Organic-based magnetic materials have attracted significant attention in recent years, particularly in the domain of spintronics. However, in order to realize viable spintronic-based technologies, high temperature coupling is a necessity. Understanding the physical exchange mechanisms that underpin the observed ordering in magnetic materials provides an effective tool to engage with this issue. In this report, a decomposition methodology is adopted to analyze the coupling in two metal phthalocyanine systems-cobalt (II) phthalocyanine (CoPc) and copper (II) phthalocyanine (CuPc)-and to extract the contributing exchange interactions. A dimeric molecular geometry is used to approximate the periodic chain structure, and the exchange interactions between the two magnetic centers are examined. The results of the study offer a more comprehensive insight into the physical mechanism underlying the observed exchange interactions and reveal the relationship between the electronic configuration and emergent magnetic properties of each respective system. More specifically, the coupling in CoPc is shown to be attributable to a dominant kinetic exchange interaction arising from the single occupation of a dz2-derived a1g molecular orbital, while in CuPc, an indirect spin polarization mechanism is found to underpin the weak exchange interaction. This study, therefore, demonstrates the validity of applying the decomposition methodology to a dimeric system and highlights its importance as a powerful tool to investigate the physical nature of magnetic interactions in molecular magnets.

In molecular crystals, many solid state phase transitions can be attributed to the entropy of intermolecular vibrations at low frequencies, where the weak noncovalent interactions dominate, and simulations based on density functional theory (DFT) suffer from relatively large errors. In this work, the precision of two critical computational parameters are evaluated, namely the choice of local basis set and (DFT-based) Hamiltonian. Each is documented in detail for the vibrational properties and thermodynamic stability of two polymorphs of paracetamol, which are chosen due to the representative chemical interactions and the good availability of high-quality reference data. Comparisons are made with experimentally measured low-temperature geometries, Raman spectra, and temperature-pressure phase diagrams. These results highlight the substantial influences of basis set, revealing the importance of both the cardinality (i.e., ζ) and the diffuseness; the failure to account for either factor might lead to unexpected results. The features of low-frequency vibrations that most significantly affect the relative stability of molecular crystals are identified and shown to be captured when the triple-ζ def2-TZVP basis set is adopted; on the contrary, widely used double-ζ basis sets are shown to be inadequate. The improvement attributed to the inclusion of Fock exchange is revealed to be marginal, especially with triple-ζ basis sets. By systematically improving levels of precision, the current work disentangles competing sources of errors impeding accurate crystal structure predictions and polymorph energy rankings. This facilitates the predictability and reliability of DFT in thermodynamic modeling of molecular crystals.

The morphology of molecular crystals depends strongly on both thermodynamic stability and the growth kinetics which are themselves dependent on the fine details of intermolecular interactions and challenging to model with ab initio methods. Here, the combination of density functional theory with the effective screen medium-reference interaction site model (DFT/ESM-RISM) is used to study the fast regrowth of a form I paracetamol crystal post-breakage, recently reported by [Bade et al., Mater. Horiz., 2023, 10, 1425-1430]. It is demonstrated that both the thermodynamic and the kinetic factors affecting regrowth are successfully captured by DFT/ESM-RISM with relatively low computational costs. With inclusion of all the externally observed facets, the morphology predicted from thermodynamic considerations alone is found to agree well with observation. Deviation from this morphology is predicated upon inclusion into the model of the fast-growing internal (010) plane, indicating the strong influence of kinetic effects on morphology. The paracetamol molecules at the surface are characterised by unsaturated hydrogen bonds; the resultant strong interaction with the solutes and the solvent significantly altering surface thermodynamics and the structure of the near-surface solvent. For example, the competition between ethanol and solvated paracetamol molecules for the formation of hydrogen bonds is found to reduce the growth rate due to steric hindrance. This effect becomes less prominent for the (010) surface, which presents no broken hydrogen bonds, resulting in a more uniform near-surface solvent structure that facilitates surface growth. As the first attempt to investigate the complicated solid-liquid interface of molecular crystals, this study broadens the applicability of DFT/ESM-RISM. The kinetic mechanisms underpinning the fast regrowth of form I paracetamol post-breakage are qualitatively elucidated, suggesting new strategies for efficient morphology control in molecular crystals.

The integration of graphene with other 2D materials has been extensively studied over the past decade to realize high-performance devices unattainable with single materials. Graphene-transition metal dichalcogenides (TMDCs) such as MoS2, WS2, MoSe2, and WSe2 vertical heterostructures have demonstrated promise in numerous electronic and optoelectronic applications due to the wide bandgap range and strong light-matter interaction in TMDCs, and the ability to form electrostatically tunable junctions with graphene. However, conventional methods for TMDCs growth, including chemical vapor deposition (CVD), electrodeposition, and atomic layer deposition (ALD), require high temperatures, which can degrade graphene's electrical and structural properties. Here, we investigate the impact of sulfur annealing on graphene, revealing significant etching and electrical degradation. Density functional theory (DFT) calculations identify the divacancy defect with two sulfur adatoms (DV-2S) and C-S-C bonds as the dominant defect, differing from the previously reported monovacancy with one sulfur adatom (MV-1S). This defect induces p-doping in graphene, consistent with experimental observations. To address these challenges, we introduce a protective strategy utilizing self-assembled monolayers (SAMs) during annealing, enabling the growth of high-quality WS2 on graphene via electrodeposition. Our findings provide a foundation for integrating TMDCs with graphene while preserving its properties, advancing high-performance electronic and optoelectronic applications.

In spintronics, a perennial goal has been the generation of organic spin-bearing semiconductor materials with magnetic ordering stable at room temperature. To this end, the class of transition metal phthalocyanines has shown much promise in fulfilling this ambition. In particular, alpha-phase cobalt (II) phthalocyanine (α-CoPc) exhibits strong antiferromagnetic exchange interactions producing a long range order up to ∼100 K. However, the underlying mechanism by which this magnetic interaction proceeds is not well understood. In this report, a simple mechanism has been proposed based on the Hubbard Hamiltonian, which elucidates the exchange coupling in α-CoPc. The mechanism provides stipulations for increasing the magnetic coupling, and this directs to a proposal that substitution of the central cobalt ion for rhodium will lead to a significant increase in coupling strength. The strength of this exchange interaction has been evaluated using broken symmetry hybrid exchange density functional theory and indicates that the novel rhodium (II) phthalocyanine system is indeed predicted to exhibit significantly stronger magnetic ordering. This study, therefore, identifies the coupling mechanism in α-CoPc as primarily attributable to kinetic exchange, explains its previously reported strong coupling relative to its first-row transition metal counterparts, and suggests that rhodium (II) phthalocyanine is likely to exhibit stable magnetic ordering at room temperature.

BiVO4 is one of the most promising light absorbing materials for use in photoelectrochemical (PEC) water splitting devices. Although intrinsic BiVO4 suffers from poor charge carrier mobility, this can be overcome by Mo-doping. However, for Mo-doped BiVO4 to be applied in commercial PEC water splitting devices, scalable routes to high performance materials need to be developed. Herein, we propose a scalable aerosol-assisted chemical vapour deposition (AA-CVD) route to high performance Mo-doped BiVO4. The materials were characterised using X-ray diffraction (XRD), Raman spectroscopy, X-ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM), atomic force microscopy (AFM), UV-visible absorption spectroscopy, and a range of PEC tests. By studying a range of Mo-precursor doping levels (0 to 12% Mo : V), an optimum precursor doping level was found (6% Mo : V); substituting V5+ sites in the host structure as Mo6+. In PEC water oxidation the highest performing material showed an onset of photocurrent (J(on)) at similar to 0.6 V-RHE and a theoretical solar photocurrent (TSP) of similar to 1.79 mA cm(-2) at 1.23 V-RHE and 1 sun irradiance. Importantly, Mo-doping was found to induce a phase change from monoclinic clinobisvanite (m-BiVO4), found in undoped BiVO4, to tetragonal scheelite (t-BiVO4). The effect of Mo-doping on the phase stability, structural and electronic properties was examined with all-electron hybrid exchange density functional theory (DFT) calculations. Doping into V and Bi sites at 6.25 and 12.5 at% was calculated for t-BiVO4 and m-BiVO4 phases. In accord with our observations, 6.25 at% Mo doping into the V sites in t-BiVO4 is found to be energetically favoured over doping into m-BiVO4 (by 2.33 meV per Mo atom inserted). The computed charge density is consistent with n-doping of the lattice as Mo6+ replaces V5+ generating an occupied mid-gap state similar to 0.4 eV below the conduction band minimum (CBM) which is primarily of Mo-4d character. Doubling this doping level to 12.5 at% in t-BiVO4 resulted in the mid-gap state merging with the CBM and the formation of a degenerate semiconductor with electrons distributed over the 3d orbitals of V ions residing in the [001] plane. In conjunction with our experimental findings, this strongly suggests that it is the increased electron conductivity due to Mo doping of BiVO4 that produces a more active photoanode for water splitting, and that this maximises between 6.25 to 12.5 at% doping.

An understanding of the anomalously enhanced hydrogen evolution reaction (HER) of magnesium (Mg) under anodic polarisation in aqueous corrosion is paramount for a predictive theory of its corrosion and metal electrocatalysis. Previous theoretical and experimental studies have proposed that sub-surface hydride phases play a role in this behaviour but the underlying atomic mechanisms remain unclear. By constructing theoretical surface Pourbaix diagrams, based on density functional theory (DFT) calculations, we have identified the atomic structure of a sub-surface hydride phase on the Mg (0001) surface that remains electrochemically stable under significant anodic overpotentials across a wide pH range. Specifically, this stability persists up to 0.38 VSHE under mildly alkaline conditions (e.g., pH = 8), thus providing thermodynamic support for the proposed hydride-enhanced HER under anodic conditions. Reaction barrier analysis establishes that the proposed sub-surface hydride phase could promote anodic HER via a Heyrovsky pathway, based on hydrogen outward diffusion, with an energy barrier of 1.54 eV as the rate-limiting step, showing an anodic characteristic and significantly favouring external anodic polarisation. Furthermore, we have established that the surface adsorption condition, contingent on both the pH and potential, significantly influences the mechanism and kinetics of the initial corrosion of Mg.

Perovskite oxides, renowned for their adaptable structure and optoelectronic characteristics, hold significant potential for applications in catalysis and photoelectrochemical processes. This research investigates the preparation of praseodymium iron oxide (PrFeO3) by spin coating and the impact of incorporating a calcium (Ca) dopant on its photoelectrochemical efficacy as photocathodes. Spin coating of a polymer containing sol‐gel yielded thin films with uniform morphology and porosity, facilitating effective semiconductor/electrolyte interactions, as characterised by scanning electron microscopy analyses. Evaluation of transient photocurrent responses revealed that introducing Ca at a 5 at% doping level significantly enhanced the photoelectrochemical activity of PrFeO3, resulting in an optimal photocurrent of ‐124 µA cm‐2 at +0.43 VRHE under simulated sunlight conditions. This enhancement was accompanied by an incident photon‐to‐current efficiency of 3.8% at +0.43 VRHE and 350 nm, along with an onset potential of +1.1 VRHE. Ultraviolet and visible spectroscopy analyses indicated an increase in light absorption capabilities in the Ca‐doped films and a noticeable reduction in bandgap compared to the undoped counterparts, further supported by incident photon‐to‐current efficiency measurements. The findings underscore the significant role of dopants in augmenting the photocurrent performance of stable perovskite oxides, highlighting their potential in advancing photon conversion technologies. This article is protected by copyright. All rights reserved.

Understanding hydrogen-metal interactions is important in various fields of surface science, including the aqueous corrosion of metals. The interaction between atomic H and a Mg surface is a key process for the formation of sub-surface Mg hydride, which may play an important role in Mg aqueous corrosion. In the present work, we performed first-principles Density Functional Theory (DFT) calculations to study the mechanisms for hydrogen adsorption and crystalline Mg hydride formation under aqueous conditions. The Electron Localisation Function (ELF) is found to be a promising indicator for predicting stable H adsorption in the Mg surface. It is found that H adsorption and hydride layer formation is dominated by high ELF adsorption sites. Our calculations suggest that the on-surface adsorption of atomic H, OH radicals and atomic O could enhance the electron localisation at specific sites in the sub-surface region, thus forming effective H traps locally. This is predicted to result in the formation of a thermodynamically stable sub-surface hydride layer, which is a potential precursor of the crucial hydride corrosion product of magnesium.

CRYSTALpytools is an open source Python project available on GitHub that implements a user-friendly interface to the Crystal code for quantum-mechanical condensed matter simulations. CRYSTALpytools provides functionalities to: i) write and read Crystal input and output files for a range of calculations (single-point, electronic structure, geometry optimization, harmonic and quasi-harmonic lattice dynamics, elastic tensor evaluation, topological analysis of the electron density, electron transport, and others); ii) extract relevant information; iii) create workflows; iv) post-process computed quantities, and v) plot results in a variety of styles for rapid and precise visual analysis. Furthermore, CRYSTALpytools allows the user to translate Crystal objects (the central data structure of the project) to and from the Structure and Atoms objects of the pymatgen and ASE libraries, respectively. These tools can be used to create, manipulate and visualise complicated structures and write them efficiently to Crystal input files. Jupyter Notebooks have also been developed for the less Python savvy users to guide them in the use of CRYSTALpytools through a user-friendly graphical interface with predefined workflows to complete different specific tasks.

A family of boron nitride (BN)-based photocatalysts for solar fuel syntheses have recently emerged. Studies have shown that oxygen doping, leading to boron oxynitride (BNO), can extend light absorption to the visible range. However, the fundamental question surrounding the origin of enhanced light harvesting and the role of specific chemical states of oxygen in BNO photochemistry remains unanswered. Here, using an integrated experimental and first-principles-based computational approach, we demonstrate that paramagnetic isolated OB3 states are paramount to inducing prominent red-shifted light absorption. Conversely, we highlight the diamagnetic nature of O-B-O states, which are shown to cause undesired larger band gaps and impaired photochemistry. This study elucidates the importance of paramagnetism in BNO semiconductors and provides fundamental insight into its photophysics. The work herein paves the way for tailoring of its optoelectronic and photochemical properties for solar fuel synthesis.

Controlling molecular spin quantum bits optically offers the potential to effectively reduce decoherence and raise the working temperature of quantum computers. Here, exchange interactions and spin dynamics, as mediated by an optically driven triplet state, are calculated for a molecule that consists of a pair of radicals and represents a potential quantum-circuit building block. Consistent with the previous experimental observation of spin coherence induced by the triplet state, our work demonstrates an optically driven quantum gate operation scheme in a molecule. A technological blueprint combining a two-dimensional molecular network and programmable nanophotonics, both of which are sufficiently developed, is proposed. We thus realize computational exploration of chemical databases to identify suitable candidates for molecular spin quantum bits and couplers to be hybridized with nanophotonic devices. The work presented here is proposed to realize a new approach for exploring molecular excited states and click chemistry, toward advancing molecular quantum technology.

Ab initio calculations have been employed to elucidate the habit and surface reactivity of iron carbonate crystals, which are a major component of corrosion scales formed in sweet solutions. The habit is environment dependent, varying from rhombohedral to micro-facetted cylinders with trigonal pyramidal caps as a function of iron activity. Consistent with modelling, the cap facets are shown to be (104) surfaces through a combination of EBSD and confocal microscopy. Furthermore, it is concluded that reactivity is facet dependent, with the (104) surface being relatively inert. These observations have the potential to initiate new approaches to corrosion control and prediction.

In many engineering scenarios, surface-active organic species are added to acidic solutions to inhibit the corrosion of metallic components. Given suitable selection, such corrosion inhibitors are highly effective, preventing significant degradation even in highly aggressive environments. Nevertheless, there are still considerable gaps in fundamental knowledge of corrosion inhibitor functionality, severely restricting rational development. Here, we demonstrate the capability of X-ray photoelectron spectroscopy (XPS), supported by ab initio modelling, for revealing key details of inhibited substrates. Attention is focussed on the corrosion inhibition of carbon steel through the addition of an exemplar imidazoline-based corrosion inhibitor (OMID) to aqueous solutions of both HCl and H2SO4. Most notably, it is demonstrated that interfacial chemistry varies with the identity of the acid. High resolution Fe 2p, O 1s, N 1s, and Cl 2p XPS spectra, acquired from well-inhibited carbon steel in 1 M HCl, show that there are two different singly protonated OMID species bound directly to the metallic carbon steel substrate. In sharp contrast, in 0.01 M H2SO4, OMID adsorbs onto an ultra-thin surface film, composed primarily of a ferric sulfate (Fe2(SO4)3)-like phase. Such insight is essential to efforts to develop a mechanistic description of corrosion inhibitor functionality, as well as knowledge-based identification of next generation corrosion inhibitors.

A molecular level understanding of metal/bulk water interface structure is key for a wide range of processes, including aqueous corrosion, which is our focus, but their buried nature makes experimental investigation difficult and we must mainly rely on simulations. We investigate the Mg(0001)/water interface using second generation Car-Parrinello molecular dynamics (MD) to gain structural information, combined with static density functional theory calculations to probe the atomic interactions and electronic structure (e.g., calculating the potential of zero charge). By performing detailed structural analyses of both metal-surface atoms and the near-surface water, we find that, among other insights: (i) water adsorption causes significant surface roughening (the planar distribution for top-layer Mg has two peaks separated by ≈0.6Å), (ii) strongly adsorbed water covers only ≈14 of available surface sites, and (iii) adsorbed water avoids clustering on the surface. Static calculations are used to gain a deeper understanding of the structuring observed in MD. For example, we use an energy decomposition analysis combined with calculated atomic charges to show that adsorbate clustering is unfavorable due to Coulombic repulsion between adsorption site surface atoms. Results are discussed in the context of previous simulations carried out on other metal/water interfaces. The largest differences for the Mg(0001)/water system appear to be the high degree of surface distortion and the minimal difference between the metal work function and metal/water potential of zero charge (at least compared to other interfaces with similar metal-water interaction strengths). The structural information, in this paper, is important for understanding aqueous Mg corrosion, as the Mg(0001)/water interface is the starting point for key reactions. Furthermore, our focus on understanding the driving forces behind this structuring leads to important insights for general metal/water interfaces.

The electronic and spintronic properties of the monovacancies in freestanding and isotopically compressed graphene are investigated using hybrid exchange density functional perturbation theory. When the effects of electronic self-interaction are taken into account, an integer magnetic moment of 2 μB is identified for a Jahn-Teller reconstructed V1(5-9) monovacancy in freestanding graphene. For graphene with stable ripples induced by a compressive strain of 5%, a bond reconstruction produces a V1(55-66) structure for the monovacancy, which is localized at the saddle points of the ripple. The sizeable local distortion induced by reconstruction modifies both the geometric and electronic properties of rippled graphene and quenches the magnetic moment of the vacancy due to the sp3 hybridization of the central atom. The nonmagnetic V1(55-66) structure is found to be stable on rippled structures, with the formation energy ∼2.3 eV lower than that of the metastable distorted V1(5-9) structures localized at sites other than the saddle points. The electronic ground state of distorted V1(5-9) corresponds to a wide range of fractional magnetic moments (0.50-1.25 μB). The computed relative stabilities and the electronic and magnetic properties of the V1(5-9) structures are found to be closely related to their local distortions. This analysis of the fundamental properties of defective graphene under compression suggests a number of strategies for generating regular defect patterns with tuneable magnetic and electronic properties and may, therefore, be used as a novel technique to achieve more precise control of graphene electronic structure for various application scenarios such as transistors, strain sensors, and directed chemisorption.

Well designed and optimized epitaxial heterostructures lie at the foundation of materials development for photovoltaic, photocatalytic, and photoelectrochemistry applications. Heterostructure materials offer tunable control over charge separation and transport at the same time preventing recombination of photogenerated excitations at the interface. Thus, it is of paramount importance that a detailed understanding is developed as the basis for further optimization strategies and design. Oxides of copper are nontoxic, low cost, abundant materials with a straightforward and stable manufacturing process. However, in individual applications, they suffer from inefficient charge transport of photogenerated carriers. Hence, in this work, we investigate the role of the interface between epitaxially aligned CuO and Cu2O to explore the potential benefits of such an architecture for more efficient electron and hole transfer. The CuO/Cu2O heterojunction nature, stability, bonding mechanism, interface dipole, electronic structure, and band bending were rationalized using hybrid density functional theory calculations. New electronic states are identified at the interface itself, which are originating neither from lattice mismatch nor strained Cu-O bonds. They form as a result of a change in coordination environment of CuO surface Cu2+ cations and an electron transfer across the interface Cu1+-O bond. The first process creates occupied defect-like electronic states above the valence band, while the second leaves hole states below the conduction band. These are constitutional to the interface and are highly likely to contribute to recombination effects competing with the improved charged separation from the suitable band bending and alignment and thus would limit the expected output photocurrent and photovoltage. Finally, a favorable effect of interstitial oxygen defects has been shown to allow for band gap tunability at the interface but only to the point of the integral geometrical contact limit of the heterostructure itself.

The effect of zeolite pore geometry and intrinsic acidity on the activation energy of propane monomolecular cracking was investigated for six topologically distinct zeolites with different pore sizes. Periodic density functional theory calculations were used to calculate the activation energy, while cluster models were used to calculate deprotonation energies. The computed intrinsic activation energies showed a smaller variation with topology than the adsorption energies. No correlation was found between the computed deprotonation and ammonia adsorption energies at the acid site and the intrinsic activation energy. Detailed analysis of the computed structures and properties suggests that acid sites with different pore topologies impose geometrical constraints on the ion-pair formed by the ammonium molecule, which differs significantly from those that affect the propane reaction.

Surface adsorption is one of the fundamental processes in numerous fields, including catalysis, the environment, energy and medicine. The development of an adsorption model which provides an effective prediction of binding energy in minutes has been a long term goal in surface and interface science. The solution has been elusive as identifying the intrinsic determinants of the adsorption energy for various compositions, structures and environments is non-trivial. We introduce a new and flexible model for predicting adsorption energies to metal substrates. The model is based on easily computed, intrinsic properties of the substrate and adsorbate, which are the same for all the considered systems. It is parameterised using machine learning based on first-principles calculations of probe molecules (e.g., H2O, CO2, O2, N2) adsorbed to a range of pure metal substrates. The model predicts the computed dissociative adsorption energy to metal surfaces with a correlation coefficient of 0.93 and a mean absolute error of 0.77 eV for the large database of molecular adsorption energies provided by Catalysis-Hub.org which have a range of 15 eV. As the model is based on pre-computed quantities it provides near-instantaneous estimates of adsorption energies and it is sufficiently accurate to eliminate around 90% of candidates in screening study of new adsorbates. The model, therefore, significantly enhances current efforts to identify new molecular coatings in many applied research fields.

The description of adsorption to surfaces and interfaces is essential in many technological fields, such as catalysis, corrosion and friction. For example, an accurate prediction of the structure and properties of molecules on substrates is essential to both the design and optimisation of coatings used to protect and enhance the properties of metals. We introduce a new model for the prediction of adsorption energies of molecules to metal substrates. The model is based on easily computed, intrinsic properties of the substrate and molecules (e.g., bulk cohesive energy, work function, molecule-cluster binding and the molecular orbital energy gap). It is parameterised by combining ab initio calculations with machine learning algorithms. The model is trained using a small set of probe molecules (e.g., H$_2$O, CO$_2$, O$_2$, N$_2$) adsorbed to a range of pure metal substrates. The model predicts the computed dissociative adsorption energy to metal surfaces with a correlation coefficient of 0.93 and a mean absolute error of 0.77 eV for the large database of molecular adsorptions stored in the this http URL database. The model therefore significantly enhances current efforts to identify new molecular coatings in many research fields and thus facilitates the discovery of new environmentally friendly and inexpensive materials with specific adhesion characteristics.