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Synthesis, crystal structure analysis, spectral characterization and nonlinear optical exploration of potent thiosemicarbazones based compounds: A DFT refine experimental study
摘要： The thiosemicarbazones have exciting biological and nonlinear optical (NLO) applications. The present study reports detail experimental and computational studies of three novel ferrocene-substituted thiosemicarbazones: (E/Z)-4-(4-chlorobenzyl)-1-(1-ferrocenyl-ethyl)thiosemicarbazone (2) and (E/Z)-4-benzyl-1-(1-ferrocenylethyl)thiosemicarbazones (1) and (E/Z)-4-(2-bromo benzyl)-1-(1-ferrocenylethyl)thiosemicarbazone (3). These compounds were synthesized and resolved into their single crystal structures for the estimation of unit cells, space groups, bond angles and bond lengths. Chemical structures of 1–3 were further characterized spectroscopically employing nuclear magnetic resonance technique (1H NMR), infrared (FT-IR), mass and UV–Visible studies. Computational studies of 1–3 were performed using density functional theory (DFT) tools at M06 level of theory and 6–31 + G(d,p) basis set combination to gain the optimized geometry. A good correlation was found between experimental SC-XRD structures and DFT optimized geometries. Electronic properties including natural bond orbital (NBO) analysis, frontier molecular orbitals (FMOs) analysis, spectroscopic FT-IR data and NLO properties were calculated using same M06/6–31 + G(d,p) level of theory. NBO analysis confirmed the formation of charge separation state due to successful migration of electrons from donor to acceptor unit through π-bridge. Global reactivity parameters were estimated using energies of FMOs which described that 1–3 are chemically hard and stable molecules. Vertical electronic transition states were calculated using time-dependent DFT (TDDFT) at same level of theory. NLO properties of 1–3 were computed 5.77, 3.48 and 8.93 times greater than the standard urea molecule respectively. Two-state model confirmed the potential of synthesized molecules as NLO candidates.
关键词： Frontier molecular orbital,Ferrocene-substituted thiosemicarbazones,Spectroscopic data,Crystal structures,Non-linear optical properties,Density functional theory
更新于2025-09-23 15:21:01
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Machine learning based temperature prediction of poly( <i>N</i> -isopropylacrylamide)-capped plasmonic nanoparticle solutions
摘要： The temperature-dependent optical properties of gold nanoparticles that are capped with the thermo-sensitive polymer: ‘poly(N-isopropylacrylamide)’ (PNIPAM), have been studied extensively for several years. Also, their suitability to function as nanoscopic thermometers for bio-sensing applications has been suggested numerous times. In an attempt to establish this, many have studied the temperature-dependent optical resonance characteristics of these particles; however, developing a simple mathematical relationship between the optical measurements and the solution temperature remains an open challenge. In this paper, we attempt to systematically address this problem using machine learning techniques to quickly and accurately predict the solution-temperature, based on spectroscopic data. Our emphasis is on establishing a simple and practically useful solution to this problem. Our dataset comprises spectroscopic absorption data from both nanorods and nanobipyramids capped with PNIPAM, measured at discretely varied and pre-set temperature states. Specific regions of the spectroscopic data are selected as features for prediction using random forest (RF), gradient boosting (GB) and adaptive boosting (AB) regression techniques. Our prediction results indicate that RF and GB techniques can be used successfully to predict solution temperatures instantly to within 1 1C of accuracy.
关键词： PNIPAM,spectroscopic data,temperature prediction,adaptive boosting,machine learning,random forest,gradient boosting,gold nanoparticles
更新于2025-09-16 10:30:52