Study of materials and interphases for electrochemical energy storage from renewable sources

Batteries should be refined depending on their application for a future in which the sustainable energy demand increases. On the one hand, it is fundamental to improve their safety, prevent failures, increase energy density, and reduce production costs. On the other hand, new battery materials and architecture are required to satisfy the growing demand. This thesis explores different electrochemical energy storage systems and new methodologies to investigate complex and dynamic processes. Lithium-ion batteries are described in all their cell components. In these systems, this thesis investigates negative electrodes. Both the development of new sustainable materials and new in situ electrode characterization methods were explored. One strategy to achieve high-energy systems is employing lithium metal anodes. In this framework, ammonium hexafluorophosphate is demonstrated to be a suitable additive for stabilizing the interphase and preventing uncontrolled dendritic deposition. Deposition/stripping cycles, electrochemical impedance spectroscopy, in situ optical microscopy, and operando confocal Raman spectroscopy have been used to study lithium metal-electrolyte interphase in the presence of the additive. Redox Flow Batteries (RFBs) are proposed as a sustainable alternative for stationary applications. An all-copper aqueous RFB (CuRFB) has been studied in all its aspects. For the electrolyte optimization, spectro-electrochemical tests in diluted solution have been used to get information on the electrolyte’s electrochemical behaviour with different copper complexes distributions. In concentrated solutions, the effects of copper-to-ligand ratios, the concentration, and the counter-ion of the complexing agent were evaluated. Electrode thermal treatment was optimized, finding a compromise between the electrochemical performance and the carbon footprint. On the membrane side, a new method for permeability studies was designed using scanning electrochemical microscopy (SECM). The Cu(II) permeability of several membranes was tested, obtaining direct visualization of Cu(II) concentration in space. Also, two spectrophotometric approaches were designed for SoC monitoring systems for negative and positive half-cells.

Sustainable exploitation of offshore renewable energy sources

Energy transition is the response of humankind to the concerning effects of fossil fuels depletion, climate change and energy insecurity, and calls for a deep penetration of renewable energy sources (RESs) in power systems and industrial processes. Despite the high potentials, low impacts and long-term availability, RESs present some limits which need to be overcome, such as the strong variability and difficult predictability, which result in scarce reliability and difficult applicability in steady-state processes. Some technological solutions relate to energy storage systems, equipment electrification and hybrid systems deployment, thus accomplishing distributed generation even in remote sites as offshore. However, all of these actions cannot disregard sustainability, which represents a founding principle for any project, bringing together economics, reliability and environmental protection. To entail sustainability in RESs-based innovative projects, previous knowledge and tools are often not tailored or miss the novel objectives. This research proposes three methodological approaches, bridging the gaps. The first contribute adapts literature-based indicators of inherent safety and energy efficiency to capture the specificities of novel process plants and hybrid systems. Minor case studies dealing with novel P2X processes exemplify the application of these novel indicators. The second method guides the conceptual design of hybrid systems for the valorisation of a RES in a site, by considering the sustainability performances of alternative design options. Its application is demonstrated through the comparison of two offshore sites where wave energy can be valorised. Finally, “OHRES”, a comprehensive tool for the sustainable optimisation of hybrid renewable energy systems is proposed. “OHRES” hinges on the exploitation of multiple RESs, by converting ex-post sustainability indicators into discrimination markers screening a large number of possible system configurations, according to the location features. Five case studies demonstrate “OHRES” versatility in the sustainable valorisation of multiple RESs.

Portfolio optimization in the energy market

Let’s put ourselves in the shoes of an energy company. Our fleet of electricity production plants mainly includes gas, hydroelectric and waste-to-energy plants. We also sold contracts for the supply of gas and electricity. For each year we have to plan the trading of the volumes needed by the plants and customers: better to fix the price of these volumes in advance with the so-called forward contracts, instead of waiting for the delivery months, exposing ourselves to price uncertainty. Here’s the thing: trying to keep uncertainty under control in a market that has never shown such extreme scenarios as in recent years: a pandemic, a worsening climate crisis and a war that is affecting economies around the world have made the energy market more volatile than ever. How to make decisions in such uncertain contexts? There is an optimization problem: given a year, we need to choose the optimal planning of volume trading times, to meet the needs of our portfolio at the best prices, taking into account the liquidity constraints given by the market and the risk constraints imposed by the company. Algorithms are needed for the generation of market scenarios over a finite time horizon, that is, a probabilistic distribution that allows a view of all the dates between now and the end of the year of interest. Algorithms are needed to solve the optimization problem: we have proposed more than one and compared them; a very simple one, which avoids considering part of the complexity, moving on to a scenario approach and finally a reinforcement learning approach.

Exact and heuristic algorithms for the integrated planning of multi-energy systems

The aim of this thesis is to present exact and heuristic algorithms for the integrated planning of multi-energy systems. The idea is to disaggregate the energy system, starting first with its core the Central Energy System, and then to proceed towards the Decentral part. Therefore, a mathematical model for the generation expansion operations to optimize the performance of a Central Energy System system is first proposed. To ensure that the proposed generation operations are compatible with the network, some extensions of the existing network are considered as well. All these decisions are evaluated both from an economic viewpoint and from an environmental perspective, as specific constraints related to greenhouse gases emissions are imposed in the formulation. Then, the thesis presents an optimization model for solar organic Rankine cycle in the context of transactive energy trading. In this study, the impact that this technology can have on the peer-to-peer trading application in renewable based community microgrids is inspected. Here the consumer becomes a prosumer and engages actively in virtual trading with other prosumers at the distribution system level. Moreover, there is an investigation of how different technological parameters of the solar Organic Rankine Cycle may affect the final solution. Finally, the thesis introduces a tactical optimization model for the maintenance operations’ scheduling phase of a Combined Heat and Power plant. Specifically, two types of cleaning operations are considered, i.e., online cleaning and offline cleaning. Furthermore, a piecewise linear representation of the electric efficiency variation curve is included. Given the challenge of solving the tactical management model, a heuristic algorithm is proposed. The heuristic works by solving the daily operational production scheduling problem, based on the final consumer’s demand and on the electricity prices. The aggregate information from the operational problem is used to derive maintenance decisions at a tactical level.

Machine learning "as a service" for high energy physics (MLaaS4HEP): evolution of a framework for ML-based physics analyses

The scientific success of the LHC experiments at CERN highly depends on the availability of computing resources which efficiently store, process, and analyse the amount of data collected every year. This is ensured by the Worldwide LHC Computing Grid infrastructure that connect computing centres distributed all over the world with high performance network. LHC has an ambitious experimental program for the coming years, which includes large investments and improvements both for the hardware of the detectors and for the software and computing systems, in order to deal with the huge increase in the event rate expected from the High Luminosity LHC (HL-LHC) phase and consequently with the huge amount of data that will be produced. Since few years the role of Artificial Intelligence has become relevant in the High Energy Physics (HEP) world. Machine Learning (ML) and Deep Learning algorithms have been successfully used in many areas of HEP, like online and offline reconstruction programs, detector simulation, object reconstruction, identification, Monte Carlo generation, and surely they will be crucial in the HL-LHC phase. This thesis aims at contributing to a CMS R&D project, regarding a ML "as a Service" solution for HEP needs (MLaaS4HEP). It consists in a data-service able to perform an entire ML pipeline (in terms of reading data, processing data, training ML models, serving predictions) in a completely model-agnostic fashion, directly using ROOT files of arbitrary size from local or distributed data sources. This framework has been updated adding new features in the data preprocessing phase, allowing more flexibility to the user. Since the MLaaS4HEP framework is experiment agnostic, the ATLAS Higgs Boson ML challenge has been chosen as physics use case, with the aim to test MLaaS4HEP and the contribution done with this work.

WEC-Sim Application for the Assessment of Wave Energy Generation in the Tyrrhenian Sea and the North Sea Through the 2-Body Point Absorber (2BPA) and the Oscillating Surge Wave Energy Converter (OSWEC)

In recent years, developed countries have turned their attention to clean and renewable energy, such as wind energy and wave energy that can be converted to electrical power. Companies and academic groups worldwide are investigating several wave energy ideas today. Accordingly, this thesis studies the numerical simulation of the dynamic response of the wave energy converters (WECs) subjected to the ocean waves. This study considers a two-body point absorber (2BPA) and an oscillating surge wave energy converter (OSWEC). The first aim is to mesh the bodies of the earlier mentioned WECs to calculate their hydrostatic properties using axiMesh.m and Mesh.m functions provided by NEMOH. The second aim is to calculate the first-order hydrodynamic coefficients of the WECs using the NEMOH BEM solver and to study the ability of this method to eliminate irregular frequencies. The third is to generate a *.h5 file for 2BPA and OSWEC devices, in which all the hydrodynamic data are included. The BEMIO, a pre-and post-processing tool developed by WEC-Sim, is used in this study to create *.h5 files. The primary and final goal is to run the wave energy converter Simulator (WEC-Sim) to simulate the dynamic responses of WECs studied in this thesis and estimate their power performance at different sites located in the Mediterranean Sea and the North Sea. The hydrodynamic data obtained by the NEMOH BEM solver for the 2BPA and OSWEC devices studied in this thesis is imported to WEC-Sim using BEMIO. Lastly, the power matrices and annual energy production (AEP) of WECs are estimated for different sites located in the Sea of Sicily, Sea of Sardinia, Adriatic Sea, Tyrrhenian Sea, and the North Sea. To this end, the NEMOH and WEC-Sim are still the most practical tools to estimate the power generation of WECs numerically.

Fatigue Design Challenges of Transition Pieces from Decommissioned Platforms for Offshore Wind Energy

All structures are subjected to various loading conditions and combinations. For offshore structures, these loads include permanent loads, hydrostatic pressure, wave, current, and wind loads. Typically, sea environments in different geographical regions are characterized by the 100-year wave height, surface currents, and velocity speeds. The main problems associated with the commonly used, deterministic method is the fact that not all waves have the same period, and that the actual stochastic nature of the marine environment is not taken into account. Offshore steel structure fatigue design is done using the DNVGL-RP-0005:2016 standard which takes precedence over the DNV-RP-C203 standard (2012). Fatigue analysis is necessary for oil and gas producing offshore steel structures which were first constructed in the Gulf of Mexico North Sea (the 1930s) and later in the North Sea (1960s). Fatigue strength is commonly described by S-N curves which have been obtained by laboratory experiments. The rapid development of the Offshore wind industry has caused the exploration into deeper ocean areas and the adoption of new support structural concepts such as full lattice tower systems amongst others. The optimal design of offshore wind support structures including foundation, turbine towers, and transition piece components putting into consideration, economy, safety, and even the environment is a critical challenge. In this study, fatigue design challenges of transition pieces from decommissioned platforms for offshore wind energy are proposed to be discussed. The fatigue resistance of the material and structural components under uniaxial and multiaxial loading is introduced with the new fatigue design rules whilst considering the combination of global and local modeling using finite element analysis software programs.

Development of a heterogeneous clustering algorithm for particle shower reconstruction in high energy physics using the SYCL abstraction layer

Nei prossimi anni è atteso un aggiornamento sostanziale di LHC, che prevede di aumentare la luminosità integrata di un fattore 10 rispetto a quella attuale. Tale parametro è proporzionale al numero di collisioni per unità di tempo. Per questo, le risorse computazionali necessarie a tutti i livelli della ricostruzione cresceranno notevolmente. Dunque, la collaborazione CMS ha cominciato già da alcuni anni ad esplorare le possibilità offerte dal calcolo eterogeneo, ovvero la pratica di distribuire la computazione tra CPU e altri acceleratori dedicati, come ad esempio schede grafiche (GPU). Una delle difficoltà di questo approccio è la necessità di scrivere, validare e mantenere codice diverso per ogni dispositivo su cui dovrà essere eseguito. Questa tesi presenta la possibilità di usare SYCL per tradurre codice per la ricostruzione di eventi in modo che sia eseguibile ed efficiente su diversi dispositivi senza modifiche sostanziali. SYCL è un livello di astrazione per il calcolo eterogeneo, che rispetta lo standard ISO C++. Questo studio si concentra sul porting di un algoritmo di clustering dei depositi di energia calorimetrici, CLUE, usando oneAPI, l'implementazione SYCL supportata da Intel. Inizialmente, è stato tradotto l'algoritmo nella sua versione standalone, principalmente per prendere familiarità con SYCL e per la comodità di confronto delle performance con le versioni già esistenti. In questo caso, le prestazioni sono molto simili a quelle di codice CUDA nativo, a parità di hardware. Per validare la fisica, l'algoritmo è stato integrato all'interno di una versione ridotta del framework usato da CMS per la ricostruzione. I risultati fisici sono identici alle altre implementazioni mentre, dal punto di vista delle prestazioni computazionali, in alcuni casi, SYCL produce codice più veloce di altri livelli di astrazione adottati da CMS, presentandosi dunque come una possibilità interessante per il futuro del calcolo eterogeneo nella fisica delle alte energie.

Analysis Of The Dna Fourier Transform-infrared Microspectroscopic Signature Using An All-reflecting Objective.

The Fourier transform-infrared (FT-IR) signature of dry samples of DNA and DNA-polypeptide complexes, as studied by IR microspectroscopy using a diamond attenuated total reflection (ATR) objective, has revealed important discriminatory characteristics relative to the PO2(-) vibrational stretchings. However, DNA IR marks that provide information on the sample's richness in hydrogen bonds have not been resolved in the spectral profiles obtained with this objective. Here we investigated the performance of an all reflecting objective (ARO) for analysis of the FT-IR signal of hydrogen bonds in DNA samples differing in base richness types (salmon testis vs calf thymus). The results obtained using the ARO indicate prominent band peaks at the spectral region representative of the vibration of nitrogenous base hydrogen bonds and of NH and NH2 groups. The band areas at this spectral region differ in agreement with the DNA base richness type when using the ARO. A peak assigned to adenine was more evident in the AT-rich salmon DNA using either the ARO or the ATR objective. It is concluded that, for the discrimination of DNA IR hydrogen bond vibrations associated with varying base type proportions, the use of an ARO is recommended.

Beam-energy Dependence Of The Directed Flow Of Protons, Antiprotons, And Pions In Au+au Collisions.

Rapidity-odd directed flow (v1) measurements for charged pions, protons, and antiprotons near midrapidity (y=0) are reported in sNN=7.7, 11.5, 19.6, 27, 39, 62.4, and 200 GeV Au+Au collisions as recorded by the STAR detector at the Relativistic Heavy Ion Collider. At intermediate impact parameters, the proton and net-proton slope parameter dv1/dy|y=0 shows a minimum between 11.5 and 19.6 GeV. In addition, the net-proton dv1/dy|y=0 changes sign twice between 7.7 and 39 GeV. The proton and net-proton results qualitatively resemble predictions of a hydrodynamic model with a first-order phase transition from hadronic matter to deconfined matter, and differ from hadronic transport calculations.

Graphene And Carbon Nanotube Nanocomposite For Gene Transfection.

Graphene and carbon nanotube nanocomposite (GCN) was synthesised and applied in gene transfection of pIRES plasmid conjugated with green fluorescent protein (GFP) in NIH-3T3 and NG97 cell lines. The tips of the multi-walled carbon nanotubes (MWCNTs) were exfoliated by oxygen plasma etching, which is also known to attach oxygen content groups on the MWCNT surfaces, changing their hydrophobicity. The nanocomposite was characterised by high resolution scanning electron microscopy; energy-dispersive X-ray, Fourier transform infrared and Raman spectroscopies, as well as zeta potential and particle size analyses using dynamic light scattering. BET adsorption isotherms showed the GCN to have an effective surface area of 38.5m(2)/g. The GCN and pIRES plasmid conjugated with the GFP gene, forming π-stacking when dispersed in water by magnetic stirring, resulting in a helical wrap. The measured zeta potential confirmed that the plasmid was connected to the nanocomposite. The NIH-3T3 and NG97 cell lines could phagocytize this wrap. The gene transfection was characterised by fluorescent protein produced in the cells and pictured by fluorescent microscopy. Before application, we studied GCN cell viability in NIH-3T3 and NG97 line cells using both MTT and Neutral Red uptake assays. Our results suggest that GCN has moderate stability behaviour as colloid solution and has great potential as a gene carrier agent in non-viral based therapy, with low cytotoxicity and good transfection efficiency.

Exposure To Bisphenol-a During Pregnancy Partially Mimics The Effects Of A High-fat Diet Altering Glucose Homeostasis And Gene Expression In Adult Male Mice.

Bisphenol-A (BPA) is one of the most widespread EDCs used as a base compound in the manufacture of polycarbonate plastics. The aim of our research has been to study how the exposure to BPA during pregnancy affects weight, glucose homeostasis, pancreatic β-cell function and gene expression in the major peripheral organs that control energy flux: white adipose tissue (WAT), the liver and skeletal muscle, in male offspring 17 and 28 weeks old. Pregnant mice were treated with a subcutaneous injection of 10 µg/kg/day of BPA or a vehicle from day 9 to 16 of pregnancy. One month old offspring were divided into four different groups: vehicle treated mice that ate a normal chow diet (Control group); BPA treated mice that also ate a normal chow diet (BPA); vehicle treated animals that had a high fat diet (HFD) and BPA treated animals that were fed HFD (HFD-BPA). The BPA group started to gain weight at 18 weeks old and caught up to the HFD group before week 28. The BPA group as well as the HFD and HFD-BPA ones presented fasting hyperglycemia, glucose intolerance and high levels of non-esterified fatty acids (NEFA) in plasma compared with the Control one. Glucose stimulated insulin release was disrupted, particularly in the HFD-BPA group. In WAT, the mRNA expression of the genes involved in fatty acid metabolism, Srebpc1, Pparα and Cpt1β was decreased by BPA to the same extent as with the HFD treatment. BPA treatment upregulated Pparγ and Prkaa1 genes in the liver; yet it diminished the expression of Cd36. Hepatic triglyceride levels were increased in all groups compared to control. In conclusion, male offspring from BPA-treated mothers presented symptoms of diabesity. This term refers to a form of diabetes which typically develops in later life and is associated with obesity.

Changes In Liver Cell Dna Methylation Status In Diabetic Mice Affect Its Ft-ir Characteristics.

Lower levels of cytosine methylation have been found in the liver cell DNA from non-obese diabetic (NOD) mice under hyperglycemic conditions. Because the Fourier transform-infrared (FT-IR) profiles of dry DNA samples are differently affected by DNA base composition, single-stranded form and histone binding, it is expected that the methylation status in the DNA could also affect its FT-IR profile. The DNA FT-IR signatures obtained from the liver cell nuclei of hyperglycemic and normoglycemic NOD mice of the same age were compared. Dried DNA samples were examined in an IR microspectroscope equipped with an all-reflecting objective (ARO) and adequate software. Changes in DNA cytosine methylation levels induced by hyperglycemia in mouse liver cells produced changes in the respective DNA FT-IR profiles, revealing modifications to the vibrational intensities and frequencies of several chemical markers, including νas -CH3 stretching vibrations in the 5-methylcytosine methyl group. A smaller band area reflecting lower energy absorbed in the DNA was found in the hyperglycemic mice and assumed to be related to the lower levels of -CH3 groups. Other spectral differences were found at 1700-1500 cm(-1) and in the fingerprint region, and a slight change in the DNA conformation at the lower DNA methylation levels was suggested for the hyperglycemic mice. The changes that affect cytosine methylation levels certainly affect the DNA-protein interactions and, consequently, gene expression in liver cells from the hyperglycemic NOD mice.

Beam-energy Dependence Of Charge Separation Along The Magnetic Field In Au+au Collisions At Rhic.

Local parity-odd domains are theorized to form inside a quark-gluon plasma which has been produced in high-energy heavy-ion collisions. The local parity-odd domains manifest themselves as charge separation along the magnetic field axis via the chiral magnetic effect. The experimental observation of charge separation has previously been reported for heavy-ion collisions at the top RHIC energies. In this Letter, we present the results of the beam-energy dependence of the charge correlations in Au+Au collisions at midrapidity for center-of-mass energies of 7.7, 11.5, 19.6, 27, 39, and 62.4 GeV from the STAR experiment. After background subtraction, the signal gradually reduces with decreased beam energy and tends to vanish by 7.7 GeV. This implies the dominance of hadronic interactions over partonic ones at lower collision energies.

Propylthiouracil Quantification In Human Plasma By High-performance Liquid Chromatography Coupled With Electrospray Tandem Mass Spectrometry: Application In A Bioequivalence Study.

A rapid, sensitive and specific method for quantifying propylthiouracil in human plasma using methylthiouracil as the internal standard (IS) is described. The analyte and the IS were extracted from plasma by liquid-liquid extraction using an organic solvent (ethyl acetate). The extracts were analyzed by high performance liquid chromatography coupled with electrospray tandem mass spectrometry (HPLC-MS/MS) in negative mode (ES-). Chromatography was performed using a Phenomenex Gemini C18 5μm analytical column (4.6mm×150mm i.d.) and a mobile phase consisting of methanol/water/acetonitrile (40/40/20, v/v/v)+0.1% of formic acid. For propylthiouracil and I.S., the optimized parameters of the declustering potential, collision energy and collision exit potential were -60 (V), -26 (eV) and -5 (V), respectively. The method had a chromatographic run time of 2.5min and a linear calibration curve over the range 20-5000ng/mL. The limit of quantification was 20ng/mL. The stability tests indicated no significant degradation. This HPLC-MS/MS procedure was used to assess the bioequivalence of two propylthiouracil 100mg tablet formulations in healthy volunteers of both sexes in fasted and fed state. The geometric mean and 90% confidence interval CI of Test/Reference percent ratios were, without and with food, respectively: 109.28% (103.63-115.25%) and 115.60% (109.03-122.58%) for Cmax, 103.31% (100.74-105.96%) and 103.40% (101.03-105.84) for AUClast. This method offers advantages over those previously reported, in terms of both a simple liquid-liquid extraction without clean-up procedures, as well as a faster run time (2.5min). The LOQ of 20ng/mL is well suited for pharmacokinetic studies. The assay performance results indicate that the method is precise and accurate enough for the routine determination of the propylthiouracil in human plasma. The test formulation with and without food was bioequivalent to reference formulation. Food administration increased the Tmax and decreased the bioavailability (Cmax and AUC).