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Excited-State Reaction Dynamics of the Radical Anions Revealed by the Novel Time-Resolved Photofragment Depletion Spectroscopy
No full textExcited-state reaction dynamics of the radical anions have been investigated by a newly-developed time-resolved photofragment depletion (TRPD) spectroscopy where the different photodetachment cross-sections of the various anionic species during the reaction process were utilized to unravel their overall temporal evolutions. The otherwise formidable interrogation of the excited-state reaction dynamics of the radical anions, primarily due to the fact that their excited-states are often located above the electron detachment threshold, could be realized here. The shape of the excited-state potential energy surface of I2- has been clearly manifested in the TRPD transients taken at several different probe wavelengths, whereas the ultrafast internal conversion from the optically-excited nonvalence-bound state into the ground or excited valence-bound states of CH3NO2- or (CH3NO2)2-, which is followed by the fast chemical bond dissociation or the rather slow cluster decomposition, has been experimentally investigated for the first time to uncover the overall mechanism of the electron transfer dynamics among different (non)valence orbitals
Heterogenous Perfluorooctanoic Acid Degradation with Molecular Copper Electrocatalyst
No full textThe increasing emission of chemically resistant perfluorinated compounds (PFCs) into the natural environment, along with their global presence in natural and treated waters and in both human and animal organisms, presents a significant environmental challenge. A cost-effective method for the successful degradation of perfluorooctanoic acid (PFOA) in aqueous solutions is crucial. Electrochemical oxidation has been demonstrated to uniquely degrade PFOA. In this study, we present a molecular copper (I) complex, [CuT2]•ClO4, in a heterogeneous aqueous system capable of degrading PFOA by up to 84% with a defluorination rate of 91% through anodic oxidation using controlled current electrolysis (CCE). Furthermore, we utilized ESI/MS to identify the degradation products from the electrochemical oxidation of PFOA. The shortening of the PFOA chain results in reduced toxicity due to decreased persistence. Thus, the findings of this study show that the [CuT2]•ClO4 complex is an efficient catalyst for the degradation and defluorination of PFOA
Exploring the Influence of Approximations for Simulating Valence Excited X-ray Spectra
No full textFirst principles simulations of excited state X-ray spectra are becoming increasingly important to interpret the wealth of electronic and geometric information contained within femtosecond X-ray absorption spectra recorded at X-ray Free Electron Lasers (X-FELs). However, because the transition dipole matrix elements must be calculated between two excited states (i.e. the valence excited state and the final core-excited state arising from the initial valence excited state) of very different energies, this can be challenging and time-consuming to compute. Herein using two molecules, protonated formaldimine and cyclobutanone, we assess the ability of n-electron valence state perturbation theory (NEVPT2), equation-of-motion coupled cluster theory (EOM-CCSD), linear-response time-dependent density functional theory (LR-TDDFT) and the maximum overlap method (MOM) to describe excited state X-ray spectra. Our study focuses in particular on the behaviour of these methods away from the Franck-Condon geometry and in the vicinity of important topological features of excited-state potential energy surfaces, namely conical intersections. We demonstrate that the primary feature of excited state X-ray spectra is associated with the core electron filling the hole created by the initial valence excitation, a process that all the methods can capture. Higher-energy states are generally weaker and more sensitive to the nature of the reference electronic wavefunction. As molecular structures evolve away from the Franck-Condon geometry, changes in the spectral shape closely follow the underlying valence excitation, highlighting the importance of accurately describing the initial valence excitation to simulate the excited state X-ray absorption spectra
Naphtho[2,3-a]pyrene Thin Films – H,I, or J? Aggregate Alphabet Soup
No full textPhoton upconversion within the solid state has the potential to improve existing solar and imaging technologies due to its achievable efficiency at low power thresholds. However, despite considerable advancements in solution-phase upconversion, expanding the library of potential solid-state annihilators and developing a fundamental understanding of their solid-state behaviors remains challenging due to intermolecular couplings affecting the energy landscape. Naphtho[2,3-a]pyrene has shown promise as a suitable solid-state annihilator; however, the origin of the underlying emissive features remains unknown. To this point, here, we investigate NaPy/polymethylmethacrylate thin films at varying concentrations to tune the intermolecular coupling strength to determine its photophysical properties. The results suggest that the multiple emissive features present at room temperature arise from an I-aggregate (520 nm), an excimer (550 nm), and a strongly coupled J-dimer (620 nm)
Design, synthesis, and biological evaluation of novel azaspirooxindolinone derivatives as potent inhibitors of ITK and BTK-positive cancers
No full textBruton\u27s tyrosine kinase (BTK) and Interleukin-2-inducible T-cell kinase (ITK) are two important members of the Tec family with crucial roles in immune system function. Deregulation in ITK and BTK activity is linked to several hematological malignancies, making them key targets for cancer immunotherapy. In this study, we synthesized new azaspirooxindolinone derivatives and evaluated their cytotoxic activity against ITK/BTK-negative and -positive cancer cell lines. Compounds 3d and 3j exhibited high cytotoxicity in both ITK-positive Jurkat (IC50 = 3.58 µM and 4.16 µM, respectively) and BTK-positive Ramos (IC50 = 3.06 µM and 1.38 µM, respectively) cell lines, indicating their potential dual activity against ITK and BTK. 3a and 3e showed high cytotoxicity specifically in ITK-positive Jurkat cells with IC50 values of 9.36 µM and 10.85 µM, respectively. Compounds 3f and 3g were highly cytotoxic specifically in Ramos cells with IC50 values of 1.82 µM and 1.42 µM, respectively. None of the active compounds exhibited cytotoxic effects against non-cancer cell lines (IC50 > 50 µM). These findings suggest that the synthesized azaspirooxindolinone derivatives, particularly compounds 3d and 3j, hold promise as dual inhibitors for ITK and BTK-positive cancers, while compounds 3a, 3e, 3f, and 3g demonstrate potential as specific inhibitors, warranting further investigation
Fabrication of superhydrophilic membranes for oil-water separation: A life cycle assessment study
No full textMembrane-based technologies are widely used in oily wastewater treatment. This study selects two superhydrophilic ultrafiltration (UF) membranes (denoted M1 and M2) for oil-in-water emulsion separation and evaluates the environmental impact of membrane fabrication using life cycle assessment (LCA). Although the two membranes have similar separation performance, M1 exhibits ~40% lower environmental impacts than M2 in almost every category owing to its fewer modification steps, lower electricity use, and less solvent consumption. Electricity consumption, reactive-copolymer synthesis, and toxic-solvent use are identified as environmental hotspots in membrane fabrication. A sensitivity analysis of different energy sources reveals that coal-based electricity has the greatest environmental impact, while photovoltaic energy reduces the impact by up to 71%. Considering solvents, dimethylformamide (DMF) shows a slightly lower environmental impact than N-methyl-2-pyrrolidone (NMP)
Data Efficiency of Classification Strategies for Chemical and Materials Design
No full textActive learning and design-build-test-learn strategies are increasingly employed to accelerate materials discovery and characterization. Many data-driven materials design campaigns target solutions within constrained domains such as synthesizability, stability, solubility, recyclability, and toxicity. Lack of knowledge about these constraints can hinder design efficiency by producing samples that fail to meet required thresholds. Acquiring this knowledge during the design campaign is inefficient, and effective classification of common materials constraints transcends specific design objectives. However, there is no consensus on the most data-efficient algorithm for classifying whether a material satisfies a constraint. To address this gap, we comprehensively compare the performance of 100 strategies designed to classify chemical and materials behavior. Performance is assessed across 31 classification tasks sourced from the literature in chemical and materials science. From these results, we recommend best practices for building data-efficient classifiers, showing the neural network- and random forest-based active learning algorithms are most efficient across tasks. We also show that classification task complexity can be quantified based on task metafeatures, most notably the noise-to-signal ratio. Overall, this work provides a comprehensive survey of data-efficient classification strategies, identifies attributes of top-performing strategies, and suggests avenues for further study
Investigations of Enteric-Coated Propyl Gallate-induced Nephrotoxicity in Beagles and Human and Dog Renal Proximal Tubule Epithelial Cells
No full textPermeability plays a major role in oral biotherapeutic delivery and permeation enhancers can improve the intestinal permeability of poorly absorbed active pharmaceutical ingredients such as peptides. As part of nonclinical development of an oral formulation for a glucagon-like peptide-1 (GLP-1) receptor agonist, MEDI7219, toxicology studies revealed that one of the formulation excipients, propyl gallate (PG), when administered in enteric-coated tablets, led to nephrotoxicity in beagles. While PG has been widely used in food and cosmetics as an anti-oxidant, understanding of its toxicology, metabolism and disposition has been rarely discussed. To elucidate the nephrotoxicity observed after administration of PG in an enteric coated tablet formulation, we employed dog and human renal proximal tubule epithelial cells (RPTEC). We observed greater cytotoxicity to PG in dog RPTEC compared to human cells. We also observed greater increases in response to PG treatment of glutathione in human cells compared to dog cells. Glutathione elevation is a common response to detoxify xenobiotics, especially ones that produce free radicals such as PG. Thus, we hypothesize that glutathione in human RPTECs was elevated to detoxify PG, but not in dog RPTECs, leading to greater cytotoxicity for dog RPTECs. Furthermore, to characterize disposition and metabolism of PG in both humans and dogs we developed a 10-plex, highly sensitive and robust LC-MS/MS-based quantification method of PG and its phase-I and phase-II metabolites in dog and human plasma. The methods were employed to support clinical study (NCT03362593) and preclinical dog studies to evaluate safety, pharmacokinetics and tolerability of PG to support its use in an oral formulation for MEDI7219
Highly Efficient Red Multi-Resonant Thermally Activated Delayed Fluorescence Emitters as Bioimaging Reagents
No full textMulti-resonant thermally activated delayed fluorescence (MR-TADF) emitters have attracted strong interest for organic electroluminescent devices due to their high photoluminescence quantum yield (ΦPL) and superior narrowband emission, resulting in high color purity output in the device. These properties are also crucial for high-performance biological probes, especially red emitters. Orange and red MR-TADF emitters, PhDPA-DiKTa and MeODPA-DiKTa, were designed by decorating the DiKTa core with di([1,1’-biphenyl]-4-yl)amine (PhDPA) and bis(4-methoxyphenyl)amine (MeODPA). Both compounds emit at long wavelengths, with PL of 592 nm (full-width at half-maximum, FWHM = 45 nm) for PhDPA-DiKTa and 633 nm (FWHM= 72 nm) for MeODPA-DiKTa in toluene. As 5 wt% doped films in mCP, PhDPA-DiKTa emits at PL of 617 nm, while MeODPA-DiKTa emits at PL of 655 nm. Both show delayed fluorescence, with delayed lifetimes, td, of 658.4 and 249.2 s, respectively. Water-dispersible glassy organic dots (g-Odots) based on these materials were prepared by encapsulating them and mCP host into an amphiphilic DSPE-PEG2k polymer. Both families of g-Odots showed a deeper red emission and enhanced ΦPL compared to the corresponding 5 wt% doped films in mCP (PL = 618 nm, PL = 77% for PhDPA-DiKTa g-Odots, PL = 663 nm, PL = 38% for MeODPA-DiKTa g-Odots). The TADF character of the emitters was conserved in the g-ODots, with d of 203.9 s for PhDPA-DiKTa g-Odots and 131.6 s for MeODPA-DiKTa g-Odots. These MR-TADF g-Odots were successfully demonstrated as biological imaging probes of HeLa cells
Machine Learning for Microscopy Data Analysis: Toward Real-time Optical and Electrical Characterization of Sub-micron Materials
No full text(Micro)spectroscopy often generates various output signals due to intrinsic inhomogeneity of material arrangement at low dimensions or machinery drift, albeit the bulk composition and experimental parameters remain constant. In fact, such diversity can be harnessed to measure material’s purity, unveiling various concealed features via statistical inspection of heterogeneous signals acquired from several microscopy scans. However, the approach requires efficient categorization of a substantial number of signals, which is currently encumbered by
laborious calculations, computational hurdles, and manual intervention. This necessitates a programmed interface to perform time-efficient big data analytics, lack of which has perpetually widened the schism between laboratory and industrial-scale microscopy-based assessment of
nanomaterials. We present a robust technique - an unsupervised machine learning driven module for automatic clustering and class-wise power spectral density calculation of real-time microscopy signals. Our methodology has been tested across different aspects of wide-field fluorescence imaging and scanning tunnelling spectroscopy, demonstrating the versatility. Additionally, we investigated the impact of data-processing on the clustering efficiency and optimized the methodology. We anticipate that our futuristic workflow package for contemporary microscopes is the initial endeavor toward fast data analytics and instant
material characterization, spanning a diverse spectrum of interests