Beyond Single-Reference Fixed-Node Approximation in Ab Initio Diffusion Monte Carlo Using Antisymmetrized Geminal Power Applied to Systems with Hundreds of Electrons.

Diffusion Monte Carlo (DMC) is an exact technique to project out the ground state (GS) of a Hamiltonian. Since the GS is always bosonic, in Fermionic systems, the projection needs to be carried out while imposing antisymmetric constraints, which is a nondeterministic polynomial hard problem. In practice, therefore, the application of DMC on electronic structure problems is made by employing the fixed-node (FN) approximation, consisting of performing DMC with the constraint of having a fixed, predefined nodal surface. How do we get the nodal surface? The typical approach, applied in systems having up to hundreds or even thousands of electrons, is to obtain the nodal surface from a preliminary mean-field approach (typically, a density functional theory calculation) used to obtain a single Slater determinant. This is known as single reference. In this paper, we propose a new approach, applicable to systems as large as the C60 fullerene, which improves the nodes by going beyond the single reference. In practice, we employ an implicitly multireference ansatz (antisymmetrized geminal power wave function constraint with molecular orbitals), initialized on the preliminary mean-field approach, which is relaxed by optimizing a few parameters of the wave function determining the nodal surface by minimizing the FN-DMC energy. We highlight the improvements of the proposed approach over the standard single-reference method on several examples and, where feasible, the computational gain over the standard multireference ansatz, which makes the methods applicable to large systems. We also show that physical properties relying on relative energies, such as binding energies, are affordable and reliable within the proposed scheme.

Signature of low-dimensional quasi-F centers in zirconium-rich electrides.

Electrides are a class of materials consisting of non-nuclear excess electrons as quasi-F centers or Farbe centers within a positively charged lattice framework, and have significant applications in the fields of electrochemistry, spintronics, and electrode materials. Using first-principles quantum mechanical calculations, we have demonstrated exotic electronic structures of zirconium-rich electrides, Zr2X (X = O, Se, and Te), and obtained the quantitative values of charge transfer (oxidation states), and projected density of states associated with the localized quasi F-centers. The localized interstitial anionic electrons exhibit significant charge transfer values of approximately -1.88, -2.01, and -1.79 per atom in Zr2O, Zr2Se, and Zr2Te, respectively, and contribute actively in the electronic band structures and density of states at the Fermi level. From the 2D contour plot of the electron localization function (ELF), it has been predicted that the spatial distribution of the quasi-F centers stabilizes in the form of a one-dimensional pattern, with localized ELF sites interconnected with delocalized electron channels. Further, low work-function values of Zr2X, ranging from 2.7-3.4 eV, confirm the electride properties of these binary compounds, promising applications in electro-catalytic oxidations and anode materials in batteries. These unique electronic properties of anionic electrons free from nuclear binding in Zr2X have not been reported yet in the literature.

Unraveling H2 chemisorption and physisorption on metal decorated graphene using quantum Monte Carlo.

Molecular hydrogen has the potential to significantly reduce the use of carbon dioxide emitting energy processes. However, hydrogen gas storage is a major bottleneck for its large-scale use as current storage methods are energy intensive. Among different storage methods, physisorbing molecular hydrogen at ambient pressure and temperatures is a promising alternative-particularly in light of the advancements in tunable lightweight nanomaterials and high throughput screening methods. Nonetheless, understanding hydrogen adsorption in well-defined nanomaterials remains experimentally challenging and reference information is scarce despite the proliferation of works predicting hydrogen adsorption. We focus on Li, Na, Ca, and K, decorated graphene sheets as substrates for molecular hydrogen adsorption, and compute the most accurate adsorption energies available to date using quantum diffusion Monte Carlo (DMC). Building on our previous insights at the density functional theory (DFT) level, we find that a weak covalent chemisorption of molecular hydrogen, known as Kubas interaction, is feasible on Ca decorated graphene according to DMC, in agreement with DFT. This finding is in contrast to previous DMC predictions of the 4H2/Ca+ gas cluster (without graphene) where chemisorption is not favored. However, we find that the adsorption energy of hydrogen on metal decorated graphene according to a widely used DFT method is not fully consistent with DMC. The reference adsorption energies reported herein can be used to find better work-horse methods for application in large-scale modeling of hydrogen adsorption. Furthermore, the implications of this work affect strategies for finding suitable hydrogen storage materials and high-throughput methods.

DMC-ICE13: Ambient and high pressure polymorphs of ice from diffusion Monte Carlo and density functional theory.

Ice is one of the most important and interesting molecular crystals, exhibiting a rich and evolving phase diagram. Recent discoveries mean that there are now 20 distinct polymorphs; a structural diversity that arises from a delicate interplay of hydrogen bonding and van der Waals dispersion forces. This wealth of structures provides a stern test of electronic structure theories, with Density Functional Theory (DFT) often not able to accurately characterize the relative energies of the various ice polymorphs. Thanks to recent advances that enable the accurate and efficient treatment of molecular crystals with Diffusion Monte Carlo (DMC), we present here the DMC-ICE13 dataset; a dataset of lattice energies of 13 ice polymorphs. This dataset encompasses the full structural complexity found in the ambient and high-pressure molecular ice polymorphs, and when experimental reference energies are available, our DMC results deliver sub-chemical accuracy. Using this dataset, we then perform an extensive benchmark of a broad range of DFT functionals. Of the functionals considered, revPBE-D3 and RSCAN reproduce reference absolute lattice energies with the smallest error, while optB86b-vdW and SCAN+rVV10 have the best performance on the relative lattice energies. Our results suggest that a single functional achieving reliable performance for all phases is still missing, and that care is needed in the selection of the most appropriate functional for the desired application. The insights obtained here may also be relevant to liquid water and other hydrogen-bonded and dispersion-bonded molecular crystals.

Thermodynamic and structural insights into the repurposing of drugs that bind to SARS-CoV-2 main protease.

Although researchers have been working tirelessly since the COVID-19 outbreak, so far only three drugs - remdesivir, ronapreve and molnupiravir - have been approved for use in some countries which directly target the SARS-CoV-2 virus. Given the slow pace and substantial costs of new drug discovery and development, together with the urgency of the matter, repurposing of existing drugs for the ongoing disease is an attractive proposition. In a recent study, a high-throughput X-ray crystallographic screen was performed for a selection of drugs which have been approved or are in clinical trials. Thirty-seven compounds have been identified from drug libraries all of which bind to the SARS-CoV-2 main protease (3CLpro). In the current study, we use molecular dynamics simulation and an ensemble-based free energy approach, namely, enhanced sampling of molecular dynamics with approximation of continuum solvent (ESMACS), to investigate a subset of the aforementioned compounds. The drugs studied here are highly diverse, interacting with different binding sites and/or subsites of 3CLpro. The predicted free energies are compared with experimental results wherever they are available and they are found to be in excellent agreement. Our study also provides detailed energetic insights into the nature of the associated drug-protein binding, in turn shedding light on the design and discovery of potential drugs.

Pandemic drugs at pandemic speed: infrastructure for accelerating COVID-19 drug discovery with hybrid machine learning- and physics-based simulations on high-performance computers.

The race to meet the challenges of the global pandemic has served as a reminder that the existing drug discovery process is expensive, inefficient and slow. There is a major bottleneck screening the vast number of potential small molecules to shortlist lead compounds for antiviral drug development. New opportunities to accelerate drug discovery lie at the interface between machine learning methods, in this case, developed for linear accelerators, and physics-based methods. The two in silico methods, each have their own advantages and limitations which, interestingly, complement each other. Here, we present an innovative infrastructural development that combines both approaches to accelerate drug discovery. The scale of the potential resulting workflow is such that it is dependent on supercomputing to achieve extremely high throughput. We have demonstrated the viability of this workflow for the study of inhibitors for four COVID-19 target proteins and our ability to perform the required large-scale calculations to identify lead antiviral compounds through repurposing on a variety of supercomputers.

Enhancing the Accuracy of Ab Initio Molecular Dynamics by Fine Tuning of Effective Two-Body Interactions: Acetonitrile as a Test Case.

Grimme's dispersion-corrected density functional theory (DFT-D) methods have emerged among the most practical approaches to perform accurate quantum mechanical calculations on molecular systems ranging from small clusters to microscopic and mesoscopic samples, i.e., including hundreds or thousands of molecules. Moreover, DFT-D functionals can be easily integrated into popular ab initio molecular dynamics (MD) software packages to carry out first-principles condensed-phase simulations at an affordable computational cost. Here, starting from the well-established D3 version of the dispersion-correction term, we present a simple protocol to improve the accurate description of the intermolecular interactions of molecular clusters of growing size, considering acetonitrile as a test case. Optimization of the interaction energy was performed with reference to diffusion quantum Monte Carlo calculations, successfully reaching the same inherent accuracy of the latter (statistical error of ∼0.1 kcal/mol per molecule). The refined DFT-D3 model was then used to perform ab initio MD simulations of liquid acetonitrile, again showing significant improvements toward available experimental data with respect to the default correction.

Atomic Undercoordination in Ag Islands on Ru(0001) Grown via Size-Selected Cluster Deposition: An Experimental and Theoretical High-Resolution Core-Level Photoemission Study.

The possibility of depositing precisely mass-selected Ag clusters (Ag1, Ag3, and Ag7) on Ru(0001) was instrumental in determining the importance of the in-plane coordination number (CN) and allowed us to establish a linear dependence of the Ag 3d5/2 core-level shift on CN. The fast cluster surface diffusion at room temperature, caused by the low interaction between silver and ruthenium, leads to the formation of islands with a low degree of ordering, as evidenced by the high density of low-coordinated atomic configurations, in particular CN = 4 and 5. On the contrary, islands formed upon Ag7 deposition show a higher density of atoms with CN = 6, thus indicating the formation of islands with a close-packed atomic arrangement. This combined experimental and theoretical approach, when applied to clusters of different elements, offers the perspective to reveal nonequivalent local configurations in two-dimensional (2D) materials grown using different building blocks, with potential implications in understanding electronic and reactivity properties at the atomic level.

Melting line of calcium characterized by in situ LH-DAC XRD and first-principles calculations.

In this work, the melting line of calcium has been characterized both experimentally, using synchrotron X-ray diffraction in laser-heated diamond-anvil cells, and theoretically, using first-principles calculations. In the investigated pressure and temperature range (pressure between 10 and 40 GPa and temperature between 300 and 3000 K) it was possible to observe the face-centred phase of calcium and to confirm (and characterize for the first time at these conditions) the presence of the body-centred cubic and the simple cubic phase of calcium. The melting points obtained with the two techniques are in excellent agreement. Furthermore, the present results agree with the only existing melting line of calcium obtained in laser-heated diamond anvil cells, using the speckle method as melting detection technique. They also confirm a flat slope of the melting line in the pressure range between 10 and 30 GPa. The flat melting curve is associated with the presence of the solid high-temperature body-centered cubic phase of calcium and to a small volume change between this phase and the liquid at melting. Reasons for the stabilization of the body-centered face at high-temperature conditions will be discussed.

Correction: Unusual reversibility in molecular break-up of PAHs: the case of pentacene dehydrogenation on Ir(111).

[This corrects the article DOI: 10.1039/D0SC03734F.].

Unusual reversibility in molecular break-up of PAHs: the case of pentacene dehydrogenation on Ir(111).

In this work, we characterize the adsorption of pentacene molecules on Ir(111) and their behaviour as a function of temperature. While room temperature adsorption preserves the molecular structure of the five benzene rings and the bonds between carbon and hydrogen atoms, we find that complete C-H molecular break up takes place between 450 K and 550 K, eventually resulting in the formation of small graphene islands at temperatures larger than 800 K. Most importantly a reversible temperature-induced dehydrogenation process is found when the system is annealed/cooled in a hydrogen atmosphere with a pressure higher than 5 × 10-7 mbar. This novel process could have interesting implications for the synthesis of larger acenes and for the manipulation of graphene nanoribbon properties.

Interaction between water and carbon nanostructures: How good are current density functional approximations?

Due to their current and future technological applications, including realization of water filters and desalination membranes, water adsorption on graphitic sp2-bonded carbon is of overwhelming interest. However, these systems are notoriously challenging to model, even for electronic structure methods such as density functional theory (DFT), because of the crucial role played by London dispersion forces and noncovalent interactions, in general. Recent efforts have established reference quality interactions of several carbon nanostructures interacting with water. Here, we compile a new benchmark set (dubbed WaC18), which includes a single water molecule interacting with a broad range of carbon structures and various bulk (3D) and two-dimensional (2D) ice polymorphs. The performance of 28 approaches, including semilocal exchange-correlation functionals, nonlocal (Fock) exchange contributions, and long-range van der Waals (vdW) treatments, is tested by computing the deviations from the reference interaction energies. The calculated mean absolute deviations on the WaC18 set depend crucially on the DFT approach, ranging from 135 meV for local density approximation (LDA) to 12 meV for PBE0-D4. We find that modern vdW corrections to DFT significantly improve over their precursors. Within the 28 tested approaches, we identify the best performing within the functional classes of generalized gradient approximated (GGA), meta-GGA, vdW-DF, and hybrid DF, which are BLYP-D4, TPSS-D4, rev-vdW-DF2, and PBE0-D4, respectively.

Translucency of Graphene to van der Waals Forces Applies to Atoms/Molecules with Different Polar Character.

Graphene has been proposed to be either fully transparent to van der Waals interactions to the extent of allowing switching between hydrophobic and hydrophilic behavior, or partially transparent (translucent), yet there has been considerable debate on this topic, which is still ongoing. In a combined experimental and theoretical study we investigate the effects of different metal substrates on the adsorption energy of atomic (argon) and molecular (carbon monoxide) adsorbates on high-quality epitaxial graphene. We demonstrate that while the adsorption energy is certainly affected by the chemical composition of the supporting substrate and by the corrugation of the carbon lattice, the van der Waals interactions between adsorbates and the metal surfaces are partially screened by graphene. Our results indicate that the concept of graphene translucency, already introduced in the case of water droplets, is found to hold more generally also in the case of single polar molecules and atoms, which are apolar.

A new scheme for fixed node diffusion quantum Monte Carlo with pseudopotentials: Improving reproducibility and reducing the trial-wave-function bias.

Fixed node diffusion quantum Monte Carlo (FN-DMC) is an increasingly used computational approach for investigating the electronic structure of molecules, solids, and surfaces with controllable accuracy. It stands out among equally accurate electronic structure approaches for its favorable cubic scaling with system size, which often makes FN-DMC the only computationally affordable high-quality method in large condensed phase systems with more than 100 atoms. In such systems, FN-DMC deploys pseudopotentials (PPs) to substantially improve efficiency. In order to deal with nonlocal terms of PPs, the FN-DMC algorithm must use an additional approximation, leading to the so-called localization error. However, the two available approximations, the locality approximation (LA) and the T-move approximation (TM), have certain disadvantages and can make DMC calculations difficult to reproduce. Here, we introduce a third approach, called the determinant localization approximation (DLA). DLA eliminates reproducibility issues and systematically provides good quality results and stable simulations that are slightly more efficient than LA and TM. When calculating energy differences-such as interaction and ionization energies-DLA is also more accurate than the LA and TM approaches. We believe that DLA paves the way to the automation of FN-DMC and its much easier application in large systems.

Physisorption of Water on Graphene: Subchemical Accuracy from Many-Body Electronic Structure Methods.

Wet carbon interfaces are ubiquitous in the natural world and exhibit anomalous properties, which could be exploited by emerging technologies. However, progress is limited by lack of understanding at the molecular level. Remarkably, even for the most fundamental system (a single water molecule interacting with graphene), there is no consensus on the nature of the interaction. We tackle this by performing an extensive set of complementary state-of-the-art computer simulations on some of the world's largest supercomputers. From this effort a consensus on the water-graphene interaction strength has been obtained. Our results have significant impact for the physical understanding, as they indicate that the interaction is weaker than predicted previously. They also pave the way for more accurate and reliable studies of liquid water at carbon interfaces.

Fast and accurate quantum Monte Carlo for molecular crystals.

Computer simulation plays a central role in modern-day materials science. The utility of a given computational approach depends largely on the balance it provides between accuracy and computational cost. Molecular crystals are a class of materials of great technological importance which are challenging for even the most sophisticated ab initio electronic structure theories to accurately describe. This is partly because they are held together by a balance of weak intermolecular forces but also because the primitive cells of molecular crystals are often substantially larger than those of atomic solids. Here, we demonstrate that diffusion quantum Monte Carlo (DMC) delivers subchemical accuracy for a diverse set of molecular crystals at a surprisingly moderate computational cost. As such, we anticipate that DMC can play an important role in understanding and predicting the properties of a large number of molecular crystals, including those built from relatively large molecules which are far beyond reach of other high-accuracy methods.

Properties of the water to boron nitride interaction: From zero to two dimensions with benchmark accuracy.

Molecular adsorption on surfaces plays an important part in catalysis, corrosion, desalination, and various other processes that are relevant to industry and in nature. As a complement to experiments, accurate adsorption energies can be obtained using various sophisticated electronic structure methods that can now be applied to periodic systems. The adsorption energy of water on boron nitride substrates, going from zero to 2-dimensional periodicity, is particularly interesting as it calls for an accurate treatment of polarizable electrostatics and dispersion interactions, as well as posing a practical challenge to experiments and electronic structure methods. Here, we present reference adsorption energies, static polarizabilities, and dynamic polarizabilities, for water on BN substrates of varying size and dimension. Adsorption energies are computed with coupled cluster theory, fixed-node quantum Monte Carlo (FNQMC), the random phase approximation, and second order Møller-Plesset theory. These wavefunction based correlated methods are found to agree in molecular as well as periodic systems. The best estimate of the water/h-BN adsorption energy is -107±7 meV from FNQMC. In addition, the water adsorption energy on the BN substrates could be expected to grow monotonically with the size of the substrate due to increased dispersion interactions, but interestingly, this is not the case here. This peculiar finding is explained using the static polarizabilities and molecular dispersion coefficients of the systems, as computed from time-dependent density functional theory (DFT). Dynamic as well as static polarizabilities are found to be highly anisotropic in these systems. In addition, the many-body dispersion method in DFT emerges as a particularly useful estimation of finite size effects for other expensive, many-body wavefunction based methods.

A comparison between quantum chemistry and quantum Monte Carlo techniques for the adsorption of water on the (001) LiH surface.

We present a comprehensive benchmark study of the adsorption energy of a single water molecule on the (001) LiH surface using periodic coupled cluster and quantum Monte Carlo theories. We benchmark and compare different implementations of quantum chemical wave function based theories in order to verify the reliability of the predicted adsorption energies and the employed approximations. Furthermore we compare the predicted adsorption energies to those obtained employing widely used van der Waals density-functionals. Our findings show that quantum chemical approaches are becoming a robust and reliable tool for condensed phase electronic structure calculations, providing an additional tool that can also help in potentially improving currently available van der Waals density-functionals.

Performance of van der Waals Corrected Functionals for Guest Adsorption in the M2(dobdc) Metal-Organic Frameworks.

Small-molecule binding in metal-organic frameworks (MOFs) can be accurately studied both experimentally and computationally, provided the proper tools are employed. Herein, we compare and contrast properties associated with guest binding by means of density functional theory (DFT) calculations using nine different functionals for the M2(dobdc) (dobdc4- = 2,5-dioxido,1,4-benzenedicarboxylate) series, where M = Mg, Mn, Fe, Co, Ni, Cu, and Zn. Additionally, we perform Quantum Monte Carlo (QMC) calculations for one system to determine if this method can be used to assess the performance of DFT. We also make comparisons with previously published experimental results for carbon dioxide and water and present new methane neutron powder diffraction (NPD) data for further comparison. All of the functionals are able to predict the experimental variation in the binding energy from one metal to the next; however, the interpretation of the performance of the functionals depends on which value is taken as the reference. On the one hand, if we compare against experimental values, we would conclude that the optB86b-vdW and optB88-vdW functionals systematically overestimate the binding strength, while the second generation of van der Waals (vdW) nonlocal functionals (vdw-DF2 and rev-vdW-DF2) correct for this providing a good description of binding energies. On the other hand, if the QMC calculation is taken as the reference then all of the nonlocal functionals yield results that fall just outside the error of the higher-level calculation. The empirically corrected vdW functionals are in reasonable agreement with experimental heat of adsorptions but under bind when compared with QMC, while Perdew-Burke-Ernzerhof fails by more than 20 kJ/mol regardless of which reference is employed. All of the functionals, with the exception of vdW-DF2, predict reasonable framework and guest binding geometries when compared with NPD measurements. The newest of the functionals considered, rev-vdW-DF2, should be used in place of vdW-DF2, as it yields improved bond distances with similar quality binding energies.