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This first-principles study investigates the interactions between amino acids and various types of montmorillonite clay surfaces, including a pristine surface, a surface with an oxygen vacancy, a surface with a silicon vacancy, and an Fe-doped surface. Our results show that all clay surfaces exhibit negative binding energies, indicating that the interaction between clay and amino acids is thermodynamically favorable. Among them, the surface with a Si vacancy displays the most negative binding energy, corresponding to the strongest interaction. We also examine the reactions between two alanine molecules to form a dipeptide molecule through the elimination of a water molecule in the absence of clay surfaces. The transition state search suggests that a proton transfer plays a critical role in the peptide bond formation based on structural and energetic features observed along the reaction path. Circular dichroism spectra computed for reactant, intermediate, and product states show distinct chiral signatures. Wave packet dynamics calculations indicate that quantum tunneling might be the mechanism underlying the reduced activation energy at low temperatures. These findings offer insight into the physicochemical processes at clay–amino acid interfaces and support the design of clay-based materials with applications in biotechnology and prebiotic chemistry. 

This study investigates the adsorption mechanism of CO3^(2−) on the (111) surface of tricalcium silicate (C3S) using density functional theory simulations. Two distinct adsorption configurations were identified: a tilted alignment with localised bonding to Ca ions and concentrated charge transfer, and a parallel orientation with delocalised interactions involving multiple Ca ions. Charge density analysis revealed charge transfer from the surface to the carbonate molecule, with electron accumulation around oxygen atoms of CO3^(2−). Partial density of states analysis showed significant changes near the Fermi level after adsorption, indicating the formation of new bonding states. Molecular dynamics simulations demonstrated that the tilted configuration stabilises the surface by reducing Ca ion mobility, while the parallel configuration leads to increased ion mobility and higher surface reactivity. These findings emphasise the importance of site-specific interactions and electronic structure changes in understanding CO2 mineralisation mechanisms in cementitious materials. 

The efficiency of silicon solar cells is affected by the light absorption and recombination losses of photoexcited charge carries. One possible way to improve the efficiency is through the deposition of transition metal nanoparticles on Si surfaces. Here, we first carry out density functional theory (DFT) calculations to obtain electronic structures for Agn (n = 1–7) monolayered clusters adsorbed on Si(111)/H surfaces. Results are presented in the form of the density of states, band gaps, and light absorption, which allow for the investigation of the interaction of Ag clusters with Si. Different behaviors can be expected depending on the size of the deposited Ag clusters. Overall, the deposition of Ag clusters leads to smaller band gaps, red-shifts, and large increases in light absorption compared to the pristine Si slab. We then study the relaxation dynamics of electron–hole pairs for slabs based on nonadiabatic couplings using the reduced density matrix approach within the Redfield formalism. Nonradiative relaxation rates are noticeably different for various structures and transitions. One observes higher relaxation rates for surfaces with adsorbates than for the pristine Si surface due to charge transfer events involving Ag orbitals. We also compute emission spectra from excited-state relaxation dynamics. The band gap emission is dark for the pristine Si due to the indirect nature of its band gap. The addition of larger Ag clusters breaks the symmetry of Si slabs, enabling indirect gap transitions. These slabs thus exhibit bright band gap emission. The introduction of adsorbates is advantageous for applications in photovoltaics and photocatalysis. 

The optical properties of the tetragonal phase of BaTiO₃have been studied using density functional methods, applying the generalized gradient approximation at room temperature and a hybrid functional for static lattice analysis. 

Organic color centers (OCCs), generated by the covalent functionalization of single-walled carbon nanotubes, have been exploited for chemical sensing, bioimaging, and quantum technologies. However, monovalent OCCs can assume at least 6 different bonding configurations on the sp2 carbon lattice of a chiral nanotube, resulting in heterogeneous OCC photoluminescence emissions. Herein, we show that a heat-activated [2 + 2] cycloaddition reaction enables the synthesis of divalent OCCs with a reduced number of atomic bonding configurations. The chemistry occurs by simply mixing enophile molecules (e.g., methylmaleimide, maleic anhydride, and 4-cyclopentene-1,3-dione) with an ethylene glycol suspension of SWCNTs at elevated temperature (70–140 °C). Unlike monovalent OCC chemistries, we observe just three OCC emission peaks that can be assigned to the three possible bonding configurations of the divalent OCCs based on density functional theory calculations. Notably, these OCC photoluminescence peaks can be controlled by temperature to decrease the emission heterogeneity even further. This divalent chemistry provides a scalable way to synthesize OCCs with tightly controlled emissions for emerging applications. 

Semiconducting conjugated polymers (CPs) are pivotal in advancing organic electronics, offering tunable properties for solar cells and field-effect transistors. Here, we carry out first-principle calculations to study individual cis-polyacetylene (cis-PA) oligomers and their ensembles. The ground electronic structures are obtained using density functional theory (DFT), and excited state dynamics are explored by computing nonadiabatic couplings (NACs) between electronic and nuclear degrees of freedom. We compute the nonradiative relaxation of charge carriers and photoluminescence (PL) using the Redfield theory. Our findings show that electrons relax faster than holes. The ensemble of oligomers shows faster relaxation compared to the single oligomer. The calculated PL spectra show features from both interband and intraband transitions. The ensemble shows broader line widths, redshift of transition energies, and lower intensities compared to the single oligomer. This comparative study suggests that the dispersion forces and orbital hybridizations between chains are the leading contributors to the variation in PL. It provides insights into the fundamental behaviors of CPs and the molecular-level understanding for the design of more efficient optoelectronic devices. 

Inorganic mixed-halogen perovskites exhibit excellent photovoltaic properties and stability; yet, their photoelectric conversion efficiency is limited by inherent surface defects. In this work, we study the impact of defects on properties of CsPbI2Br slabs using first-principles calculations, focusing on specific defects such as I vacancy (VI), I interposition (Ii), and I substitution by Pb (PbI). Our findings reveal that these defects affect the geometric and optoelectronic properties as well as dynamics of charge carriers of slabs. We employ two theoretical frameworks (surface hopping and Redfield theory) of nonadiabatic molecular dynamics simulations to comprehensively study relaxation processes and obtain consistent results. The presence of VI reduces carrier lifetimes, while the influence of PbI on carrier lifetimes is negligible. In contrast, Ii defects lead to prolonged carrier lifetimes. These insights provide valuable guidance for the rational design of perovskite photovoltaic devices, aiming to enhance their efficiency and stability. 

The development of reusable polymeric materials inspires an attempt to combine renewable biomass with upcycling to form a biorenewable closed system. It has been reported that 2,5-furandicarboxylic acid (FDCA) can be recovered for recycling when incorporated as monomers into photodegradable polymeric systems. Here, we develop a procedure to better understand the photodegradation reactions combining density functional theory (DFT) based time-dependent excited-state molecular dynamics (TDESMD) studies with machine learning-based quantitative structure–activity relationships (QSAR) methodology. This procedure allows for the unveiling of hidden structural features between active orbitals that affect the rate of photodegradation and is coined InfoTDESMD. Findings show that electrotopological features are influential factors affecting the rate of photodegradation in differing environments. Additionally, statistical validations and knowledge-based analysis of descriptors are conducted to further understand the structural features’ influence on the rate of photodegradation of polymeric materials. 

An exploration of the “on-the-fly” nonadiabatic couplings (NACs) for nonradiative relaxation and recombination of excited states in 2D Dion–Jacobson (DJ) lead halide perovskites (LHPs) is accelerated by a machine learning approach. Specifically, ab initio molecular dynamics (AIMD) of nanostructures composed of heavy elements is performed with the use of machine-learning force-fields (MLFFs), as implemented in the Vienna Ab initio Simulation Package (VASP). The force field parametrization is established using on-the-fly learning, which continuously builds a force field using AIMD data. At each time step of the molecular dynamics (MD) simulation, the total energy and forces are predicted based on the MLFF and if the Bayesian error estimate exceeds a threshold, an ab initio calculation is performed, which is used to construct a new force field. Model training of MLFF and evaluation were performed for a range of DJ-LHP models of different thicknesses and halide compositions. The MLFF-MD trajectories were evaluated against pure AIMD trajectories to assess the level of discrepancy and error accumulation. To examine the practical effectiveness of this approach, we have used the MLFF-based MD trajectories to compute NAC and excited-state dynamics. At each stage, results based on machine learning are compared to traditional ab initio based electronic dissipative dynamics. We find that MLFF-MD provides comparable results to AIMDs when MLFF is trained in an NPT ensemble. 

Two-dimensional organic–inorganic hybrid lead halide perovskites are of interest for photovoltaic and light emitting devices due to their favorable properties that can be tuned. Here we use density functional theory to model two-dimensional lead halide perovskites of different thicknesses and using two different hallogens. Excited-state optoelectronic properties of the perovskite models are examined using excited-state dynamics treated by reduced density matrix method. Nonadiabatic couplings were computed based on the on-the-fly approach along a molecular dynamics trajectory at ambient temperatures. The density matrix-based equation of motion for electronic degrees of freedom was used to determine the dynamics of electronic degrees of freedom. We observe that the thickness of the perovskite layer shows a redshift in the absorption spectra with increasing thickness but has minimal effect on the photoluminescence quantum yield of the material.