A definition of the magnetic transition temperature using valence bond theory

Macroscopic magnetic properties are analyzed using Valence Bond theory. Commonly the critical temperature TC for magnetic systems is associated with a maximum in the energy-based heat capacity Cp(T). Here a more broadly applicable definition of the magnetic transition temperature TC is described using spin moment expectation value (i.e. applying the spin exchange density operator) instead of energy. Namely, the magnetic capacity Cs(T) reflects variation in the spin multiplicity as a function of temperature, which is shown to be related to ∂[χT(T)]/∂T. Magnetic capacity Cs(T) depends on long-range spin interactions that are not relevant in the energy-based heat capacity Cp(T). Differences between Cs(T) and Cp(T) are shown to be due to spin order/disorder within the crystal, that can be monitored via a Valence Bond analysis of the corresponding magnetic wavefunction. Indeed the concept of the Boltzmann spin-alignment order is used to provide information about the spin correlation between magnetic units. As a final illustration, the critical temperature is derived from the magnetic capacity for several molecular magnets presenting different magnetic topolo- gies that have been experimentally studied. A systematic shift between the transition temperatures associated with Cs(T) and Cp(T) is observed. It is demonstrated that this shift can be attributed to the loss of long-range spin correlation. This suggests that the magnetic capacity Cs(T) can be used as a predictive tool for the magnetic topology, and thus for the synthetic chemists

Pitfalls on evaluating pair exchange interactions for modelling molecule-based magnetism

Molecule-based magnetism is a solid-state property that results from the microscopic interaction between magnetic centres or radicals. The observed magnetic response is due to unpaired electrons whose coupling leads to a particular magnetic topology. Therefore, to understand the magnetic response of a given molecule-based magnet and reproduce the available experimental magnetic properties by means of statistical mechanics, one has to be able to determine the value of the JAB magnetic exchange coupling between radicals. The calculation of JAB is thus a key point for modelling molecule-based magnetism. In this Perspectives article, we will build upon our experience in modelling molecular magnetism to point out some pitfalls on evaluating JAB couplings. Special attention must be paid to the cluster models used to evaluate JAB, which should account for cooperative effects among JAB interactions and also consider the environment (counterions, hydrogen bonding) of the two radicals whose interaction has to be evaluated. It will be also necessary to assess whether a DFT-based or a wavefunction-based method is best to study a given radical. Finally, in addition to model and method, the JAB couplings have to be able to adapt to changes in the magnetic topology due to thermal fluctuations. Therefore, it is most important to appraise in which systems molecular dynamics simulations would be required. Given the large number of issues one must tackle when choosing the correct model and method to evaluate JAB interactions for modelling magnetic properties in molecule-based materials, the “human factor” is a must to cross-examine and challenge computations before trusting any result

Electronic Descriptors for Supervised Spectroscopic Predictions

Spectroscopic properties of molecules holds great importance for the description of the molecular response under the effect of an UV/Vis electromagnetic radiation. Computationally expensive ab initio (e.g. MultiConfigurational SCF, Coupled Cluster) or TDDFT methods are commonly used by the quantum chemistry community to compute these properties. In this work, we propose a (supervised) Machine Learning approach to model the absorption spectra of organic molecules. Several supervised ML methods have been tested such as Kernel Ridge Regression (KRR), Multiperceptron Neural Networs (MLP) and Convolutional Neural Networks. The use of only geometrical descriptors (e.g. Coulomb Matrix) proved to be insufficient for an accurate training. Inspired on the TDDFT theory, we propose to use a set of electronic descriptors obtained from low-cost DFT methods: orbital energy differences, transition dipole moment between occupied and unoccupied Kohn-Sham orbitals and charge-transfer character of mono-excitations. We demonstrate that with this electronic descriptors and the use of Neural Networks we can predict not only a density of excited states, but also getting very good estimation of the absorption spectrum and charge-transfer character of the electronic excited states, reaching results close to the chemical accuracy (~2 kcal/mol or ~0.1eV)

A basic electro-topological descriptor for the prediction of organic molecule geometries by simple machine learning

This paper proposes a machine learning (ML) method to predict stable molecular geometries from their chemical composition. The method is useful for generating molecular conformations which may serve as initial geometries for saving time during expensive structure optimizations by quantum mechanical calculations of large molecules. Conformations are found by predicting the local arrangement around each atom in the molecule after trained from a database of previously optimized small molecules. It works by dividing each molecule in the database into minimal building blocks of different type. The algorithm is then trained to predict bond lengths and angles for each type of building block using an electro-topological fingerprint as descriptor. A conformation is then generated by joining the predicted blocks. Our model is able to give promising results for optimized molecular geometries from the basic knowledge of the chemical formula and connectivity. The method trends to reproduce interatomic distances within test blocks with RMSD under 0.05

Revising the common understanding of metamagnetism in the molecule-based bisdithiazolyl BDTMe compound

The BDTMe molecule-based material is the first example of a thiazyl radical to exhibit metamagnetic behavior. Contrary to the common idea that metamagnetism occurs in low-dimensional systems, it is found that BDTMe magnetic topology consists of a complex 3D network of almost isotropic ferromagnetic spin-ladders that are coupled ferromagnetically and further connected by some weaker antiferromagnetic interactions. Calculated magnetic susceptibility χT(T) data is in agreement with experiment. Calculated M(H) data clearly show the typical sigmoidal shape of a metamagnet at temperatures below 2 K. The calculated critical field becomes more apparent in the dM/dH(H) plot, being in very good agreement with experiment. Our computational study concludes that the magnetic topology of BDTMe is preserved throughout the entire experimental range of temperatures (0–100 K). Accordingly, the ground state is the same irrespective of the temperature at which we study the BDTMe crystal. Revising the commonly accepted understanding of a metamagnet explained as ground state changing from antiferromagnetic to ferromagnetic, the Boltzmann population of the different states is here suggested to be the key concept: at 2 K the ground singlet state has more weight (24%) than at 10 K (1.5%), where excited states have an important role. Changes in the antiferromagnetic interactions that couple the ferromagnetic skeleton of BDTMe will directly affect the population of the distinct states that belong to a given magnetic topology and thus its magnetic response. Accordingly, this strategy could be valid for a wide range of bisdithiazolyl BDT-compounds whose magnetism can be tuned by means of weak antiferromagnetic interactions

Pitfalls on evaluating pair exchange interactions for modelling molecule-based magnetism

Molecule-based magnetism is a solid-state property that results from the microscopic interaction between magnetic centres or radicals. The observed magnetic response is due to unpaired electrons whose coupling leads to a particular magnetic topology. Therefore, to understand the magnetic response of a given molecule-based magnet and reproduce the available experimental magnetic properties by means of statistical mechanics, one has to be able to determine the value of the J(AB) magnetic exchange coupling between radicals. The calculation of J(AB) is thus a key point for modelling molecule-based magnetism. In this Perspectives article, we will build upon our experience in modelling molecular magnetism to point out some pitfalls on evaluating J(AB) couplings. Special attention must be paid to the cluster models used to evaluate J(AB), which should account for cooperative effects among J(AB) interactions and also consider the environment (counterions, hydrogen bonding) of the two radicals whose interaction has to be evaluated. It will be also necessary to assess whether a DFT-based or a wavefunction-based method is best to study a given radical. Finally, in addition to model and method, the J(AB) couplings have to be able to adapt to changes in the magnetic topology due to thermal fluctuations. Therefore, it is most important to appraise in which systems molecular dynamics simulations would be required. Given the large number of issues one must tackle when choosing the correct model and method to evaluate J(AB) interactions for modelling magnetic properties in molecule-based materials, the "human factor" is a must to cross-examine and challenge computations before trusting any result.MD, JRA, and JJN acknowledge financial support from MINECO (CTQ2017-87773-P/AEI/FEDER, UE), Spanish Structures Excellence Maria de Maeztu program (MDM-2017-0767), and Catalan DURSI (2017SGR348)

Covalent C–N Bond Formation through a Surface Catalyzed Thermal Cyclodehydrogenation

The integration of substitutional dopants at predetermined positions along the hexagonal lattice of graphene-derived polycyclic aromatic hydrocarbons is a critical tool in the design of functional electronic materials. Here, we report the unusually mild thermally induced oxidative cyclodehydrogenation of dianthryl pyrazino[2,3-g]quinoxalines to form the four covalent C–N bonds in tetraazateranthene on Au(111) and Ag(111) surfaces. Bond-resolved scanning probe microscopy, differential conductance spectroscopy, along with first-principles calculations unambiguously confirm the structural assignment. Detailed mechanistic analysis based on ab initio density functional theory calculations reveals a stepwise mechanism featuring a rate determining barrier of only ΔE⧧ = 0.6 eV, consistent with the experimentally observed reaction conditions

Pitfalls on evaluating pair exchange interactions for modelling molecule-based magnetism

Molecule-based magnetism is a solid-state property that results from the microscopic interaction between magnetic centres or radicals. The observed magnetic response is due to unpaired electrons whose coupling leads to a particular magnetic topology. Therefore, to understand the magnetic response of a given molecule-based magnet and reproduce the available experimental magnetic properties by means of statistical mechanics, one has to be able to determine the value of the JAB magnetic exchange coupling between radicals. The calculation of JAB is thus a key point for modelling molecule-based magnetism. In this Perspectives article, we will build upon our experience in modelling molecular magnetism to point out some pitfalls on evaluating JAB couplings. Special attention must be paid to the cluster models used to evaluate JAB, which should account for cooperative effects among JAB interactions and also consider the environment (counterions, hydrogen bonding) of the two radicals whose interaction has to be evaluated. It will be also necessary to assess whether a DFT-based or a wavefunction-based method is best to study a given radical. Finally, in addition to model and method, the JAB couplings have to be able to adapt to changes in the magnetic topology due to thermal fluctuations. Therefore, it is most important to appraise in which systems molecular dynamics simulations would be required. Given the large number of issues one must tackle when choosing the correct model and method to evaluate JAB interactions for modelling magnetic properties in molecule-based materials, the "human factor" is a must to cross-examine and challenge computations before trusting any result

Octopus, a computational framework for exploring light-driven phenomena and quantum dynamics in extended and finite systems

Over the last few years, extraordinary advances in experimental and theoretical tools have allowed us to monitor and control matter at short time and atomic scales with a high degree of precision. An appealing and challenging route toward engineering materials with tailored properties is to find ways to design or selectively manipulate materials, especially at the quantum level. To this end, having a state-of-the-art ab initio computer simulation tool that enables a reliable and accurate simulation of light-induced changes in the physical and chemical properties of complex systems is of utmost importance. The first principles real-space-based Octopus project was born with that idea in mind, i.e., to provide a unique framework that allows us to describe non-equilibrium phenomena in molecular complexes, low dimensional materials, and extended systems by accounting for electronic, ionic, and photon quantum mechanical effects within a generalized time-dependent density functional theory. This article aims to present the new features that have been implemented over the last few years, including technical developments related to performance and massive parallelism. We also describe the major theoretical developments to address ultrafast light-driven processes, such as the new theoretical framework of quantum electrodynamics density-functional formalism for the description of novel light-matter hybrid states. Those advances, and others being released soon as part of the Octopus package, will allow the scientific community to simulate and characterize spatial and time-resolved spectroscopies, ultrafast phenomena in molecules and materials, and new emergent states of matter (quantum electrodynamical-materials)

Octopus, a computational framework for exploring light-driven phenomena and quantum dynamics in extended and finite systems

Over the last few years, extraordinary advances in experimental and theoretical tools have allowed us to monitor and control matter at short time and atomic scales with a high degree of precision. An appealing and challenging route toward engineering materials with tailored properties is to find ways to design or selectively manipulate materials, especially at the quantum level. To this end, having a state-of-the-art ab initio computer simulation tool that enables a reliable and accurate simulation of light-induced changes in the physical and chemical properties of complex systems is of utmost importance. The first principles real-space-based Octopus project was born with that idea in mind, i.e., to provide a unique framework that allows us to describe non-equilibrium phenomena in molecular complexes, low dimensional materials, and extended systems by accounting for electronic, ionic, and photon quantum mechanical effects within a generalized time-dependent density functional theory. This article aims to present the new features that have been implemented over the last few years, including technical developments related to performance and massive parallelism. We also describe the major theoretical developments to address ultrafast light-driven processes, such as the new theoretical framework of quantum electrodynamics density-functional formalism for the description of novel light–matter hybrid states. Those advances, and others being released soon as part of the Octopus package, will allow the scientific community to simulate and characterize spatial and time-resolved spectroscopies, ultrafast phenomena in molecules and materials, and new emergent states of matter (quantum electrodynamical-materials).This work was supported by the European Research Council (Grant No. ERC-2015-AdG694097), the Cluster of Excellence “Advanced Imaging of Matter” (AIM), Grupos Consolidados (IT1249-19), and SFB925. The Flatiron Institute is a division of the Simons Foundation. X.A., A.W., and A.C. acknowledge that part of this work was performed under the auspices of the U.S. Department of Energy at Lawrence Livermore National Laboratory under Contract No. DE-AC52-07A27344. J.J.-S. gratefully acknowledges the funding from the European Union Horizon 2020 Research and Innovation Program under the Marie Sklodowska-Curie Grant Agreement No. 795246-StrongLights. J.F. acknowledges financial support from the Deutsche Forschungsgemeinschaft (DFG Forschungsstipendium FL 997/1-1). D.A.S. acknowledges University of California, Merced start-up funding.Peer reviewe