Virtual Seminar Series organized by the Department of Chemistry, Materials and Chemical Engineering "Giulio Natta" waiting to be able to resume the live activity.
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Today, we are witnessing important developments that go beyond “traditional” chemical engineering. Chemists and engineers are working together on techniques that could transform our concept of “chemical plant”. This will lead to modular, miniaturized, safe, energy-efficient, and ecological processes. These advancements have opened the doors to synthetic transformations that were once considered “impossible” under “traditional” conditions, and are particularly relevant for the pharmaceutical and fine chemical industries, the two sectors that have historically produced the highest amount of pollution and waste.
With examples from our research, this seminar will highlight the impact of process intensification on several layers, from the utilization of catalytic materials with unprecedented structural control to the experimental design of continuous processes and flow conditions for the chemical industry of tomorrow.
Carbon allotropes from sp3-hybridized carbon (diamond) and sp2-hybridized carbon (graphite,
graphene, fullerenes, nanotubes) have well-established properties, many of which are technologically relevant. In particular, the discovery of fullerenes and graphene has captured the imagination of many chemists since these allotropes and their derivatives might serve as platforms for the next generation of electronic and energy capture devices. One needs to look no further than Nobel Prizes awarded in 1996 (C60) and 2010 (graphene) to appreciate the impact of these discoveries. A carbon allotrope derived from sp-hybridized carbon atoms (carbyne) has been discussed since the 1960s, although an authentic sample of “natural” carbyne has not yet been identified. Recent computational studies suggest that carbyne might be the strongest known material or the ideal molecular wire, although experimental confirmation of these predictions remains elusive and the search for carbyne continues.
Organic chemists have tackled the challenge of carbyne through the synthesis and study of model compounds. With this goal in mind, we have developed a new methods toward the synthesis of polyynes[2–3] and cumulenes as compounds to model the properties of carbyne. These efforts provide us with a unique opportunity to explore the physical characteristics of these compounds as a function of length. This presentation will describe the evolution of properties in the progression of oligoynes, to polyynes, to carbyne. The contrast of various properties through correlations drawn from spectroscopic analyses and X-ray crystallography are key to these studies and will be discussed. Finally, some predictions for the properties of carbyne will be offered.
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 Y. Gao, Y. Hou, F. Gordillo-Gámez, M. J. Ferguson, J. Casado, R. R. Tykwinski, Nat. Chem. 2020, accepted
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June 19, 2020, 11:30 am
Signal and Data Processing Workflows for Untargeted Chemical Analysis: Sensor Array and Mass Spectrometry Analysis of Complex Gas Samples
Department of Electronics and Biomedical Engineering, University of Barcelona & Institute for Bioengineering of Catalonia, Barcelona Institute of Science and Technology
In diverse sectors such as health, food, environment, complex natural gas samples are analysed. Those samples can contain hundreds or thousands of compounds. In many cases, the question to be answered does not require full separation, quantification, and identification of all compounds. Instead detection of abnormal samples (normal/ faulty), assignation of classes to samples (e.g.healthy/disease), or evaluation of global quantitative indexes (e.g odour intensity) is required.
The analysis of gas phase samples can be carried out with high-end lab equipment based on Chromatography-Mass Spectrometry or lower cost systems based on chemical sensors. In all cases, the resulting raw signals/data need substantial efforts to extract the hidden information. In health applications the problem of biomarker discovery becomes like finding a needle in a haystack. Intimate knowledge of the instrumental problems and the sampling conditions is key for the correct interpretation of the results.
These problems are often addressed by building mega-variate predictive models using tools from machine learning. However, in small sample conditions the possibilities to obtain overoptimistic results abound due to the curse of dimensionality. Careful model validation and statement of model validity domains is needed.
Integrated structural biology approaches provide us with an opportunity to understand the inner workings of proteins and protein complexes that controls basic cellular functions. Recent technical advances in electron. Microscopy (EM) have allowed us to overcome previous limitations restricting the size and heterogeneity of complexes under study. The resulting movies show, at near atomic resolution, large macromolecular machines at work. Looking forwards, the future holds the promise of routinely carrying out high-resolution imaging of these machines operating within normal and diseased cells.
Viral infections are among the main causes of death in the world. When prevention is not an option, antiviral drugs are the last resort to prevent the spread and the mortality of these infections. There are only a few effective drugs on the market, for the most part they prevent intracellular viral replication. Unfortunately, they are too few when compared to the many viruses that threaten humans.
In this talk, I will show a new design rule to achieve drugs that fight viruses extracellularly by irreversibly inhibiting their infectivity, i.e. I will show how to create virucidal compounds. The design of these macromolecular virucidal agents starts by a bio-mimic approach and is characterized by the limited toxicity towards host cells that one would expect from such compounds. Yet, I will demonstrate that the multivalent binding to the viruses, coupled with a large hydrophobic contact between the compounds and the virus leads to a loss of integrity of the virion that obviously leads to an irreversible loss of infectivity. Results in and ex-vivo will be illustrated especially for the cases of influenza, herpes, and respiratory syncytial virus.
In bioinspired materials there is a search for ever more complex functionalities and responses. Classic functionalities in materials science are stimuli-responses and shape-memory effects, relevant for numerous applications. Beyond those, could materials showing a response to a particular stimulus become responsive to another stimulus to which they are originally indifferent? Such a behavior would mimic the classical conditioning in behavioral psychology, one of the elementary forms of associative learning, originally shown by Pavlov in his experiments with dogs. Here we demonstrate two soft matter systems (a hydrogel and a liquid crystalline network) programmed to mimic classical conditioning. We foresee a wealth of possibilities for different materials systems, combinations of stimuli and different "memory" concepts for classically conditioned functional materials.