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X-WR-CALNAME:Instituto de Física
X-ORIGINAL-URL:https://www.if.ufrj.br
X-WR-CALDESC:Events for Instituto de Física
BEGIN:VEVENT
DTSTART;TZID=America/Sao_Paulo:20230926T105000
DTEND;TZID=America/Sao_Paulo:20230926T120000
DTSTAMP:20260307T123922
CREATED:20230922T181303Z
LAST-MODIFIED:20230922T181303Z
UID:21607-1695725400-1695729600@www.if.ufrj.br
SUMMARY:Seminários do Departamento de Física dos Sólidos - Itamar Borges Jr. (IME - Dept. de Química)
DESCRIPTION:The Substituent Effect in Chemistry and Machine Learning: Applications to Organic Photovoltaics and Energetic Materials\n \nItamar Borges Jr.\n(IME – Dept. de Química)\n \nResumo: \nThe substituent effect – the modification of the electronic properties of molecules by changing groups of atoms – is ubiquitous in Chemistry and Materials Science. Machine learning (ML) techniques\, a set of statistical methods that take advantage of recent developments in hardware and larger volumes of more accurate data\, have become a handy tool for basic research. Combining these two approaches can reveal unknown phenomena and new physical insights. In this talk\, we present Hammett’s theory\, which quantifies via numerical constants\, the electron-donor or -withdrawal power of substituents. We discuss a new comprehensive and systematic set of Hammett’s constants for general use determined with ML [1]. Afterward\, we examine diketopyrrolopyrrole (DPP) molecules with one or two substituents\, which can be used as a fine-tuned donor material in organic electronic devices. Several photovoltaic properties\, including power conversion efficiencies in bulk heterojunctions\, exciton binding energies and intramolecular charge transfer effects\, are discussed in the framework of Hammett’s theory [2]. Finally\, we examine the molecular origin of the impact sensitivity of an energetic material\, which was rationalized with ML. In particular\, we found that a positive or negative contribution of the molecular properties to the sensitivity depends on the value of this property [3]. Finally\, we discuss some implications of combining quantum chemistry with ML and mention other research carried out by our group. \nReferences:\n[1] – MONTEIRO-DE-CASTRO\, GABRIEL ; DUARTE\, JULIO CESAR ; BORGES\, ITAMAR . Machine Learning Determination of New Hammett’s Constants for meta- and para- Substituted Benzoic Acids Derivatives Employing Quantum Chemical Atomic Charge Methods. JOURNAL OF ORGANIC CHEMISTRY (JOC)\, 2023\, 88\, 9802. \nAlso featured in Chemistry World (Royal Society of Chemistry)\, July 31\, 2023 “86-old Hammett equation gets a machine learning upgrade”\, https://www.chemistryworld.com/news/86-year-old-hammett-equation-gets-a-machine-learning-update/4017798.article \n86-year old Hammett equation gets a machine learning update\nAlgorithm opens the door to improved understanding of aromatic substituent effects\nwww.chemistryworld.com \n[2] – MONTEIRO-DE-CASTRO\, GABRIEL; BORGES\, ITAMAR. A Hammett’s analysis of the substituent effect in functionalized diketopyrrolopyrrole (DPP) systems: Optoelectronic properties and intramolecular charge transfer effects. JOURNAL OF COMPUTATIONAL CHEMISTRY (JCC) 2023\, 44\, 2656 – 2273. \n[3] – DUARTE\, JÚLIO CESAR ; ROCHA\, ROMULO DIAS DA ; BORGES JR\, ITAMAR . Which molecular properties determine the impact sensitivity of an explosive? A machine learning quantitative investigation of nitroaromatic explosives. PHYSICAL CHEMISTRY CHEMICAL PHYSICS (PCCP) 2023\, 25\, 6877 \n  \n\n \nDepartamento de Física dos Sólidos\nInstituto de Física UFRJ \n
URL:https://www.if.ufrj.br/evento/seminarios-do-departamento-de-fisica-dos-solidos-itamar-borges-jr-ime-dept-de-quimica/
CATEGORIES:IF - Seminários,IF - Seminários de Grupo
ORGANIZER;CN="Natanael%20de%20Carvalho%20Costa":MAILTO:natanael@if.ufrj.br
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