Nanocomposites have developed as cutting-edge materials with unique features ideal for use in electronics, energy storage, catalysis, and biomedical engineering. This study demonstrates how the physicochemical and interfacial characteristics of nanocomposite systems can be investigated using a variety of computer approaches. Atomistic insights into electrical structures and interfacial interactions can be obtained using techniques like Density Functional Theory (DFT). At bigger scales, molecular dynamics (MD) simulations are useful for studying diffusive, mechanical, and thermal phenomena. Furthermore, long-time-scale phenomena like dispersion and aggregation behavior can be studied using Monte Carlo simulations and coarse-grained modeling. Rapid screening and formulation optimization for nanocomposite materials are made possible by the growing adoption of machine learning methods for predictive modeling. The adaptability of nanocomposites across a range of domains has been proved by recent computational research. For example, DFT and molecular docking studies of B-CuO/rGO nanocomposites demonstrated their effective antibacterial potential and appropriate electrical characteristics for photocatalysis. Semi-interpenetrating nanocomposite hydrogels for bone tissue engineering have been optimized using machine learning, improving regeneration results through data-driven design. Graphene oxide nanosheets also showed good stability and bioactivity with a HOMO-LUMO gap of 2.806 eV. GQD–Pt(II) nanocomposites investigated through DFT show an improved photovoltaic performance for renewable energy production, with the electron-donating groups reaching energy conversion efficiencies up to 24.6%. These illustrations show how computational methods can direct material design, forecast structure–property connections, and foster innovation. Computational studies on nanocomposites constitute an engaging and developing field of study that has enormous potential for future technological breakthroughs and justifies more research because of its capacity to provide in-depth insights at low experimental costs.

The mechanical behavior of nanowires (NWs), nanotubes (NTs), and nanopillars is critical to advancing nanotechnology and developing nanoelectromechanical systems (NEMS). These nanostructures exhibit mechanical properties that are significantly different from their bulk counterparts due to their reduced dimensions and high surface-to-volume ratios. Nanowires exhibit remarkable elasticity and strength; for example, zinc oxide (ZnO) nanowires have demonstrated a Young’s modulus of approximately 76 GPa and a fracture strain of approximately 8%. The "smaller is stronger" phenomenon is prominent, where reducing nanowire diameters to below 100 nm often leads to strength values exceeding several GPa, compared to the MPa range typical for bulk materials. Carbon nanotubes, particularly single-walled carbon nanotubes (SWNTs), demonstrate extraordinary mechanical properties, with Young’s moduli exceeding 1 TPa and tensile strengths reaching up to 200 GPa. Multi-walled carbon nanotubes (MWNTs) also exhibit superior mechanical robustness, with tensile strengths ranging from 11 to 63 GPa, depending on the number of walls and structural defects. Diameter-dependent behaviors are observed, where nanotubes with diameters under 10 nm generally possess higher stiffness and strength due to minimized defect density and enhanced curvature effects. Nanotubes can also exhibit viscoelasticity under cyclic loading, with energy dissipation characteristics similar to biological tissues. Nanopillars, although less extensively studied, share a similar one-dimensional architecture and exhibit comparable mechanical characteristics. Compression tests on metallic nanopillars have demonstrated yield strengths exceeding 1 GPa, a significant enhancement over their bulk equivalents. Size-dependent strengthening and surface-mediated deformation mechanisms are key features influencing their mechanical responses. Embedding nanowires or nanotubes into polymer matrices can boost composite strength by over 200% compared to pristine polymers.

Rising levels of CO₂ emissions and the search for cleaner energy sources have led to the development of new catalytic systems that can convert CO₂ into useful products. One such chemical is methanol, a liquid fuel with a high energy density that plays an important role in the sustainable carbon cycle.

This work presents a theoretical study of subnanometer metal clusters (of up to five atoms) confined within MOF cavities as catalyst models for CO₂ hydrogenation. The investigation includes not only methanol formation but also the potential formation of other C1 products, such as carbon monoxide and formic acid.

For this purpose, cluster@MOF systems are first designed, and their most stable geometries are identified to serve as starting points for reaction modeling. The DFT molecular dynamics (DFT-MD) method is used to study both the binding of the clusters within the MOF and the CO₂ adsorption. This is followed by investigation of all of the reaction steps, their characterization, and the construction of an energy profile. Transition state validation is performed using the intrinsic reaction coordinate (IRC) method. Detailed study of the structure–function relationships in the proposed catalytic systems will enable an understanding of the reaction mechanisms and optimization of the active site within the cluster@MOF system.

With the theoretical design of new functionalized fluorophores for solar energy harvesting, it is possible to obtain systems with desirable properties such as sharp and intense absorption, emissions in the near-infrared region, a high fluorescent quantum yield efficiency, and a transparent window within the visible region. The aim of this work is to study the influence of structural changes on the photochemical properties of squaraine dyes.

Reliable predictions of the properties of their radiative and non-radiative rates, fluorescent lifetime, and quantum yield require the vibrational structure of the studied systems to satisfy the harmonic approximation. We employ a time-dependent density functional formalism (TDDFT) to compute the excited-state properties, spectra, and radiative and non-radiative rates, with the implicitly described solvent effect included throughout the calculations. These systems were modeled using a combination of DFT and TDDFT methods to obtain accurate ground- and excited-state properties relevant to photophysical analyses.

For the investigated indolenine-based squaraine dyes, their trans- and cis-configuration, as well as their substitution into active sites, or structurally sensitive aggregation, can influence their spectral behavior, such as shifting towards the red spectral region or transparency at higher excited states. In addition, a comparison of the theoretically predicted and experimentally measured results is presented.

This lecture delves into the distinctive optical and electronic characteristics of metal nanoclusters (NCs), with a specific focus on luminescent noble metal NCs, through two interconnected research avenues:

1. Luminescent Noble Metal Nanoclusters for Solar Energy Applications.

2. Noble Metal Nanoclusters in Biomedical Applications.

In the pursuit of advancing photovoltaic technology beyond conventional silicon and emerging perovskite solar cells, Grätzel et al. pioneered the dye-sensitized solar cell (DSSC). This line of investigation integrates natural pigments like carotenoids with noble metal NCs to form bio–nano hybrids. These bio-inspired luminescent materials hold the potential to enhance light absorption, charge transfer efficiency, and overall stability in next-generation photovoltaic systems. Computational quantum chemistry tools, notably Density Functional Theory (DFT) and Time-Dependent Density Functional Theory (TD-DFT), play pivotal roles in designing advanced nanomaterials for DSSCs, aiming to enhance their efficiency and durability. The strategy involves harnessing the optical properties of noble metal nanoclusters (such as gold and silver) in synergy with environmentally sourced organic dyes. Our research group has developed a theoretical framework focused on enhancing anthocyanins' properties by employing the donor–acceptor concept. This involves binding dye molecules with noble metal nanoclusters to form complex bio–nano hybrids (Dye@NC), optimizing their adsorption on TiO2 surfaces. Beyond solar energy applications, noble metal nanoclusters are gaining prominence in medical diagnostics, imaging, and sensing due to their unique quantum effects and exceptional optical properties. This lecture highlights the interdisciplinary approach merging photophysics and photochemistry with materials science and nanotechnology to explore the potential of luminescent noble metal nanoclusters in advancing both solar energy conversion technologies and biomedical applications.

Diverse systems, including lanthanides (Ln; from La to Lu), are attracting increasing attention, particularly in the research and development of magnetic and luminescent materials. Among versatile lanthanide-based materials, lanthanide nitride cluster fullerenes (Ln₃N@C₈₀) and bisphthalocyanines (LnPc₂) have emerged as promising candidates for advanced applications such as spintronic devices.

The formation of hybrids or dyads of carbon nanomaterials (graphene and carbon nanotubes) with LnPc₂ enhances magnetic properties due to synergy between components. The Ln₃N@C₈₀ + LnPc₂ dyads remain underexplored. So far, only different macrocycles, such as porphyrins, have been reported to crystallize endohedral fullerenes (EFs). This interaction can alter EFs' structures; however, the extent to which they can achieve this is unclear.

We performed DFT characterization to investigate structural and electronic changes in noncovalently interacting lanthanide (Ln = La, Ce, Gd, Lu) nitride cluster fullerenes and bisphthalocyanines forming Ln₃N@C₈₀ + LnPc₂ dyads. Optimized geometries, formation and frontier orbital energies, HOMO-LUMO plots, the charge and spin of Ln and N(Ln₃N@C₈₀) atoms, and spin density plots were analyzed relative to isolated Ln₃N@C₈₀ and LnPc₂.

Spin distribution is among the most influenced properties in these interactions. Changes are more evident in dyads with Ce and Gd than their La and Lu counterparts. The interaction of Ce₃N@C₈₀ and Gd₃N@C₈₀ with CePc₂ and GdPc₂ redistributes spin density, altering spin-up and spin-down electron orientations in encapsulated Ce₃N and Gd₃N clusters. This behavior could enable tuning of magnetic properties, enhancing their performance as Single-Molecule Magnets in spintronic and magnetic devices

Four thiophene-based organic molecules, H1-H4, featuring diverse thiophene central cores, triphenylamine side groups, and amide bridges, were designed as D-π-A-π-D type hole-transporting materials (HTMs) for use in perovskite solar cells (PSCs).

According to our findings, the proposed and produced HTMs demonstrated outstanding coherence in terms of charge carrier transit, dispersion, and excitation qualities that are perfectly suitable for strong hole mobility. The findings reveal that acceptor moieties functionalized HTMs exhibit minimal optical absorption in the visible portion with negligible overlap with the active perovskite layer, indicating suitable optoelectronic and photophysical profiles of effective HTMs. Additionally, the results demonstrate excellent band alignment with the active perovskite layer with fitting HOMO energy levels.

This result is comparable to state-of-the-art materials, such as Spiro-OMeTAD, in a similar comparison. Cost estimates indicate that the material cost is approximately an order of magnitude lower for EDOT-OMeTPA (HR), resulting in a negligible contribution to the peak cost per watt of USD 0.004 W⁻¹. Furthermore, the high synthetic accessibility of EDOT-OMeTPA also reduces the use of toxic chemicals, thereby significantly reducing its environmental impact. Our results pave the way towards low-cost, environmentally friendly, and efficient HTMs.

Finally, our findings provide a molecular-level understanding of creating new HTM design strategies for enhanced photovoltaic features. To achieve higher efficacy, thiophene-based HTMs are intended to be incorporated into upcoming solar cell technologies

Lead-free perovskite solar cells have attracted global research interest due to their tunable band gaps, optical properties, and environmental friendliness. In this work, we computationally studied KSnI₃ perovskite solar cells. This was achieved by investigating the impact of using LiTiO₂, ZnO, SnO₂, and AlZnO as electron transport layers coupled with rGO as a hole transport layer. The optimization of the thicknesses and dopant densities of individual layers yielded PCEs of 27.60%, 24.94%, 27.62%, and 30.44% for of FTO/Al-ZnO/KSnI₃/rGO/Se, FTO/LiTiO₂/KSnI₃/rGO/Se, FTO/ZnO/KSnI₃/rGO/Se, and FTO/SnO₂/KSnI₃/rGO/Se solar cell configurations, respectively. Thus, our FTO/SnO₂/KSnI₃/rGO/Se device is almost 8 % more efficient than FTO/SnO₂/3C-SiC/KSnI₃/NiO/C, which is currently the most efficient KSnI₃ perovskite solar cell structure in the literature. Thus, our FTO/SnO₂/KSnI₃/rGO/Se perovskite solar cell structure is now, by far, the most efficient PSC design. Its best performance is achieved under ideal conditions of zero series resistance, shunt resistance of 10⁷ Ω cm², and a temperature of 371 K. In this presentation, I will reveal the details of the aforementioned results and how the approach used in this study can be applied, in future studies, not only to other perovskite solar cells, but also to other types of solar cells such as solid-state dye-sensitized solar cells to significantly improve their efficiency.

In this study, sodium- and strontium-modified bismuth titanate—Bi_0.5Sr_0.5TiO₃ and Bi_0.5Na_0.5TiO₃ (BNT and BST)—have been prepared via the autocombustion technique. Fuels (C₆H₈O₇ and C₂H₅NO₂) were added in an optimized ratio of 1.5:1 during preparation. The samples were characterized using X-ray diffractometer (XRD), energy dispersive (EDX) spectroscopy, UV–visible absorbance and FT-IR spectroscopy. The electrical behaviour of the samples calcinated at 950℃ was studied using an LCR meter. The synthesized samples presented a perovskite structure with an average crystallite size in the range of 10–25 nm. This variation in crystallite size may be due to the difference in ionic radii of Na and Sr. The lattice constant and volume of the unit cell increased with an increase in crystallite size. Furthermore, the Williamson Hall graph was plotted by utilizing XRD data. The EDX studies revealed that pure Na⁺ and Sr²⁺ incorporated with bismuth titanate were prepared without any trace of impurities. The optical properties were subsequently determined, capturing a sharp absorbance peak at a wavelength of 339.5 nm for BNT and 345.9 nm for BST. Tauc’s relation was adopted to measure the energy bandgap (E_g): 2.5eV and 2.00eV for Na- and Sr-doped bismuth titanate. The absorption band observed at 420cm^-1 to 720cm^-1 in FT-IR studies represented the presence of the Ti-O bond and confirmed the structure. To perform electrical characterization, the powder samples were transformed into pellets by applying a pressure of 3 tonnes and sintering at 1000℃ for 3 hours. The dielectric constant (Ꜫ_r) and the tangent loss (δ) of the prepared pellet samples were found to increase at higher frequency. The ac conductivity (σ) of both the BNT and BST samples was also measured. Through the realization of structural, optical and electrical efficiency, the optimized samples demonstrate potential for application in energy storage devices.

Memristors are considered promising passive nanoelectronic components for next-generation non-volatile memory applications. Non-stoichiometric rutile (TiO_2-x) exhibits a memristive effect caused by the migration of oxygen vacancies under an applied electric field. Additionally, oxygen vacancies can act as mediators of long-range ferromagnetic order in oxide semiconductors doped with magnetic 3D ions, such as Co:TiO_2-x. For the first time, we propose combining the memristive properties of Co:TiO_2-x with its ferromagnetic properties to create a novel non-volatile memory cell–magnetic memristor for nanoelectronic and spintronic applications.

Single-crystalline (001)-rutile TiO₂ plates were implanted with 40 keV cobalt or argon ions at ion fluences of (0.3-1.5)×10¹⁷ ions/cm², an ion flux of 2–10 μA/cm², and a substrate temperature of 900 K. Then strip- or rectangular-type memory cells with dimensions of 100-800 μm were fabricated on Co-ion-implanted rutile samples using electron-beam lithography and ion-beam deposition of gold contacts.

The lithographic samples of magnetic memristors were characterized using current-voltage measurements, optical microscopy, vibrating sample magnetometry (VSM), and magneto-optic Kerr effect (MOKE) measurements at room temperature.

Current-voltage characterization identified samples optimal for repeated cyclic oxygen vacancy migration and memristive effect observation. Real-time monitoring in strip lithographic cells determined the average flow rate of positively charged vacancies at various applied voltages. Both VSM and MOKE measurements show a strong influence of oxygen vacancy content on magnetization and magneto-optical response (MOKE). After the electromigration of oxygen vacancies in lithographic cells of Co:TiO_2-x samples, the MOKE signal became 2-3 times stronger in vacancy-rich regions of cells compared to the initial state or drop nearly to zero in vacancy-depleted regions of cells.

Moreover, for the first time, we demonstrate the fundamental possibility of writing information bits by applying voltage pulses to the fabricated lithographic memory cells, while simultaneously reading data via the registration of magneto-optical responses in cells.