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Artificial intelligence algorithms can be exploited to enhance identification, localization, and grasping performance in robotics applications, employing low-cost vision systems (such as 2D cameras). The aim of this paper is, indeed, to optimize the camera pose to improve object detection tasks considering a mul- tiple objects scenario. Therefore, transfer learning capabilities are required to minimize the experimental effort in subsequent grasps. Bayesian optimization (BO) with transfer learning (TL) capabilities has been proposed to address the mentioned scenario. A grasping task of multiple parts has been considered, being executed by an ABB Yumi single-arm manipulator IRB 14050 with a 2D Cognex AE3 In-Sight camera mounted at its end- effector. The proposed BO+ TL methodology has been compared with BO (without TL). The achieved results show that BO+TL is more efficient than BO exploiting the already available data.

An anionic mechanism is used to create polymers and copolymers as confined to, or anchored to, high-surface-area porous nanoparticles. Linear polymers with soft and glassy chains, such as polyisoprene and polymethylmethacrylate, were produced by confined anionic polymerization in 3D networks of porous aromatic frameworks. Alternatively, multiple anions were generated on the designed frameworks which bear removal protons at selected positions, and initiate chain propagation, resulting in chains covalently connected to the 3D network. Such growth can continue outside the pores to produce polymer-matrix nanoparticles coated with anchored chains. Sequential reactions were promoted by the living character of this anionic propagation, yielding nanoparticles that were covered by a second polymer anchored by anionic block copolymerization. The intimacy of the matrix and the grown-in polymers was demonstrated by magnetization transfer across the interfaces in 2D 1H-13C-HETCOR NMR spectra.

The synthesis of porous organic 3D frameworks, wherein amine, hydroxyl and Li-alkoxide functions were built directly on the monomer-unit carbon core, realizes improved interactions with target gases. CO2 was retained by the amine group with a remarkable energy of 54 kJ mol-1, while 2D MAS NMR provided rare evidence of amine-to-gas short-distance interactions. Frameworks containing hydroxyl and Li-alkoxide functions show optimal interaction energies with CH4 of up to 25 kJ mol-1. The light network of 3-branch building units ensures the expandability of the nano-sponges.

It has been over half a century since polyacrylonitrile (PAN)-based carbon fibers were first developed. However, the mechanism of the carbonization reaction remains largely unknown. Structural evolution of PAN during the preoxidation reaction, a stabilization reaction, is one of the most complicated stages because many chemical reactions, including cyclization, dehydration, and cross-linking reactions, simultaneously take place. Here, we report the stabilization reaction of single PAN chains within the one-dimensional nanochannels of metal-organic frameworks (MOFs) to study an effect of interchain interactions on the stabilization process as well as the structure of the resulting ladder polymer (LP). The stabilization reaction of PAN within the MOFs could suppress the rapid generation of heat that initiates the self-catalyzed reaction and inevitably provokes many side-reactions and scission of PAN chains in the bulk state. Consequently, LP prepared within the MOFs had a more extended conjugated backbone than the bulk condition. This journal is © The Royal Society of Chemistry.

Il lavoro si è diviso in due parti. La prima parte è stato uno studio sulle capacità di adsorbimento di gas dei materiali porosi, in particolare sulla capacità di sistemi porosi organici nello stoccaggio di metano. Il lavoro si è basato su uno studio sistematico di una serie di materiali porosi organici, delle capacità di stoccaggio di metano ad alta pressione. I materiali sintetizzati sono stati confrontati con alcuni materiali porosi commerciali con alte prestazioni nello stoccaggio e hanno evidenziato un aumento delle quantità di gas possibilmente trasportabile al loro interno. I materiali sono stati confrontanti anche con i metodi comunemente usati per il trasporto di metano, risultando dei potenziali candidati per tale applicazione, considerando la facilità di produzione e la stabilità sia termica che chimica. Un'altra serie di materiali porosi con leggere modifiche alla struttura principale, ha dimostrato invece, la possibilità di modificare l'interazione del materiale con i differenti gas andando a ottenere dei composti con leggere modifiche strutturali ma con interazioni fisiche differenti. In una seconda parte mi sono concentrato sull'utilizzo dei pori di questi materiali come reattori per polimerizzazioni confinate. Il lavoro ha portato allo sviluppo per la prima volta della polimerizzazione anionica all'interno di tali materiali. Questa nuova e innovativa tecnica ha permesso di produrre polimeri con tatticità distinta e catene isolate. Successivamente, si è deciso di ancorare chimicamente il materiale poroso al polimero in crescita. Questo ha portato a polimeri con strutture diverse da quelle ottenibili con le classiche polimerizzazioni e allo sviluppo di un nuovo tipo di composito completamente carbonioso e chimicamente legato che impedisce il problema dello smiscelamento. Successivamente, l'utilizzo di materiali con pori monodimensionali, ha portato allo sviluppo di poliacrilonitrile all'interno dei canali del materiale. Il poliacrilonitrile, The work was divided into two parts. The first part was a study on the gas adsorption capacity of porous materials, in particular on the capacity of porous organic systems in methane storage. The work was based on a systematic study of a series of organic porous materials, of high pressure methane storage capacities. The synthesized materials were compared with some commercial porous materials with high performance in storage and showed an increase in the quantities of gas possibly transportable inside them. The materials were also compared with the methods commonly used for the transport of methane, resulting in potential candidates for this application, considering the ease of production and both thermal and chemical stability. Another series of porous materials with slight changes to the main structure, has shown, however, the possibility of modifying the interaction of the material with the different gases going to obtain compounds with slight structural changes but with different physical interactions. In a second part I focused on using the pores of these materials as reactors for confined polymerizations. The work led to the development of anionic polymerization in these materials for the first time. This new and innovative technique has allowed us to produce polymers with distinct tactics and isolated chains. Subsequently, it was decided to chemically anchor the porous material to the growing polymer. This has led to polymers with structures different from those obtainable with the classic polymerizations and to the development of a new type of completely carbonaceous and chemically bound composite that prevents the problem of de-mixing. Subsequently, the use of materials with one-dimensional pores, led to the development of polyacrylonitrile within the material channels. Polyacrylonitrile was subsequently converted through carbon fiber thermal treatments into the porous material. The thermal treatment of polyacrylonitrile inside the pores has led to a struc

High surface area 3D polymers represent one of the most promising classes of porous materials because of their high gas uptake and stability to thermal and chemical degradation. A series of porous organic polymers with aromatic building units have been synthesized and compared to explore their high-pressure performance as adsorbents of gases of relevant importance for energy and the environment. Particular attention was paid to methane storage up to pressures as high as 180 bar at ambient temperature. Porous polymers were prepared starting from a wide choice of spatially expanded aromatic monomers: a systematic change in the number of rings, variable size and shape was taken under consideration. The high number of rings (up to 6), which act as multiple reactive sites and form a number of connections between the multi-dentate nodes, result in an extensive cross-linked framework. Condensation was obtained by two alternative synthetic routes, viz., Yamamoto cross-coupling and Friedel-Crafts alkylation reactions. The structural characteristics and high stability of the porous polymers, even to mechanical compression, were carefully determined by several methods, including 1D and 2D solid state NMR, FT IR and thermal analyses. The CH4 uptake in the porous polymers allowed an understanding of the incremental response to pressure, up to extremely high values, and the exploitation of the extensive pressure range to customize the gas adsorption/desorption cycles for storage and transportation. Owing to the notable presence of large mesopores and network flexibility, combined with high surface area, a remarkable gain at high pressure was achieved, ensuring a highly competitive uptake/delivery efficiency. At 180 bar, adsorption values up to 445 cm3 STP g-1 were measured for porous organic polymers such as carbazolyl- and triptycene-based materials. The benchmark of these materials PAF1 reaches the value of 916 cm3 STP g-1 of adsorbed CH4, exceeding the performance of most of t

A novel estimator for the identification of continuous-time linear time-varying systems is presented in this paper. The estimator uses kernel-based regression to identify the time-varying coefficients of a linear ordinary differential equation, based on noisy samples of the input and output signals. The estimator adopts a mixed time- and frequency-domain formulation, which allows it to be formulated as the solution of a set of algebraic equations, without relying on finite differences to approximate the time derivatives. Since a kernel-based approach is used, the model complexity selection of the time-varying parameters is formulated as an optimisation problem with continuous variables. Variance and bias expressions of the estimate are derived and validated on a simulation example. Also, it is shown that, in highly noisy environments, the proposed kernel-based estimator provides more reliable results than an 'Oracle'-based estimator which is deprived of regularisation.

The fabrication of porous architectures for the confinement of gases and polymer chains to pores is a challenging research area. The matrices range from fully-organic and metal-organic frameworks to porous molecular crystals of synthetic and biological origin, such as dipeptides.[1] We were mostly intrigued in comparing the matrices depending on the nature of the interactions, pore shape, surface area and pore capacity. Like gases, flexible polymer chains can diffuse inside the galleries undergoing severe steric requirements which tune their conformations, dynamics and properties. Fast-1H, 19F and 2D hetero-correlated MAS NMR spectroscopies played a key role in determining the host-guest interactions at the interfaces and the relationships between the components. A few case studies will be highlighted. A peculiar kind of porous crystalline solid derives from the use of hard and soft interactions in a hierarchical construction. Primary supramolecular toroidal structures are formed by robust metal-organic bonds: they can self-assemble four-by-four into the shape of Platonic solids, held together by van der Waals and coulombic interactions.[2] Anions play a major role in modulating the architectures. The 3D crystalline structures are permanently porous and able to entrap reversibly vapors and gases. In a further example, 1,3-butadiene vapors could be separated from other C4 hydrocarbon by a MOF matrix [3], which provides structural flexibility and unique guest-responsive accommodation. Regarding the relevant issue of manipulating and transforming polymer chains in a confined environment, we varied the conducting properties of polyacrylonitrile chains by thermal transformation into graphitized nanofibers.[4] Moreover, isolation of single polysilane chains increased the rate of carrier mobility in comparison with that in the bulk state due to the elimination of the slow interchain hole-hopping.[5] The main chain conformation of polysilane could be controlled by changing

In many control applications, it is attractive to describe nonlinear (NL) and time-varying (TV) plants by linear parameter-varying (LPV) models and design controllers based on such representations to regulate the behavior of the system. The LPV system class offers the representation of NL and TV phenomena as a linear dynamic relationship between input and output signals, which is dependent on some measurable signals, e.g., operating conditions, often called as scheduling variables. For such models, powerful control synthesis tools are available, but the way how to systematically convert available first principles models to LPV descriptions of the plant, to efficiently identify LPV models for control from data and to understand how modeling errors affect the control performance are still subject of undergoing research. Therefore, it is attractive to synthesize the controller directly from data without the need of modeling the plant and addressing the underlying difficulties. Hence, in this paper, a novel data-driven synthesis scheme is proposed in a stochastic framework to provide a practically applicable solution for synthesizing LPV controllers directly from data. Both the cases of fixed order controller tuning and controller structure learning are discussed and two different design approaches are provided. The effectiveness of the proposed methods is also illustrated by means of an academic example and a real application based simulation case study.

Compositi nanostrutturati sono stati ottenuti dalla polimerizzazione radicalica dell’acrilonitrile, stechiometrico e in eccesso, all’interno della matrice porosa del PAF1. Le analisi spettroscopiche e termiche hanno rilevato una presenza massiva di poliacrilonitrile all’interno della matrice porosa e hanno evidenziato un’intima relazione tra le nanofasi. Trattamenti termici e successive analisi spettroscopiche hanno evidenziato come la matrice polimerica possa essere utilizzata come supporto per la trasformazione termica del PAN.

Introduction: Porous materials with permanent porosity have recently emerged as an exciting research field with potential applications in gas storage, separation and catalysis. Porous aromatic frameworks and periodic mesoporous organosilicas showed high robustness and extraordinary chemical stability that made them ideal for supporting chemical reactions without framework destruction. Confined polymerization in nanopores allowed the synthesis of innovative nanostructured materials and nanocomposites with extended interfaces that couldn’t be obtained otherwise. Materials and methods: Porous aromatic framework (PAF-1) was synthetized through a Yamamoto-type Ullmann cross-coupling. P-phenylene silica (PSS) was prepared by a template synthesis. These porous frameworks were characterized with nitrogen adsorption measurement, IR spectroscopy, DSC, TGA and ss-NMR. The polymerizations were performed in the liquid phase: a solution of AIBN (azobisisobutyronitrile) in distilled acrylonitrile was diffused inside the pores of the matrixes and the samples were heated to activate the polymerizations. The nanocomposites were prepared either with stoichiometric amount of monomers or excess monomers. The nanocomposites were characterized with nitrogen adsorption measurement, thermogravimetric analysis and electron microscope techniques (SEM, HR-TEM). The interactions between the porous matrixes and the engendered polymer were investigated with fast magic-angle-spinning 2D 1H-13C HETCOR NMR. The nanocomposites were heated at different temperatures (300-1000°C) under an inert atmosphere. Results: The confined polymerization of acrylonitrile inside the pores of PAF-1 and PSS with stoichiometric amount of monomers led to the fabrication of nanocomposites with intimate relationship between host and guest. The matrixes and the polymer form extensively interdigitated nanophases through multiple interactions. By treating the PAF-1/PAN nanocomposite at 300°C the formation of a ladder polymer

Least-Squares Support Vector Machines (LS-SVMs), originating from Statistical Learning and Reproducing Kernel Hilbert Space (RKHS) theories, represent a promising approach to identify nonlinear systems via nonparametric estimation of the involved nonlinearities in a computationally and stochastically attractive way. However, application of LS-SVMs and other RKHS variants in the identification context is formulated as a regularized linear regression aiming at the minimization of the ℓ2 loss of the prediction error. This formulation corresponds to the assumption of an auto-regressive noise structure, which is often found to be too restrictive in practical applications. In this paper, Instrumental Variable (IV) based estimation is integrated into the LS-SVM approach, providing, under minor conditions, consistent identification of nonlinear systems regarding the noise modeling error. It is shown how the cost function of the LS-SVM is modified to achieve an IV-based solution. Although, a practically well applicable choice of the instrumental variable is proposed for the derived approach, optimal choice of this instrument in terms of the estimates associated variance still remains to be an open problem. The effectiveness of the proposed IV based LS-SVM scheme is also demonstrated by a Monte Carlo study based simulation example.

Most of the approaches available in the literature for the identification of Linear Parameter-Varying (LPV) systems rely on the assumption that only the measurements of the output signal are corrupted by the noise, while the observations of the scheduling variable are considered to be noise free. However, in practice, this turns out to be an unrealistic assumption in most of the cases, as the scheduling variable is often related to a measured signal and, thus, it is inherently affected by a measurement noise. In this paper, it is shown that neglecting the noise on the scheduling signal, which corresponds to an error-in-variables problem, can lead to a significant bias on the estimated parameters. Consequently, in order to overcome this corruptive phenomenon affecting practical use of data-driven LPV modeling, we present an identification scheme to compute a consistent estimate of LPV Input/Output (IO) models from noisy output and scheduling signal observations. A simulation example is provided to prove the effectiveness of the proposed methodology.

The extraordinary surface areas (BET> 5000 m2/g) and pore capacity exhibited by porous aromatic frameworks (PAFs), which are themselves organic polymeric architectures[1] interconnected by covalent bonds, allow sorption of a large amount of monomers to form high-molecular-mass polymers tightly interwoven with the porous matrix [2]. Polyacrylonitrile (PAN) polymerized by this methodology could undergo in-situ thermal transformation to semi-conductive or conductive polymers and carbon nano-fibers. PAN was also synthesized in the form of isotactic polymer within the nanochannels of dipeptide porous crystals which were used as sacrificial polymerization vessels [3]. The crystalline matrix sublimed away at 250 °C after the polymer intramolecular reaction to yield a rigid 'ladder polymer', which retained the morphology of the crystal scaffold. Morphological control has also been obtained starting from mesoporous silica to fabricate polymeric micro-objects. In the case of metal-organic host framework the innovative idea was to make the host participate in the polymerization with two reactive vinyl pendant groups, that resulted in a cross-linked network [4]. The crystal scaffold of the host was removed except where it participates in the cross-linking reaction and acts as clipping point for the aligned polymer chains. Although the polymer chains grow in the atactic configuration, they exhibit periodic order since they are kept in register by the molecular clips. Chain-periodicity was ascertained by XRD and TEM. Moreover, molecular rotors were built in porous organic frameworks, combining the features of porosity and dynamics. The intervention of guests entering from the liquid or vapor phases, such as melted alkanes or iodine, could modulate the motional behavior of the rotors, as shown by 2H NMR. References 1. Angew. Chem. Int Ed. 2014, 53, 1043. 2. Angew. Chem. Int Ed. 2012, 51, 10136. 3 Angew. Chem. Int Ed. 2012, 51, 9258. 4. Nature Chem. 2013, 5, 335.

Our scientific activity is focused on polymerizations in porous materials and the control of solid state reactions as well as on the formation in situ of new complex architectures with polymers. The project exploits both the unprecedented potentials of porous materials presently in use and the properties induced to the polymers e.g. stereochemistry, chain alignment and morphology control: the matrices range from fully-organic covalent frameworks and metal-organic frameworks to porous molecular crystals of biological origin. The extraordinary surface areas (BET> 5000 m2/g) and pore capacity exhibited by porous aromatic frameworks (PAFs), which are themselves polymeric architectures[1] interconnected by covalent bonds, allow sorption of a large amount of monomers to form high-molecular-mass polymers tightly interwoven with the porous matrix [2]. Polyacrylonitrile (PAN) polymerized by this methodology could undergo in-situ thermal transformation to semi-conductive or conductive polymers and carbon nano-fibers. PAN was also synthesized in the form of isotactic polymer within the nanochannels of dipeptide porous crystals which were used as sacrificial polymerization vessels [3]. The crystalline matrix sublimed away at 250 °C after the polymer intramolecular reaction to yield a rigid 'ladder polymer', which retained the morphology of the crystal scaffold. Morphological control has also been obtained starting from mesoporous silica to fabricate polymeric micro-objects [4]. In the case of metal-organic host framework the innovative idea was to make the host participating in the polymerization with two reactive vinyl pendant groups, that resulted in a cross-linked network [5]. The crystal scaffold of the host was removed except where it participates in the cross-linking reaction and acts as clipping point for the aligned polymer chains. Although the polymer chains grow in the atactic configuration, they exhibit periodic order since are kept in register by the molecular clips