RT-EOM-CCSD Calculations of Inner and Outer Valence Ionization Energies and Spectral Functions.

Photoelectron spectroscopy (PES) is a standard experimental method for material characterization, but its interpretation can be hampered by its reliance on standard materials. To facilitate the study of unknown systems, theoretical methods are desirable. Here, we present a real-time equation-of-motion coupled cluster (RT-EOM-CC) approach for valence PES, extending our core-level development. We demonstrate that RT-EOM-CC yields ionization energies and spectral functions in good agreement with experimental and CI-based results, even for some more correlated cases.

Quantum Flow Algorithms for Simulating Many-Body Systems on Quantum Computers.

We conducted quantum simulations of strongly correlated systems using the quantum flow (QFlow) approach, which enables sampling large subspaces of the Hilbert space through coupled variational problems in reduced dimensionality active spaces. Our QFlow algorithms significantly reduce circuit complexity and pave the way for scalable and constant-circuit-depth quantum computing. Our simulations show that QFlow can optimize the collective number of wave function parameters without increasing the required qubits using active spaces having an order of magnitude fewer number of parameters.

A Perspective on Sustainable Computational Chemistry Software Development and Integration.

The power of quantum chemistry to predict the ground and excited state properties of complex chemical systems has driven the development of computational quantum chemistry software, integrating advances in theory, applied mathematics, and computer science. The emergence of new computational paradigms associated with exascale technologies also poses significant challenges that require a flexible forward strategy to take full advantage of existing and forthcoming computational resources. In this context, the sustainability and interoperability of computational chemistry software development are among the most pressing issues. In this perspective, we discuss software infrastructure needs and investments with an eye to fully utilize exascale resources and provide unique computational tools for next-generation science problems and scientific discoveries.

TAMM: Tensor algebra for many-body methods.

Tensor algebra operations such as contractions in computational chemistry consume a significant fraction of the computing time on large-scale computing platforms. The widespread use of tensor contractions between large multi-dimensional tensors in describing electronic structure theory has motivated the development of multiple tensor algebra frameworks targeting heterogeneous computing platforms. In this paper, we present Tensor Algebra for Many-body Methods (TAMM), a framework for productive and performance-portable development of scalable computational chemistry methods. TAMM decouples the specification of the computation from the execution of these operations on available high-performance computing systems. With this design choice, the scientific application developers (domain scientists) can focus on the algorithmic requirements using the tensor algebra interface provided by TAMM, whereas high-performance computing developers can direct their attention to various optimizations on the underlying constructs, such as efficient data distribution, optimized scheduling algorithms, and efficient use of intra-node resources (e.g., graphics processing units). The modular structure of TAMM allows it to support different hardware architectures and incorporate new algorithmic advances. We describe the TAMM framework and our approach to the sustainable development of scalable ground- and excited-state electronic structure methods. We present case studies highlighting the ease of use, including the performance and productivity gains compared to other frameworks.

NWChem: Recent and Ongoing Developments.

This paper summarizes developments in the NWChem computational chemistry suite since the last major release (NWChem 7.0.0). Specifically, we focus on functionality, along with input blocks, that is accessible in the current stable release (NWChem 7.2.0) and in the "master" development branch, interfaces to quantum computing simulators, interfaces to external libraries, the NWChem github repository, and containerization of NWChem executable images. Some ongoing developments that will be available in the near future are also discussed.

Modeling Singlet Fission on a Quantum Computer.

We demonstrate a practical application of quantum computing by using it to investigate the linear H4 molecule as a simple model for singlet fission. We use the Peeters-Devreese-Soldatov energy functional to calculate the necessary energetics based on the moments of the Hamiltonian estimated on the quantum computer. To reduce the number of required measurements, we use several independent strategies: 1) reduction of the size of the relevant Hilbert space by tapering off qubits; 2) measurement optimization via rotations to eigenbases shared by groups of qubit-wise commuting Pauli strings; and 3) parallel execution of multiple state preparation and measurement operations using all 20 qubits available on the Quantinuum H1-1 quantum hardware. Our results meet the energetic requirements for singlet fission, are in excellent agreement with exact transition energies (for the chosen one-particle basis), and outperform classical methods considered computationally feasible for singlet fission candidates.

Biomass valorization toward sustainable asphalt pavements: Progress and prospects.

To cope with the global climate crisis and assist in achieving the carbon neutrality, the use of biomass materials to fully or partially replace petroleum-based products and unrenewable resources is expected to become a widespread solution. Based on the analysis of the existing literature, this paper firstly classified biomass materials with potential application prospects in pavement engineering according to their application and summarized their respective preparation methods and characteristics. The pavement performance of asphalt mixtures with biomass materials was analyzed and summarized, and the economic and environmental benefits of bio-asphalt binder were evaluated. The analysis shows that pavement biomass materials with potential for practical application can be divided into three categories: bio-oil, bio-fiber, and bio-filler. Adding bio-oil to modify or extend the virgin asphalt binder can mostly improve the low temperature performance of asphalt binder. Adding styrene-butadienestyrene (SBS) or other preferable bio-components for composite modification will have a further improved effect. Most of the asphalt mixtures prepared by using bio-oil modified asphalt binders have improved the low temperature crack resistance and fatigue resistance of asphalt mixtures, but the high temperature stability and moisture resistance may decrease. As a rejuvenator, most bio-oils can restore the high and low temperature performance of aged asphalt and recycled asphalt mixture, and improve fatigue resistance. Adding bio-fiber could significantly improve the high temperature stability, low temperature crack resistance and moisture resistance of asphalt mixtures. Biochar as a bio-filler can slow down the asphalt aging process and some other bio-fillers can improve the high temperature stability and fatigue resistance of asphalt binders. Through calculation, it is found that the cost performance of bio-asphalt has the ability to surpass conventional asphalt and has economic benefits. The use of biomass materials for pavements not only reduces pollutants, but also reduces the dependence on petroleum-based products. It has significant environmental benefits and development potential.

Real-Time Equation-of-Motion Coupled-Cluster Cumulant Green's Function Method: Heterogeneous Parallel Implementation Based on the Tensor Algebra for Many-Body Methods Infrastructure.

We report the implementation of the real-time equation-of-motion coupled-cluster (RT-EOM-CC) cumulant Green's function method [ J. Chem. Phys. 2020, 152, 174113] within the Tensor Algebra for Many-body Methods (TAMM) infrastructure. TAMM is a massively parallel heterogeneous tensor library designed for utilizing forthcoming exascale computing resources. The two-body electron repulsion matrix elements are Cholesky-decomposed, and we imposed spin-explicit forms of the various operators when evaluating the tensor contractions. Unlike our previous real algebra Tensor Contraction Engine (TCE) implementation, the TAMM implementation supports fully complex algebra. The RT-EOM-CC singles (S) and doubles (D) time-dependent amplitudes are propagated using a first-order Adams-Moulton method. This new implementation shows excellent scalability tested up to 500 GPUs using the Zn-porphyrin molecule with 655 basis functions, with parallel efficiencies above 90% up to 400 GPUs. The TAMM RT-EOM-CCSD was used to study core photoemission spectra in the formaldehyde and ethyl trifluoroacetate (ESCA) molecules. Simulations of the latter involve as many as 71 occupied and 649 virtual orbitals. The relative quasiparticle ionization energies and overall spectral functions agree well with available experimental results.

High-throughput ab initio reaction mechanism exploration in the cloud with automated multi-reference validation.

Quantum chemical calculations on atomistic systems have evolved into a standard approach to studying molecular matter. These calculations often involve a significant amount of manual input and expertise, although most of this effort could be automated, which would alleviate the need for expertise in software and hardware accessibility. Here, we present the AutoRXN workflow, an automated workflow for exploratory high-throughput electronic structure calculations of molecular systems, in which (i) density functional theory methods are exploited to deliver minimum and transition-state structures and corresponding energies and properties, (ii) coupled cluster calculations are then launched for optimized structures to provide more accurate energy and property estimates, and (iii) multi-reference diagnostics are evaluated to back check the coupled cluster results and subject them to automated multi-configurational calculations for potential multi-configurational cases. All calculations are carried out in a cloud environment and support massive computational campaigns. Key features of all components of the AutoRXN workflow are autonomy, stability, and minimum operator interference. We highlight the AutoRXN workflow with the example of an autonomous reaction mechanism exploration of the mode of action of a homogeneous catalyst for the asymmetric reduction of ketones.

Triple Excitations in Green's Function Coupled Cluster Solver for Studies of Strongly Correlated Systems in the Framework of Self-Energy Embedding Theory.

Embedding theories became important approaches used for accurate calculations of both molecules and solids. In these theories, a small chosen subset of orbitals is treated with an accurate method, called an impurity solver, capable of describing higher correlation effects. Ideally, such a chosen fragment should contain multiple orbitals responsible for the chemical and physical behavior of the compound. Handling a large number of chosen orbitals presents a very significant challenge for the current generation of solvers used in the physics and chemistry community. Here, we develop a Green's function coupled cluster singles doubles and triples (GFCCSDT) solver that can be used for a quantitative description in both molecules and solids. This solver allows us to treat orbital spaces that are inaccessible to other accurate solvers. At the same time, GFCCSDT maintains high accuracy of the resulting self-energy. Moreover, in conjunction with the GFCCSD solver, it allows us to test the systematic convergence of computational studies. Developing the CC family of solvers paves the road to fully systematic Green's function embedding calculations in solids. In this paper, we focus on the investigation of GFCCSDT self-energies for a strongly correlated problem of SrMnO3 solid. Subsequently, we apply this solver to solid MnO showing that an approximate variant of GFCCSDT is capable of yielding a high accuracy orbital resolved spectral function.

Ageing Evaluation of Foamed Polymer Modified Bitumen with Bio-Flux Additive.

This paper presents the results of an analysis of the changes in the stiffness of asphalt binders modified with a bio-flux additive and subjected to the processes of foaming and short-term ageing. The purpose of the analyses was to determine changes in the rheological properties of asphalt binder as a result of technological processes characteristic of hot and warm mix asphalt technology. Three asphalt binders with similar penetration but varying degrees of polymer modification were tested: 50/70, 45/80-55 polymer-modified bitumen, and 45/80-80 highly modified bitumen. Tests were carried out on four groups of binders: original binders, foamed binders after 14 days of storage, non-foamed binders after Rolling Thin Film Oven Test (RTFOT) ageing, and foamed binders after 14 days of storage subjected to RTFOT ageing. The master curves of the complex shear modulus G* were analysed, and three indexes of binder stiffening were determined, characterising the investigated effects. The tests showed that some of the stiffening indices significantly depended on the degree of polymer modification and the content of the bio-flux additive. Moreover, it was found that the foaming process in the case of paving-grade bitumen and polymer-modified bitumen did not contribute to the additional stiffening of the binders.

Sub-system self-consistency in coupled cluster theory.

In this article, we provide numerical evidence indicating that the single-reference coupled-cluster (CC) energies can be calculated alternatively to their copybook definition. We demonstrate that the CC energy can be reconstructed by diagonalizing the effective Hamiltonians describing correlated sub-systems of the many-body system. In the extreme case, we provide numerical evidence that the CC energy can be reproduced through the diagonalization of the effective Hamiltonian describing sub-system composed of a single electron. These properties of the CC formalism can be exploited to design protocols to define effective interactions in sub-systems used as probes to calculate the energy of the entire system and introduce a new type of self-consistency for approximate CC approaches.

Effects of Laboratory Ageing on the FTIR Measurements of Water-Foamed Bio-Fluxed Asphalt Binders.

The study investigated the effects of laboratory ageing on the fluxed and water-foamed asphalt binders in scope of Fourier transform infrared spectroscopic measurements of ageing indicators and changes in their chemical composition. The investigated binders included two paving grades, two polymer modified asphalt binders, and a highly modified asphalt binder. The bio-flux additive was produced from rapeseed methyl esters in an oxidation reaction in the presence of a metal catalyst and organic peroxide. The use of the bio-origin additive, in particular oil derivatives, was aimed at softening and better foaming of asphalt binders. This modification is possible due to the good mixability of vegetable oils with an asphalt binder, which gives a homogeneous product with reduced stiffness. The study involved the rolling thin film oven, short-term, and the pressure ageing vessel, long term, and ageing to induce oxidation on the evaluated asphalt binders. The addition of the bio-flux additive has significantly decreased the measured content of ketone compounds related to oxidation in both non-aged and aged asphalt binders, although this effect after ageing were far smaller in magnitude. Additionally, both ageing processes decreased significantly the absorbances in the ester spectral bands specific to the bio-flux additive. All mentioned effects were similar in magnitude in all tested asphalt binders.

Warm Mix Asphalt Binder Utilizing Water Foaming and Fluxing Using Bio-Derived Agent.

The present paper investigates the effects of simultaneous mechanical foaming using water and fluxing with a bio-derived agent on the properties of three distinct asphalt binders: 50/70 paving-grade bitumen, 45/80-55 polymer-modified bitumen, and 45/80-80 highly modified asphalt binder. The testing involved classical tests for assessing binder consistency (penetration at 25 °C, ring and ball softening point, Fraass breaking point, and dynamic viscosity) as well as performance tests (high and low Superpave critical temperatures and multiple stress creep recovery). The tests included assessment directly after asphalt binder foaming and were repeated after a 14-day period. It was shown that bitumen foaming had only short-term effects on the asphalt binders, which did not persist in the repeated tests after 14 days. The fluxing agent that was utilized caused significant changes in the consistency of all asphalt binders. The changes in the performance characteristics of the 50/70 and 45/80-55 binders were severe and amounted to a significant decrease in high-temperature performance of these binders. On the other hand, an improvement in all performance characteristics in the case of the 45/80-80 asphalt binder was observed as a result of the applied processes, particularly when measured 14 days after foaming. This study shows that the simultaneous use of foaming and the fluxing additive decreased the dynamic viscosity of the 45/80-80 binder, while improving its properties relating the pavement performance.

Optimized Quantum Phase Estimation for Simulating Electronic States in Various Energy Regimes.

While quantum algorithms for simulations exhibit better asymptotic scaling than their classical counterparts, they currently cannot be accurately implemented on real-world devices. Instead, chemists and computer scientists rely on costly classical simulations of these quantum algorithms. In particular, the quantum phase estimation (QPE) algorithm is among several approaches that has attracted much attention in recent years due to its genuine quantum character. However, it is memory-intensive to simulate and intractable for moderate system sizes. This paper discusses the performance and applicability of QPESIM, a new simulation of the QPE algorithm designed to take advantage of modest computational resources. In particular, we demonstrate the versatility of QPESIM in simulating various electronic states by examining the ground and core-level states of H2O. For these states, we also discuss the effect of the active-space size on the quality of the calculated energies. For the high-energy core-level states, we demonstrate that new QPE simulations for active spaces defined by 15 active orbitals significantly reduce the errors in core-level excitation energies compared to earlier QPE simulations using smaller active spaces.

Modeling Absolute Redox Potentials of Ferrocene in the Condensed Phase.

Absolute thermodynamic quantities for critical chemical reactions are needed to determine the role of solvents and reactive environments in catalysis and electrocatalysis. Theoretical methods can provide such quantification but are often hindered by the innate complexity of electron correlation and dynamic relaxation of solvent environments. We present and validate a protocol for calculating the redox potentials of the ferrocene/ferrocenium redox pair in acetonitrile. Equation-of-motion and effective fragment potential (EFP) methods are used to characterize the adiabatic and vertical ionization potentials as well as the electron affinity processes. We benchmark molecular mechanics against the EFP model to show the differences in the ferrocene electronic polarizability in two redox states. Our best estimate of the redox potential (4.94 eV) agrees well with the experimental value (4.93 eV). This demonstrates the ability of modern computational methods to predict absolute redox potentials quantitatively and to quantify the correlation of dynamic effects, which underlie their origin.

Real-time equation-of-motion CC cumulant and CC Green's function simulations of photoemission spectra of water and water dimer.

Newly developed coupled-cluster (CC) methods enable simulations of ionization potentials and spectral functions of molecular systems in a wide range of energy scales ranging from core-binding to valence. This paper discusses the results obtained with the real-time equation-of-motion CC cumulant (RT-EOM-CC) approach and CC Green's function (CCGF) approaches in applications to the water and water dimer molecules. We compare the ionization potentials obtained with these methods for the valence region with the results obtained with the coupled-cluster with singles, doubles, and perturbative triples formulation as a difference of energies for N and N - 1 electron systems. All methods show good agreement with each other. They also agree well with the experiment with errors usually below 0.1 eV for the ionization potentials. We also analyze unique features of the spectral functions, associated with the position of satellite peaks, obtained with the RT-EOM-CC and CCGF methods employing single and double excitations, as a function of the monomer OH bond length and the proton transfer coordinate in the dimer. Finally, we analyze the impact of the basis set effects on the quality of calculated ionization potentials and find that the basis set effects are less pronounced for the augmented-type sets.

Coupled cluster downfolding methods: The effect of double commutator terms on the accuracy of ground-state energies.

Downfolding coupled cluster techniques have recently been introduced into quantum chemistry as a tool for the dimensionality reduction of the many-body quantum problem. As opposed to earlier formulations in physics and chemistry based on the concept of effective Hamiltonians, the appearance of the downfolded Hamiltonians is a natural consequence of the single-reference exponential parameterization of the wave function. In this paper, we discuss the impact of higher-order terms originating in double commutators. In analogy to previous studies, we consider the case when only one- and two-body interactions are included in the downfolded Hamiltonians. We demonstrate the efficiency of the many-body expansions involving single and double commutators for the unitary extension of the downfolded Hamiltonians on the example of the beryllium atom, and bond-breaking processes in the Li2 and H2O molecules. For the H2O system, we also analyze energies obtained with downfolding procedures as functions of the active space size.

Small intestinal bacterial overgrowth in Alzheimer's disease.

The results of animal studies and clinical data support the gut microbiota contribution to the pathogenesis of Alzheimer's disease (AD). The aim of this pilot study was to evaluate the prevalence of small intestinal bacterial overgrowth (SIBO) and fecal markers of intestinal inflammation and permeability in AD patients. The study was conducted in 45 AD patients and 27 controls. Data on comorbidities, pharmacotherapy, and gastrointestinal symptoms were acquired from medical records and a questionnaire. SIBO was evaluated using lactulose hydrogen breath test. Fecal calprotectin and zonulin levels were assessed by ELISA assays. The positive result of SIBO breath test was found in 49% of the AD patients and 22% of the controls (p = 0.025). The comparative analysis between SIBO-positive and SIBO-negative AD patients with respect to the degree of cognitive impairment, comorbidities and used medications did not reveal any statistically significant difference, except for less common heartburn in SIBO-positive AD patients than in SIBO-negative ones (9 vs 35%, p = 0.038). The median fecal calprotectin and zonulin levels in the AD group compared to the control group amounted to 43.1 vs 64.2 µg/g (p = 0.846) and 73.5 vs 49.0 ng/ml (p = 0.177), respectively. In the AD patients there was no association between the presence of SIBO and fecal calprotectin level. Patients with AD are characterized by higher prevalence of SIBO not associated with increased fecal calprotectin level that may be related to anti-inflammatory effect of cholinergic drugs used in the treatment of AD.

Quantum Solvers for Plane-Wave Hamiltonians: Abridging Virtual Spaces Through the Optimization of Pairwise Correlations.

For many-body methods such as MCSCF and CASSCF, in which the number of one-electron orbitals is optimized and independent of the basis set used, there are no problems with using plane-wave basis sets. However, for methods currently used in quantum computing such as select configuration interaction (CI) and coupled cluster (CC) methods, it is necessary to have a virtual space that is able to capture a significant amount of electron-electron correlation in the system. The virtual orbitals in a pseudopotential plane-wave Hartree-Fock calculation, because of Coulomb repulsion, are often scattering states that interact very weakly with the filled orbitals. As a result, very little correlation energy is captured from them. The use of virtual spaces derived from the one-electron operators has also been tried, and while some correlations are captured, the amount is quite low. To overcome these limitations, we have been developing new classes of algorithms to define virtual spaces by optimizing orbitals from small pairwise CI Hamiltonians, which we term as correlation optimized virtual orbitals with the abbreviation COVOs. With these procedures, we have been able to derive virtual spaces, containing only a few orbitals, which are able to capture a significant amount of correlation. The focus in this manuscript is on using these derived basis sets to target full CI (FCI) quality results for H2 on near-term quantum computers. However, the initial results for this approach were promising. We were able to obtain good agreement with FCI/cc-pVTZ results for this system with just 4 virtual orbitals, using both FCI and quantum simulations. The quality of the results using COVOs suggests that it may be possible to use them in other many-body approaches, including coupled cluster and Møller-Plesset perturbation theories, and open up the door to many-body calculations for pseudopotential plane-wave basis set methods.