching its full potential. One of the central limitations of existing hybrid process chains is the lack of a harmonized, structured and automated workflows to support an adaptive manufacturing strategy. This work is motivated by the need to bridge this gap and to capture the logic behind an adaptive hybrid process chain with the aim to support the achievement of enhanced product quality and improved operational efficiency in hybrid additive manufacturing. The paper discusses the implementation of a hybrid CAx platform and the underlying methodology aiming at the dynamic reduction of variabilities associated with the laser metal deposition process. The hybrid workflow identifies the most adapted sequence and planning of additive and subtractive operations while considering part inspection as an in-envelope functionality to quantify the geometrical and dimensional part deviations and to trigger the regenerative mechanism. The methodology is demonstrated on a hybrid machine by deploying laser ablation for the in situ removal of build deviations and an adapted deposition operation as part of a regenerative strategy leading to higher part confidence.

International audience; Variable filters are key components for compact spectral imagers. In this paper, we present a method for the fabrication of linearly variable filters based on Bühler HELIOS machine (plasma assisted reactive magnetron sputtering). These filters are obtained by producing a variation of the thickness of all the layers of the coating, using adapted masks placed in between the sputtering targets for the low and high refractive index materials and the substrates. Variable band pass filter from 550 nm up to 1000 nm is demonstrated.

This paper develops a modeling approach for the simulation of thermal contacts delimited by curvilinear edges. The study introduces a correction for semi-analytical methods based on the half-space assumption to account for thermal boundary conditions. The approach establishes a correction radius to control the heat flux and adjusts the corrective heat load to handle the thermoelastic normal stress on free surfaces. Compared to finite element analysis (FEA), the displacement calculated with the approach demonstrates a 99% improvement. A comparison of the complete thermal modification and normal stress elimination with FEA for a thermal contact shows more than 73% improvement, leading to an error margin of under 5%. The calculation burden is also drastically reduced as compared to that of an FEA.

One of the greatest environmental goals for the aluminum alloys industry is generating higher quality products by introducing cleaner input materials while maintaining low production costs. A typical dilemma for the master alloy producers is the cleanness level of the master alloy since insoluble inclusions could serve as inoculants during the solidification process. In this work, commercial Ti5B1 master alloy is used for grain refinement of Al7Si4Cu aluminum alloy and compared with the cleaned master alloy that contained a lower amount of residual refractory oxides and salts. Metallography analysis was used for grain size measurement while Computer Aided Cooling Curve Analysis was used for assessment of the undercooling and heat release values. In all instances, specimens treated with the cleaned master alloy showed smaller grains in the final structure and lower undercooling values. The difference in released heat between liquidus and recalescence temperatures was about 25% in specimens where added 0.66 wt% of cleaned master alloys compared to specimens where the commercial master alloys were added. Using cleaner Ti5B1 master alloy with a higher number of TiAl3 and TiB2 particles improves its grain refinement efficiency and transmits fewer impurities in produced parts. Producing cleaner master alloy would be beneficial from economic and environmental aspects by increasing its value and service time of produced parts besides simplifying the recycling process at the end of parts life-cycle. This is the peer reviewed version of the paper: Mitrašinović, A., Tomić, M., 2022. Functional and Environmental Advantage of Cleaning Ti5B1 Master Alloy, International Journal of Precision Engineering and Manufacturing-Green Technology, 9, 783–793 [https://doi.org/10.1007/s40684-021-00339-2] Peer-reviewed manuscript: [https://hdl.handle.net/21.15107/rcub_dais_11733]

On the long road towards low-cost flexible hybrid electronics, integration and printable solar energy harvesting solutions, there is an urgent need for high-performance transparent conductive electrodes produced using manufacturing-ready techniques and equipment. In recent years, randomly-distributed metallic nanowire-based transparent mesh electrodes have proven highly-promising as they offer a superb compromise between high performances and low fabrication costs. Unfortunately, these high figure-of-merit transparent mesh electrodes usually rely heavily on extensive post-deposition processing. While conventional thermal annealing yields good performances, it is especially ill-suited for deposition on low-temperature substrates or for high-throughput manufacturing solutions. Similarly, laser-induced annealing severely limits the processing time for electrodes covering large surfaces. In this paper, we report the fabrication of ultra high-performance silver nanowires-based transparent conductive electrodes fabricated using optimized manufacturing-ready ultrafast photonic curing solutions. Using conventional indium tin oxide (ITO) as our benchmark for transparent electrodes, we demonstrate a 2.6–2.7 $$\times $$ × performance gain using two different figure-of-merit indicators. Based on these results, we believe this research provides an ideal manufacturing-ready approach for the large-scale and low-cost fabrication of ultra high-performance transparent electrodes for flexible hybrid electronics and solar-energy harvesting applications.