Antonios Hatziapostolou

Methanol has been identified as a transition fuel for the decarbonisation of combustion-based industries, including automotive and maritime. This study aims to conduct a critical review of methanol combustion in compression ignition engines and analyse the reviewed studies’ results to quantify methanol use’s impact on engine performance and emissions characteristics. The diesel and diesel–methanol operation of these engines are comparatively assessed, demonstrating the trade-offs between the methanol fraction, the key engine performance parameters, including brake thermal efficiency, peak in-cylinder pressure, heat release rate, and temperature, as well as the carbon dioxide, carbon monoxide, nitrogen oxides, and particulate matter emissions. The types of the reviewed engines considering the main two combustion methods, namely premixed and diffusion combustion, are discussed. Research gaps are identified, and recommendations for future research directions to address existing challenges for the wider use of methanol as a marine fuel are provided. This comprehensive review provides insights supporting methanol engine operation, and it is expected to lead to further studies towards more efficient use of methanol-fueled marine engines.

Bioprinting offers great potential for the fabrication of three-dimensional living tissues by the precise layer-by-layer printing of biological materials, including living cells and cell-laden hydrogels. The laser-induced forward transfer (LIFT) of cell-laden bioinks is one of the most promising laser-printing technologies enabling biofabrication. However, for it to be a viable bioprinting technology, bioink printability must be carefully examined. In this study, we used a time-resolved imaging system to study the cell-laden bioink droplet formation process in terms of the droplet size, velocity, and traveling distance. For this purpose, the bioinks were prepared using breast cancer cells with different cell concentrations to evaluate the effect of the cell concentration on the droplet formation process and the survival of the cells after printing. These bioinks were compared with cell-free bioinks under the same printing conditions to understand the effect of the particle physical properties on the droplet formation procedure. The morphology of the printed droplets indicated that it is possible to print uniform droplets for a wide range of cell concentrations. Overall, it is concluded that the laser fluence and the distance of the donor–receiver substrates play an important role in the printing impingement type; consequently, a careful adjustment of these parameters can lead to high-quality printing.

The flow through a forced circulation Z-type flat plate solar collector was investigated by means of combined experimental measurements and numerical simulations. The efficient operation of such collectors depends on the uniformity of the flow rate distribution among their riser tubes, while low pumping power demand is also sought. Mass flow rate measurements in the riser tubes were performed, utilizing a specially adapted ultrasound instrument for various values of total flow rates in the collector. By means of a commercial Computational Fluid Dynamics (CFD) code, laminar and turbulent flow models in different computational grids were tested and validated against the experiments. Appropriate metrics were introduced to quantify flow rate distribution non-uniformity among the risers, and pressure drop through the manifold was calculated. Parametric studies for flow conditions outside the experimental window were performed utilizing the CFD method in order to assess the effect of the Reynolds number in the flow distribution among the riser tubes. Furthermore, aiming to enhance flow rate uniformity, a methodology based on modifying the diameter of each riser tube was applied and successfully demonstrated. The proposed method can be employed in large solar collector arrays, either as stand-alone systems or as belonging to hybrid alternative sources of energy (ASE) systems, aiming to optimize their overall efficiency.

The increasing development of flexible and printed electronics has fueled substantial advancements in selective laser sintering, which has been attracting interest over the past decade. Laser sintering of metal nanoparticle dispersions in particular (from low viscous inks to high viscous pastes) offers significant advantages with respect to more conventional thermal sintering or curing techniques. Apart from the obvious lateral selectivity, the use of short-pulsed and high repetition rate lasers minimizes the heat affected zone and offers unparalleled control over a digital process, enabling the processing of stacked and pre-structured layers on very sensitive polymeric substrates. In this work, the authors have conducted a systematic investigation of the laser sintering of micro-patterns comprising Ag nanoparticle high viscous inks: The effect of laser pulse width within the range of 20–200 nanoseconds (ns), a regime which many commercially available, high repetition rate lasers operate in, has been thoroughly investigated experimentally in order to define the optimal processing parameters for the fabrication of highly conductive Ag patterns on polymeric substrates. The in-depth temperature profiles resulting from the effect of laser pulses of varying pulse widths have been calculated using a numerical model relying on the finite element method, which has been fed with physical parameters extracted from optical and structural characterization. Electrical characterization of the resulting sintered micro-patterns has been benchmarked against the calculated temperature profiles, so that the resistivity can be associated with the maximal temperature value. This quantitative correlation offers the possibility to predict the optimal process window in future laser sintering experiments. The reported computational and experimental findings will foster the wider adoption of laser micro-sintering technology for laboratory and industrial use.

Ag nanowire (NW) networks have exquisite optical and electrical properties which make them ideal candidate materials for flexible transparent conductive electrodes. Despite the compatibility of Ag NW networks with laser processing, few demonstrations of laser fabricated Ag NW based components currently exist. In this work, we report on a novel single step laser transferring and laser curing process of micrometer sized pixels of Ag NW networks on flexible substrates. This process relies on the selective laser heating of the Ag NWs induced by the laser pulse energy and the subsequent localized melting of the polymeric substrate. We demonstrate that a single laser pulse can induce both transfer and curing of the Ag NW network. The feasibility of the process is confirmed experimentally and validated by Finite Element Analysis simulations, which indicate that selective heating is carried out within a submicron-sized heat affected zone. The resulting structures can be utilized as fully functional flexible transparent electrodes with figures of merit even higher than 100. Low sheet resistance (90%) make the reported process highly desirable for a variety of applications, including selective heating or annealing of nanocomposite materials and laser processing of nanostructured materials on a large variety of optically transparent substrates, such as Polydimethylsiloxane (PDMS).

In computer-assisted education, the continuous monitoring and assessment of the learner is crucial for the delivery of personalized education to be effective. In this paper, we present a pilot application of the Student Diagnosis, Assistance, Evaluation System based on Artificial Intelligence (StuDiAsE), an open learning system for unattended student diagnosis, assistance and evaluation based on artificial intelligence. The system demonstrated in this paper has been designed with engineering students in mind and is capable of monitoring their comprehension, assessing their prior knowledge, building individual learner profiles, providing personalized assistance and, finally, evaluating a learner's performance both quantitatively and qualitatively by means of artificial intelligence techniques. The architecture and user interface of the system are being exhibited, the results and feedback received from a pilot application of the system within a theoretical engineering course are being demonstrated and the outcomes are being discussed.

Homogeneous charge compression ignition (HCCI) combustion encompasses the advantages of both diesel and gasoline fuel engines. However, shortcomings mainly associated with the rapid pressure rise rate need to be studied in detail and account for the inherencies of each fuel mixture. The work numerically investigates the effect of key operating parameters on performance and pollutant characteristics on a widely investigated research engine. An accredited, detailed chemical kinetic mechanism for gasoline surrogate components, coupled with a NOx sub-mechanism, is implemented on a commercial 0D single-zone engine model, in order to identify optimum performance guidelines regarding operating parameters using typical primary reference fuels. The effect of operated fuels, intake charge and exhaust gas recirculation (EGR) levels are discussed based on pressure traces, heat release rate profiles, combustion phasing analyses, and in-cylinder speciation and kinetic information. The work also explores the app...

Monitoring and evaluating engineering learners through computer-based laboratory exercises is a difficult task, especially under classroom conditions. A complete diagnosis requires the capability to assess both the competence of the learner to use the scientific software and the understanding of the theoretical principles. This monitoring and evaluation needs to be continuous, unobtrusive and personalized in order to be effective. This study presents the results of the pilot application of an eLearning environment developed specifically with engineering learners in mind. As its name suggests, the Learner Diagnosis, Assistance, and Evaluation System based on Artificial Intelligence (StuDiAsE) is an Open Learning Environment that can perform unattended diagnostic, evaluation and feedback tasks based on both quantitative and qualitative parameters. The base architecture of the system, the user interface and its effect on the performance of postgraduate engineering learners are being presented.