Machine-learning assisted scheduling optimization and its application in quantum chemical calculations.

Easy and effective usage of computational resources is crucial for scientific calculations, both from the perspectives of timeliness and economic efficiency. This work proposes a bi-level optimization framework to optimize the computational sequences. Machine-learning (ML) assisted static load-balancing, and different dynamic load-balancing algorithms can be integrated. Consequently, the computational and scheduling engine of the ParaEngine is developed to invoke optimized quantum chemical (QC) calculations. Illustrated benchmark calculations include high-throughput drug suit, solvent model, P38 protein, and SARS-CoV-2 systems. The results show that the usage rate of given computational resources for high throughput and large-scale fragmentation QC calculations can primarily profit, and faster accomplishing computational tasks can be expected when employing high-performance computing (HPC) clusters.

Kylin 1.0: An ab-initio density matrix renormalization group quantum chemistry program.

The accurate evaluation of electron correlations is highly necessary for the proper descriptions of the electronic structures in strongly correlated molecules, ranging from bond-dissociating molecules, polyradicals, to large conjugated molecules and transition metal complexes. For this purpose, in this paper, a new ab-initio quantum chemistry program Kylin 1.0 for electron correlation calculations at various quantum many-body levels, including configuration interaction (CI), perturbation theory (PT), and density matrix renormalization group (DMRG), is presented. Furthermore, fundamental quantum chemistry methods such as Hartree-Fock self-consistent field (HF-SCF) and the complete active space SCF (CASSCF) are also implemented. The Kylin 1.0 program possesses the following features: (1) a matrix product operator (MPO) formulation-based efficient DMRG implementation for describing static electron correlation within a large active space composed of more than 100 orbitals, supporting both U 1 n × U 1 S z and U 1 n × SU 2 S symmetries; (2) an efficient second-order DMRG-self-consistent field (SCF) implementation; (3) an externally contracted multi-reference CI (MRCI) and Epstein-Nesbet PT with DMRG reference wave functions for including the remaining dynamic electron correlation outside the large active spaces. In this paper, we introduce the capabilities and numerical benchmark examples of the Kylin 1.0 program.

Rapid and ultrasensitive detection of SARS-CoV-2 spike protein based on upconversion luminescence biosensor for COVID-19 point-of-care diagnostics.

Here, we firstly introduce a detection system consisting of upconversion nanoparticles (UCNPs) and Au nanorods (AuNRs) for an ultrasensitive, rapid, quantitative and on-site detection of SARS-CoV-2 spike (S) protein based on Förster resonance energy transfer (FRET) effect. Briefly, the UCNPs capture the S protein of lysed SARS-CoV-2 in the swabs and subsequently they are bound with the anti-S antibodies modified AuNRs, resulting in significant nonradiative transitions from UCNPs (donors) to AuNRs (acceptors) at 480 nm and 800 nm, respectively. Notably, the specific recognition and quantitation of S protein can be realized in minutes at 800 nm because of the low autofluorescence and high Yb-Tm energy transfer in upconversion process. Inspiringly, the limit of detection (LOD) of the S protein can reach down to 1.06 fg mL-1, while the recognition of nucleocapsid protein is also comparable with a commercial test kit in a shorter time (only 5 min). The established strategy is technically superior to those reported point-of-care biosensors in terms of detection time, cost, and sensitivity, which paves a new avenue for future on-site rapid viral screening and point-of-care diagnostics.

Optimizing two-electron repulsion integral calculations with McMurchie-Davidson method on graphic processing unit.

In this article, several optimization methods of two-electron repulsion integral calculations on a graphic processing unit (GPU) are presented. These methods are based on the investigations of the method presented by McMurchie and Davidson (MD). A new Boys function evaluation method for the GPU calculation is introduced. The series summation, the error function, and the finite sum formula method are combined; thus, good performance on the GPU can be achieved. By taking some theoretical study of the McMurchie-Davidson recurrence relations, three major optimization approaches are derived from the deduction of the general term formula for the Hermite expansion coefficient. The three approaches contain a new form of the Hermite expansion coefficients with corresponding recurrence relations, which is more efficient for one-electron integrals and [ss|∗∗] or [∗∗|ss] type two-electron integrals. In addition, a simple yet efficient new recurrence formula for the coefficient evaluation is derived, which is more efficient both in float operations and memory operations than its original one. In average, the new recurrence relation can save 26% float operations and 37% memory operations. Finally, a common sub-expression elimination (CSE) method is implemented. This CSE method is directly generated from some equalities we discovered from the general term formula other than by computer algebra system software. This optimized method achieved up to 3.09 speedups compared to the original MD method on the GPU and up to 92.75 speedups compared to the GAMESS calculation on the central processing unit.

Portably parallel construction of a configuration-interaction wave function from a matrix-product state using the Charm++ framework.

The construction of configuration-interaction (CI) expansions from a matrix product state (MPS) involves numerous matrix operations and the skillful sampling of important configurations in a large Hilbert space. In this work, we present an efficient procedure for constructing CI expansions from MPS employing the parallel object-oriented Charm++ programming framework, upon which automatic load-balancing and object migrating facilities can be employed. This procedure was employed in the MPS-to-CI utility (Moritz et al., J. Chem. Phys. 2007, 126, 224109), the sampling-reconstructed complete active-space algorithm (SR-CAS, Boguslawski et al., J. Chem. Phys. 2011, 134, 224101), and the entanglement-driven genetic algorithm (EDGA, Luo et al., J. Chem. Theory Comput. 2017, 13, 4699). It enhances productivity and allows the sampling programs to evolve to their population-expansion versions, for example, EDGA with population expansion (PE-EDGA). Further, examples of 1,2-dioxetanone and firefly dioxetanone anion (FDO- ) molecules demonstrated the following: (a) parallel efficiencies can be persistently improved by simply by increasing the proportions of the asynchronous executions and (b) a sampled CAS-type CI wave function of a bi-radical-state FDO- molecule utilizing the full valence (30e,26o) active space can be constructed within a few hours with using thousands of cores.

Elucidating the multi-configurational character of the firefly dioxetanone anion and its prototypes in the biradical region using full valence active spaces.

We analyzed the near-degenerate states of the firefly dioxetanone anion (FDO-) and its prototypes, especially in the biradical region, using multi-configurational approaches. The importance of utilizing full valence active spaces by means of density-matrix renormalization group self-consistent field (DMRG-SCF) calculations was described. Our results revealed that the neglect of some valence orbitals can affect the quantitative accuracy in later multi-reference calculations or the qualitative conclusion when optimizing conical intersections. Using all of the relevant valence orbitals of FDO-, we confirmed that there were two conical intersections, as reported in previous work, and that the intersecting states were changed when the active space was enlarged. Beyond these, we found that there were strong interactions between states in the biradical regions, in which the changes in entanglements can be used to visualize the interacting state evolution.

Multiconfigurational Effects in Theoretical Resonance Raman Spectra.

We analyze resonance Raman spectra of the nucleobase uracil in the short-time approximation calculated with multiconfigurational methods. We discuss the importance of static electron correlation by means of density-matrix renormalization group self-consistent field (DMRG-SCF) calculations. Our DMRG-SCF results reveal that a minimal active orbital space that leads to a qualitatively correct description of the resonance Raman spectrum of uracil should encompass parts of the σ/σ* bonding/anti-bonding orbitals of the pyrimidine ring. We trace these findings back to the considerable entanglement between the σ/σ* bonding/anti-bonding as well as valence π/π* orbitals in the excited-state electronic structure of uracil, which indicates non-negligible non-dynamical correlation effects that are less pronounced in the electronic ground state.

New Approaches for ab initio Calculations of Molecules with Strong Electron Correlation.

Reliable quantum chemical methods for the description of molecules with dense-lying frontier orbitals are needed in the context of many chemical compounds and reactions. Here, we review developments that led to our new computational toolbox which implements the quantum chemical density matrix renormalization group in a second-generation algorithm. We present an overview of the different components of this toolbox.

Density-matrix renormalization group algorithm with multi-level active space.

The density-matrix renormalization group (DMRG) method, which can deal with a large active space composed of tens of orbitals, is nowadays widely used as an efficient addition to traditional complete active space (CAS)-based approaches. In this paper, we present the DMRG algorithm with a multi-level (ML) control of the active space based on chemical intuition-based hierarchical orbital ordering, which is called as ML-DMRG with its self-consistent field (SCF) variant ML-DMRG-SCF. Ground and excited state calculations of H2O, N2, indole, and Cr2 with comparisons to DMRG references using fixed number of kept states (M) illustrate that ML-type DMRG calculations can obtain noticeable efficiency gains. It is also shown that the orbital re-ordering based on hierarchical multiple active subspaces may be beneficial for reducing computational time for not only ML-DMRG calculations but also DMRG ones with fixed M values.

Self-consistent embedding of density-matrix renormalization group wavefunctions in a density functional environment.

We present the first implementation of a density matrix renormalization group algorithm embedded in an environment described by density functional theory. The frozen density embedding scheme is used with a freeze-and-thaw strategy for a self-consistent polarization of the orbital-optimized wavefunction and the environmental densities with respect to each other.

Microfluidic Chip-Assisted Upconversion Luminescence Biosensing Platform for Point-of-Care Virus Diagnostics.

Epidemics caused by multiple viruses continue to emerge, which have brought a terrible impact on human society. Identification of viral infections with high sensitivity and portability is of significant importance for the screening and management of diseases caused by viruses. Herein, a microfluidic chip (MFC)-assisted upconversion luminescence biosensing platform is designed and fabricated for point-of-care virus detection. Upconversion nanoparticles with excellent stability are successfully synthesized as luminescent agents for optical signal generation in the portable virus diagnostic platform. The relevant investigation results illustrate that the MFC-assisted virus diagnostic platform possesses outstanding performance such as good integration, high sensitivity (1.12 pg mL-1), ease of use, and portability. In addition, clinical sample test result verifies its more prominent virus diagnostic properties than commercially available rapid test strips. All of these thrilling capabilities imply that the designed portable virus diagnostic platform has great potential for future virus detection applications.

Calculating excited states of molecular aggregates by the renormalized excitonic method.

In this paper, we apply the recently developed ab initio renormalized excitonic method (REM) to the excitation energy calculations of various molecular aggregates, through the extension of REM to the time-dependent density functional theory (TDDFT). Tested molecular aggregate systems include one-dimensional hydrogen-bonded water chains, ring crystals with π-π stacking or van der Waals interactions, two dimensional benzene aggregates and the general aqueous systems with polar and nonpolar solutes. The basis set factor as well as the effect of the exchange-correlation functionals are also investigated. The results indicate that the REM-TDDFT method with suitable basis set and exchange-correlation functionals can give good descriptions of excitation energies and excitation area for lowest electronic excitations in the molecular aggregate systems with economic computational costs. It is shown that the deviations of REM-TDDFT excitation energies from those by standard TDDFT are much less than 0.1 eV and the computational time can be reduced by one order.

Assessment of various natural orbitals as the basis of large active space density-matrix renormalization group calculations.

It is well-known that not only the orbital ordering but also the choice of the orbitals itself as the basis may significantly influence the computational efficiency of density-matrix renormalization group (DMRG) calculations. In this study, for assessing the efficiency of using various natural orbitals (NOs) as the DMRG basis, we performed benchmark DMRG calculations with different bases, which included the NOs obtained by various traditional electron correlation methods, as well as NOs acquired from preliminary moderate DMRG calculations (e.g., preserved states less than 500). The tested systems included N2, transition metal Cr2 systems, as well as 1D hydrogen polyradical chain systems under equilibrium and dissociation conditions and 2D hydrogen aggregates. The results indicate that a good compromise between the requirement for low computational costs of acquiring NOs and the demand for high efficiency of NOs as the basis of DMRG calculations may be very dependent on the studied systems' diverse electron correlation characteristics and the size of the active space. It is also shown that a DMRG-complete active space configuration interaction (DMRG-CASCI) calculation in a basis of carefully chosen NOs can provide a less expensive alternative to the standard DMRG-complete active space self-consistent field (DMRG-CASSCF) calculation and avoid the convergence difficulties of orbital optimization for large active spaces. The effect of different NO ordering schemes on DMRG-CASCI calculations is also discussed.

Solvent effect on electronic absorption, fluorescence, and phosphorescence of acetone in water: revisited by quantum mechanics/molecular mechanics (QM/MM) simulations.

The accurate simulation of fluorescence and phosphorescence spectra in solution remains a huge challenge due to the difficulty of simulating excited state dynamics in condensed phase. In this work we revisit the solvent effect on the electronic absorption, fluorescence, and phosphorescence of acetone by virtue of quantum mechanics/molecular mechanics (QM/MM) equilibrium state dynamics simulations for both the ground state (S0) and the lowest excited singlet (S1) and triplet (T1) states of aqueous acetone, which use periodic boundary conditions and hundreds of explicit solvent molecules and are free of empirical electrostatic fittings for excited states. Our calculated solvent effects on acetone's n → π* (S0 → S1) absorption (0.25-0.31 eV) and n ← π* (S1 → S0) emission (0.03-0.04 eV) as well as the Stokes shift (0.22-0.27 eV) are in good accordance with the experimental results (0.19 to 0.31, -0.02 to 0.05, and 0.14 to 0.33 eV, respectively). We also predict small water effects (-0.05 to 0.03 eV) for S1 → T1 and T1 → S0 phosphorescence emissions of acetone, which have no experimental data to date. For the recent dispute about the magnitude of the solvent effect for acetone's S1 → S0 fluorescence, we confirm that such effect is very small, agreeing well with the experimental determinations and most recent theoretical calculations. The large solvent effect for electronic absorption and small or negligible one for fluorescence and phosphorescence are shown to be related with much reduced dipole moments of acetone and accordingly much less hydrogen bonds for aqueous acetone in the electronic excited states S1 and T1 comparing to the ground state S0. We also disclose that solvent polarization effects are relatively small for all the electronic transitions of aqueous acetone involved in this work through the investigation of the QM region size effect on QM/MM results.

Solvatochromic shifts of polar and non-polar molecules in ambient and supercritical water: a sequential quantum mechanics/molecular mechanics study including solute-solvent electron exchange-correlation.

Polar and non-polar solutes (acetone and benzene) dissolved in ambient water and supercritical water are investigated theoretically using a sequential quantum mechanics (QM)/molecular mechanics (MM) method which combines classical molecular dynamics simulations and QM/MM calculations. From the detailed analysis of the dependence of the QM region size and point charge background region size as well as the different functionals, it is found that the inclusion of the solvent molecules within the first solvation shell into the QM region to account for the exchange-correlation between a solute and neighboring solvent molecules is important for the highly accurate spectral shift calculations, especially vital for the non-polar solutes whose interactions with the solvents are dominated by the quantum dispersions. At the same time, sufficiently large surrounding partial charge region (r(cutoff) ≥15 Å) as well as the functional corrections to describe the long-range dispersion-corrections are also essential for the study of the electronic excited states in condensed phase. Our calculated solvatochromic shift values and their density dependencies at ambient and high temperature conditions are found to be in good agreements with experimental observations. This indicates that sound theoretical studies of solvatochromic shift can be achieved provided that a reasonable computational scheme with sufficiently large N(water) (QM) and r(cutoff) values is implemented. We also find both of aqueous acetone and aqueous benzene under high temperatures present three distinctive regions: low-density gas-like region, supercritical region, and high-density liquid-like region. The plateau behavior of solvatochromic shift in the supercritical region can be ascribed to the solvent clustering around the solute, which is a fundamental phenomenon of supercritical fluids (SCFs). The density dependence of our calculated coordination number of the first solvation shell nicely reproduces the trend of spectral shift and verifies the solvent clustering phenomenon of SCFs and its relationship with SCF's physicochemical properties.

A new fragment-based approach for calculating electronic excitation energies of large systems.

We present a new fragment-based scheme to calculate the excited states of large systems without necessity of a Hartree-Fock (HF) solution of the whole system. This method is based on the implementation of the renormalized excitonic method [M. A. Hajj et al., Phys. Rev. B 72, 224412 (2005)] at ab initio level, which assumes that the excitation of the whole system can be expressed by a linear combination of various local excitations. We decomposed the whole system into several blocks and then constructed the effective Hamiltonians for the intra- and inter-block interactions with block canonical molecular orbitals instead of widely used localized molecular orbitals. Accordingly, we avoided the prerequisite HF solution and the localization procedure of the molecular orbitals in the popular local correlation methods. Test calculations were implemented for hydrogen molecule chains at the full configuration interaction, symmetry adapted cluster/symmetry adapted cluster configuration interaction, HF/configuration interaction singles (CIS) levels and more realistic polyene systems at the HF/CIS level. The calculated vertical excitation energies for lowest excited states are in reasonable accordance with those determined by the calculations of the whole systems with traditional methods, showing that our new fragment-based method can give good estimates for low-lying energy spectra of both weak and moderate interaction systems with economic computational costs.

Advances in upconversion luminescence nanomaterial-based biosensor for virus diagnosis.

Various infectious viruses have been posing a major threat to global public health, especially SARS-CoV-2, which has already claimed more than six million lives up to now. Tremendous efforts have been made to develop effective techniques for rapid and reliable pathogen detection. The unique characteristics of upconversion nanoparticles (UCNPs) pose numerous advantages when employed in biosensors, and they are a promising candidate for virus detection. Herein, this Review will discuss the recent advancement in the UCNP-based biosensors for virus and biomarkers detection. We summarize four basic principles that guide the design of UCNP-based biosensors, which are utilized with luminescent or electric responses as output signals. These strategies under fundamental mechanisms facilitate the enhancement of the sensitivity of UCNP-based biosensors. Moreover, a detailed discussion and benefits of applying UCNP in various virus bioassays will be presented. We will also address some obstacles in these detection techniques and suggest routes for progress in the field. These progressions will undoubtedly pose UCNP-based biosensors in a prominent position for providing a convenient, alternative approach to virus detection.

Forecasting System of Computational Time of DFT/TDDFT Calculations under the Multiverse Ansatz via Machine Learning and Cheminformatics.

With the view of achieving a better performance in task assignment and load-balancing, a top-level designed forecasting system for predicting computational times of density-functional theory (DFT)/time-dependent DFT (TDDFT) calculations is presented. The computational time is assumed as the intrinsic property for the molecule. Based on this assumption, the forecasting system is established using the "reinforced concrete", which combines the cheminformatics, several machine-learning (ML) models, and the framework of many-world interpretation (MWI) in multiverse ansatz. Herein, the cheminformatics is used to recognize the topological structure of molecules, the ML models are used to build the relationships between topology and computational cost, and the MWI framework is used to hold various combinations of DFT functionals and basis sets in DFT/TDDFT calculations. Calculated results of molecules from the DrugBank dataset show that (1) it can give quantitative predictions of computational costs, typical mean relative errors can be less than 0.2 for DFT/TDDFT calculations with derivations of ±25% using the exactly pretrained ML models and (2) it can also be employed to various combinations of DFT functional and basis set cases without exactly pretrained ML models, while only slightly enlarge predicting errors.

Variational Multistate Density Functional Theory for a Balanced Treatment of Static and Dynamic Correlations.

Here, an approach to variational multistate density functional theory (vMSDFT) is explored. In this approach, the Kohn-Sham orbitals as well as configuration coefficients were simultaneously optimized, thus yielding a full variational minimum. Furthermore, this work also proposes two important improvements on the MSDFT framework. First, a "point-to-point correction" is used to correct the static correlation present in the DFT framework. Therefore, double counting of static correlation in vMSDFT is mitigated. Second, a general form to construct the transition density functional in the vMSDFT framework is proposed, which allows for the properties of vMSDFT wave functions to be standardized to the complete active space self-consistent field properties. The utility of vMSDFT is illustrated on molecular systems of interest including bond breaking, diradicals, excited states, and conical intersections. The numerical results suggest that the accuracy of vMSDFT is in close agreement with the high-level multireference methods.