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Upconversion photodynamic therapy (UC-PDT), which integrates upconversion nanoparticles (UCNPs) with photosensitizers (PSs), presents a promising advancement in the field of phototherapy. However, despite the extensive studies focused on the design and synthesis of UCNPs, there is a paucity of systematic research on the mechanisms underlying the synergistic upconversion photodynamic effects. Here we have synthesized upconversion core@dotted-shell nanoparticles (CDSNPs) and covalently tethered them with two distinct PSs, thereby constructing a dual-PS UC-PDT system with high synergistic photodynamic performance. To unravel the mechanism underlying the synergism, we employed a combination of quantum mechanical calculations and ultrafast time-resolved spectroscopy techniques. The results indicate that rare earth oxides play a pivotal role in enhancing the intersystem crossing processes of PSs through modulating their excited electronic states. Additionally, Förster resonance energy transfer between two distinct PSs contributes to the amplification of triplet state populations, thus further enhancing the photodynamic effect. experiments demonstrate that the prepared CDSNPs based dual-PS system exhibits excellent biocompatibility with normal cells and exceptional synergistic photodynamic efficacy against tumor cells upon near-infrared excitation. This research contributes theoretical insights into the design and application of multi-photosensitizer UC-PDT systems, laying the groundwork for more efficient preclinical implementations in the future.

We investigate theoretically the design and application of nine triazine (Tr)-core star-shaped molecules built with thiophene (Th), phenyl (Ph), and carbazole (Cz) moieties in dye-sensitized solar cells (DSSCs) and bulk heterojunction (BHJ) organic solar cells. Density functional theory and time-dependent density functional theory are employed to rationalize the electronic structure, charge transfer properties, and photovoltaic performance of these systems. Tr-Th-Cz and Tr-Ph- p -Th-Cz display power conversion efficiency ( PCE ) values close to 30% due to a favorable alignment of the energy levels. Computed open-circuit voltage values show that lack of π-bridges, as in the Tr-Th and Tr-Cz, favor higher voltage generation. Systems containing thiophene (Th) and carbazole (Cz) present the most favorable values for efficient electron injection and dye regeneration. Furthermore, the incorporation of these Th and Cz donor substituents into the triazine core combined with π-bridges significantly impacts other optoelectronic properties of the organic solar cells. The computed high singlet–triplet gap values indicate limited potential of these molecules as thermally activated delayed fluorescence (TADF) emitters for applications in organic light-emitting diodes (OLEDs).

The efficiency of photovoltaic solar cells (PSCs) heavily relies on hole-transport materials (HTMs). Understanding the intricate relationship between structure and properties is pivotal in crafting effective HTMs. In this study a set of 4 new organic molecules were strategically crafted using different core and π-linkers to analyze their role as potential novel HTMs. We delve into understanding and investigate how their structures influence the electronic, optical, and hole-transport properties of designed HTMs using DFT and TDDFT methodology. The efficacy of the newly designed molecules is assessed across multiple dimensions, encompassing frontier molecular orbitals, absorption spectra, hole mobility, electrostatic potential (ESP), transition density matrix, density of states, reorganization energy (RE), binding energy (BE), dipole moment stability etc., providing a comprehensive evaluation of their performance. The calculated properties are further compared with well known HTM spiro-OMeTAD. Results indicate that three out of the four analyzed compounds can serve as preferential HTM candidate for PSC device as a consequence of narrow band gap, small excitation energy, low RE of hole, good stability and low binding energy. Our ESP results suggest that achieving planarity between the core and the linking phenyl group within the triphenylamine moiety is crucial for enhancing charge transport efficiency and elevating the optical and electronic characteristics of the investigated HTMs. This study provides crucial insights for the deliberate and effective design of high-performance HTMs.

In this work, we present a computational investigation on the photoexcitation of indigo carmine (IC). Physical insights regarding IC photoexcitation and photolysis were obtained from a fundamental perspective through quantum chemistry computations. Density functional theory (DFT) was used to investigate the ground state while its time-dependent formalism (TD-DFT) was used for probing excited state properties, such as vertical excitation energies, generalized oscillator strengths (GOS), and structures. All the computations were undertaken using two different approaches: M06-2X/6-311+G(d,p) and CAM-B3LYP/6-311+G(d,p), in water. Results determined using both methods are in systematic agreement. For instance, the first singlet excited state was found at 2.28 eV (with GOS = 0.4730) and 2.19 eV (GOS = 0.4695) at the TD-DFT/CAM-B3LYP/6-311+G(d,p) and TD-DFT/M06-2X/6-311+G(d,p) levels of theory, respectively. Excellent agreement was observed between the computed and the corresponding experimental UV-Vis spectra. Moreover, results suggest IC undergoes photodecomposition through excited state chemical reaction rather than via a direct photolysis path. To the best of our knowledge, this work is the first to tackle the photoexcitation, and its potential connections to photodegradation, of IC from a fundamental chemical perspective, being presented with expectations to motivate further studies.

Strong correlations within a symmetry-unbroken ground-state wavefunction can show up in approximate density functional theory as symmetry-broken spin densities or total densities, which are sometimes observable. They can arise from soft modes of fluctuations (sometimes collective excitations) such as spin-density or charge-density waves at nonzero wavevector. In this sense, an approximate density functional for exchange and correlation that breaks symmetry can be more revealing (albeit less accurate) than an exact functional that does not. The examples discussed here include the stretched H₂ molecule, antiferromagnetic solids, and the static charge-density wave/Wigner crystal phase of a low-density jellium. Time-dependent density functional theory is used to show quantitatively that the static charge-density wave is a soft plasmon. More precisely, the frequency of a related density fluctuation drops to zero, as found from the frequency moments of the spectral function, calculated from a recent constraint-based wavevector- and frequency-dependent jellium exchange-correlation kernel.

The appropriate catalysts can accelerate the reaction rate and effectively boost the efficient conversion of various molecules, which is of great importance in the study of chemistry, chemical industry, energy, materials and environmental science. Therefore, efficient, environmentally friendly, and easy to operate synthesis methods have been used to prepare various types of catalysts. Although previous studies have reported the synthesis and characterization of the aforementioned catalysts, more still remain in trial and error methods, without in-depth consideration and improvement of traditional synthesis methods. Here, we comprehensively summarize and compare the preparation methods of the trial-and-error synthesis strategy, structure-activity relationships and density functional theory (DFT) guided catalysts rational design for nanomaterials and atomically dispersed catalysts. We also discuss in detail the utilization of the nanomaterials and single atom catalysts for converting small molecules (H 2 O, O 2 , CO 2 , N 2 , etc.) into value-added products driven by electrocatalysis, photocatalysis, and thermocatalysis. Finally, the challenges and outlooks of mass preparation and production of efficient and green catalysts through conventional trial and error synthesis and DFT theory are featured in accordance with its current development.

Generally, it is difficult to generate a high-performance pure blue emission organic light-emitting diode (OLED). That is because the intrinsically wide band-gap makes it hard to inject charges into the emitting layer in such devices. To solve the problem, carbazole derivatives have been widely used because they have more thermal stability, a good hole transporting property, more electron rich (p-type) material, and higher photoconductivity. In the present work, novel copolymers containing donor-acceptor-acceptor-donor (D-A-A-D) blue compounds used for OLEDs were investigated. The theory of the geometrical and electronic properties of N-ethylcarbazole (ECz) as donor molecule (D) coupled to a series of 6 acceptor molecules (A) for advanced OLEDs were investigated. The acceptors were thiazole (TZ), thiadiazole (TD), thienopyrazine (TPZ), thienothiadiazole (TTD), benzothiadiazole (BTD), and thiadiazolothienopyrazine (TDTP). The ground state structure of the copolymers were studied using Density Functional Theory (DFT) at B3LYP/6-31G(d) level. Molecular orbital analysis study indicated 3 investigated copolymers (ECz-diTZ-ECz, ECz-diTD-ECz, ECz-diBTD-ECz) have efficient bipolar charge transport properties for both electron and hole injection to the TiO2 conduction band (4.8 eV). In addition, the excited states electronic properties were calculated using Time-Dependent Density Functional Theory (TD-DFT) at the same level. Among these investigated copolymer ECz-diTZ-ECz and ECz-diTD-ECz showed the maximum absorption wavelengths (λabs) with blue emitting at 429 and 431 nm, respectively. The results suggested that selected D-A-A-D copolymers can improve the electron- and hole- transporting abilities of the devices. Therefore, the designed copolymers would be a promising material for future development of light-emitting diodes, electrochromic windows, photovoltaic cells, and photorefractive materials.

Recent advances in experimental and computational methods are increasing the quantity and complexity of generated data. This massive amount of raw data needs to be stored and interpreted in order to advance the materials science field. Identifying correlations and patterns from large amounts of complex data is being performed by machine learning algorithms for decades. Recently, the materials science community started to invest in these methodologies to extract knowledge and insights from the accumulated data. This review follows a logical sequence starting from density functional theory as the representative instance of electronic structure methods, to the subsequent high-throughput approach, used to generate large amounts of data. Ultimately, data-driven strategies which include data mining, screening, and machine learning techniques, employ the data generated. We show how these approaches to modern computational materials science are being used to uncover complexities and design novel materials with enhanced properties. Finally, we point to the present research problems, challenges, and potential future perspectives of this new exciting field.

Density functional theory (DFT) simulations of the oxygen evolution reaction (OER) are considered essential for understanding the limitations of water splitting. Most DFT calculations of the OER use an acidic reaction mechanism and the standard hydrogen electrode (SHE) as reference electrode. However, experimental studies are usually carried out under alkaline conditions using the reversible hydrogen electrode (RHE) as reference electrode. The difference between the conditions in experiment and calculations is then usually taken into account by applying a pH-dependent correction factor to the latter. As, however, the OER reaction mechanisms under acidic and under alkaline conditions are quite different, it is not clear a priori whether a simple correction factor can account for this difference. We derive in this paper step by step the theory to simulate the OER based on the alkaline reaction mechanism and explain the OER process with this mechanism and the RHE as reference electrode. We compare the mechanisms for alkaline and acidic OER catalysis and highlight the roles of the RHE and the SHE. Our detailed analysis validates current OER simulations in the literature and explains the differences in OER calculations with acidic and alkaline mechanisms.

This study investigates the efficacy of adsorbents from locally sourced olive waste—encompassing olive skins, leaves, and pits, recovered from the initial centrifugation of olives (OWP)—and a composite with sodium alginate (OWPSA) for the removal of Cu[sup.2+] ions from synthetic wastewater. Experimental analyses conducted at room temperature, with an initial Cu[sup.2+] concentration of 50 mg/L and a solid/liquid ratio of 1 g/L, showed that the removal efficiencies were approximately 79.54% and 94.54% for OWP and OWPSA, respectively, highlighting the positive impact of alginate on adsorption capacity. Utilizing statistical physics isotherm models, particularly the single-layer model coupled to real gas (SLMRG), allowed us to robustly fit the experimental data, providing insights into the adsorption mechanisms. Thermodynamic parameters affirmed the spontaneity and endothermic nature of the processes. Adsorption kinetics were interpreted effectively using the pseudo-second-order (PSO) model. Molecular modeling investigations, including the conductor-like screening model for real solvents (COSMO-RS), density functional theory (DFT), and atom-in-molecule (AIM) analysis, unveiled intricate molecular interactions among the adsorbent components—cellulose, hemicellulose, lignin, and alginate—and the pollutant Cu[sup.2+], confirming their physically interactive nature. These findings emphasize the synergistic application of experimental and theoretical approaches, providing a comprehensive understanding of copper adsorption dynamics at the molecular level. This methodology holds promise for unraveling intricate processes across various adsorbent materials in wastewater treatment applications.