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- A 3D MOF with Cu20/Cu6 clusters: self-assembly, CO2 encapsulation, structural features, and magnetic propertiesPublication . Sliwa, Ewelina I.; Nesterov, Dmytro S.; Klak, Julia; Kirillov, Alexander M.; Smolenski, PiotrAbstract Molecular design of multicopper clusters has been of increasing importance in inorganic chemistry, biomedical science, and functional materials. Herein, two new copper compounds were self-assembled from copper(II) monofluoroacetate or trifluoroacetate, elemental copper, and 1,3,5-triaza-7-phosphaadamantane (PTA). The reaction starting from copper(II) monofluoroacetate yielded a tetranuclear cluster, [Cu4II(μ3-OH)2(μ-L)6(PTA=O)2] (1), where L is monofluoroacetate(1−) and PTA=O is the oxide of PTA. Formation of 1 involves the oxidation of PTA and the incorporation of μ3-OH– ligands. In contrast, a similar reaction with copper(II) trifluoroacetate produced a unique three-dimensional metal–organic framework (3D MOF), formulated as [{Cu20II(CO3)(μ3-O)2(μ3-OH)22(μ-L′)12}{Cu6I(μ3-PTA)6(CH3CN)12}]n·6n(L′)·3n(H2O)·2n(CH3CN) (2), where L′ is trifluoroacetate. It comprises Cu20 clusters, with an encapsulated carbonate anion fixed from atmospheric CO2, which are bridged by {Cu6I(PTA)6} units into a 3D MOF. Control experiments confirmed that carbonate originates from ambient CO2 rather than from added carbonate salts. Both 1 and 2 were fully characterized, and their magnetic properties were investigated, revealing dominant antiferromagnetic interactions within the Cu4 and Cu20 clusters, respectively. Density functional theory (DFT) calculations confirmed the antiferromagnetic ground spin state of 1 and disclosed the stability of the Cu20 core in 2. This work highlights the influence of fluorinated carboxylates and atmospheric conditions on the assembly and architecture of multicopper clusters, and extends their family to new examples.
- a-fractal function with variable parameters: an explicit representationPublication . Priyanka, T. M. C.; Serpa, Cristina; Gowrisankar, A.In this paper, new results on the alpha-fractal function with variable parameters are presented. The Weyl-Marchaud variable order fractional derivative of an alpha-fractal function with variable parameters is examined by imposing certain conditions on the scaling factors. Following the investigation of fractional derivative, the definite integral of the alpha-fractal function with variable parameters is evaluated for various intervals in the prescribed domain. Finally, an explicit structure for the alpha-fractal function is provided using the base q representation of numbers.
- Adenine tagged Mn-based coordination polymer for conversion of carbon dioxide to cyclic carbonates under atmospheric pressurePublication . Eskemech, Alehegn; Bhakhar, Rubi; Biswas, Pritam; Karmakar, Anirban; Krishnan, Venkata; Koner, Rik RaniAbstract Natural processes collectively balance the global carbon cycle, effectively controlling atmospheric carbon dioxide (CO2) levels. However, excessive CO2 emissions due to industrialization and population growth have disrupted natural processes by increasing the atmospheric CO2 concentration. To address this issue, CO2 capture and conversion have been implemented. Metal–organic frameworks (MOFs)/coordination polymers (CPs) with bioligands, such as amino acids and nucleobases, are receiving much interest. However, bio-MOFs are not much reported due to the lack of control over their coordination with metal ions. In this work, we have developed an adenine-tagged Mn-CP with dominant basic sites, [Mn(IPT2–)(Ade)(DMF)]n (IPT2– = isophthalate; Ade = adenine; DMF = N,N′-dimethylformamide). The analysis of isosteric heat (Qst) of CO2 adsorption supported the presence of strong interactions between CO2 and Mn-CP. Mn-CP demonstrated moderate to outstanding performance in coupling CO2 with smaller and larger epoxides at ambient pressure under neat conditions. The thermodynamic activation parameters indicate that Mn-CP operates through an associative mechanism (ΔS⧧ = −283.4 J mol−1 K−1), with a reduced kinetic barrier characterized by ΔH⧧ of 17.28 kJ mol–1 and Ea of 20.5 kJ mol–1. The catalytic efficiency of Mn-CP was particularly notable in the coupling reaction of epichlorohydrin and CO2, yielding 92% of the corresponding cyclic carbonate under atmospheric pressure.
- Analysis of integrated calcium looping alternatives in a cement plantPublication . Amorim, Ana; Filipe, Rui; Matos, Henrique A.Calcium looping is a promising post-combustion CO2 capturing technology, highly compatible with the cement industry, one of the major industrial sources of CO2 emissions. Limestone, a raw material for clinker, forms lime, a calcium looping adsorbent. Thus, it is possible to maximize the synergies between a cement plant and a calcium looping unit by establishing an integrated configuration. Nevertheless, the integration of calcium looping in cement plants has not yet been thoroughly studied. This study examines different integration alternatives, developing models for the preheater and calciner using Aspen Plus, validated with operational data, alongside an entrained-flow carbonator model considering adsorbent deactivation. By combining these models, six integrated configurations are proposed and compared with the tail-end calcium looping configuration. The integrated configurations show a reduction in fuel consumption and net energy consumption for the same CO2 avoided emissions. The most promising configuration was identified and a comparative techno-economic analysis was conducted.
- Anti-hypercholesterolemia effects of edible seaweed extracts and metabolomic changes in Hep-G2 and Caco-2 cell linesPublication . Coelho, Mariana; Pacheco, RitaHypercholesterolemia is a major risk for the development of cardiovascular diseases (CVDs), the main cause of mortality worldwide, and it is characterized by high levels of circulating cholesterol. The drugs currently available for hypercholesterolemia control have several side effects, so it is necessary to develop new effective and safer therapies. Seaweeds serve as sources of several bioactive compounds with claimed beneficial effects. Eisenia bicyclis (Aramé) and Porphyra tenera (Nori) are edible seaweeds that were previously recognized as rich in bioactive compounds. In the present study, we aim to evaluate the anti-hypercholesterolemia effect of these two seaweed extracts and their health potential. Both extracts, but more efficiently Aramé extract, have liver 3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGR) inhibitory activity as well as the capability to reduce approximately 30% of cholesterol permeation through human Caco-2 cells by simulating the intestinal lining, which is a target for hypercholesterolemia treatments. An untargeted metabolomic assay on human intestinal Caco-2 and liver Hep-G2 cell lines exposed to Aramé and Nori extracts revealed changes in the cells’ metabolism, indicating the extracts’ health beneficial effects. The metabolic pathways affected by exposure to both extracts were associated with lipid metabolism, such as phospholipids, and fatty acid metabolism, amino acid pathways, cofactors, vitamins, and cellular respiration metabolism. The effects were more profound in Aramé-treated cells, but they were also observed in Nori-exposed cells. The metabolite modifications were associated with the protection against CVDs and other diseases and to the improvement of the cells’ oxidative stress tolerance. The results obtained for the anti-hypercholesterolemia properties, in addition to the revelation of the positive impact on cell metabolism, offer an important contribution for further evaluation of these seaweed extracts as functional foods or for CVD prevention.
- Ardosia: simulating circuits and robotic systems in a platformPublication . Marnoto de Oliveira Campos, Francisco MateusCircuit simulation, together with practical sessions, is considered a fundamental tool to assist in the teaching of electronics. Robotics offers rich real-world applications that foster student interest in developing engineering projects. Despite the potential benefits of uniting these two realities, software tools that combine circuits and robotic systems in a single simulation platform are scarce. This article presents Ardosia, a simulation software that combines electronics and robotics in a single simulation arena. The electronic aspects of the simulation are handled by the Falstad Circuit Simulator, a software with proven success in promoting student interest and learning outcomes. Importantly, this software features significant interactive and visualization characteristics that are deemed valuable to enhance conceptual understanding. Non-electrical physics simulation is performed by a special-purpose engine, designed to simulate sensor and actuator behavior in a 2-D world. In combination, the two simulation engines yield a model where electronic circuits are embodied in the world through robot sensors and actuators interacting together and with the surroundings. Such a simulator is intended to promote the use of robotics projects in electronics education, since students will be equipped with software to conveniently design and evaluate robotic systems, through simulation, before applying their ideas in an experimental setting. This article presents an overview of Ardosia, complemented with examples of use in electronics education and a validation experiment comparing simulation with real-world data.
- Assessing machine learning techniques for intrusion detection in cyber-physical systemsPublication . Santos, Vinicius F.; Albuquerque, Célio; Passos, Diego; Ereno Quincozes, Silvio; Mossé, DanielCyber-physical systems (CPS) are vital to key infrastructures such as Smart Grids and water treatment, and are increasingly vulnerable to a broad spectrum of evolving attacks. Whereas traditional security mechanisms, such as encryption and firewalls, are often inadequate for CPS architectures, the implementation of Intrusion Detection Systems (IDS) tailored for CPS has become an essential strategy for securing them. In this context, it is worth noting the difference between traditional offline Machine Learning (ML) techniques and understanding how they perform under different IDS applications. To answer these questions, this article presents a novel comparison of five offline and three online ML algorithms for intrusion detection using seven CPS-specific datasets, revealing that offline ML is superior when attack signatures are present without time constraints, while online techniques offer a quicker response to new attacks. The findings provide a pathway for enhancing CPS security through a balanced and effective combination of ML techniques.
- Assessment of decarbonization scenarios for the portuguese road sectorPublication . Salvador, João; Duarte, Gonçalo; Baptista, Patrícia C.Abstract This study presents a scenario-based modeling framework to evaluate potential decarbonization pathways for Portugal’s road transport sector. The model simulates the evolution of a light-duty vehicle (LDV) fleet under varying degrees of electrification and biofuel integration, accounting for energy consumption, CO2 emissions and market shares of alternative propulsion technologies. Coupled with projected energy mix trajectories, the framework estimates final energy demand and well-to-wheel (WTW) emissions for each scenario, benchmarking outcomes against national and European climate targets. A key structural limitation identified is the long vehicle survival rate—averaging 14 years—which constrains fleet renewal and delays the transition to full electrification. Diesel-powered light commercial vehicles exhibit even slower replacement dynamics, rendering the Portuguese targets of full electrification by 2030 highly improbable without targeted scrappage and incentive programs. Scenario analysis indicates that even with accelerated electric vehicle (EV) uptake, battery electric vehicles (BEVs) would comprise only 12% of the fleet by 2030 and 77% by 2050. Electrification scenario raises electricity demand fortyfold by 2050, stressing generation and infrastructure. Scenarios that consider diversification of energy sources reduce this strain but require triple electricity for large-scale green hydrogen and synthetic fuel production.
- Assessment of influential operational parameters in the mitigation of CO2 emissions in a power plant: case study in PortugalPublication . Balanuta, Vítor; Baptista, Patricia; Neves da Fonseca Cardoso Carreira, Fernando Paulo; Duarte, Gonçalo; Casaca, Cláudia Sofia Séneca da LuzThe European decarbonization goals and requirement for energy independence are mostly relying on intermittent renewable energy sources for electrification. A numerical model was developed to simulate the operation of a steam generator, allowing a study of the potential impacts of retrofitting existing coal-fired power plants to operate with biomass or coal–biomass mixtures on combustion parameters and CO2 emissions. The results obtained using the operational parameters of the Sines power plant indicate that a mixture of 25% coal and 75% pine sawdust allow operation at λ = 1.8, demonstrating that a small amount of coal allows operation near the coal combustion parameters (λ = 1.9). These conditions have the drawback of a reduction of 8.7% in adiabatic flame temperature but a significant reduction of 57.5% in CO2 emissions, considering the biomass as carbon-neutral.
- Automatic completion of data gaps applied to a system of water pumpsPublication . Enguiça, Ricardo; Soares, FilipaWe consider a time series with real data from a water lift station, equipped with three water pumps which are activated and deactivated depending on certain starting and halting thresholds. Given the water level and the number of active pumps, both read every 5 min, we aim to infer when each pump was activated or deactivated. To do so, we build an algorithm that sets a hierarchy of criteria based on the past and future of a given interval to identify which thresholds have been crossed during that interval. We then fill the gaps between the 5 min time steps, modeling the water level continuously with a piecewise linear function. This filling takes into account not only every water level reading and every previously identified change of status, but also the fact that activation and deactivation of a pump has no immediate effect on water level. This allows for the fulfillment of the ultimate objective of the problem in its real context, which is to provide the water management company an estimate of how long each pump has been working. Additionally, our estimates correct the errors contained in the time series regarding the number of active pumps.