Robust and Accurate Computational Estimation of the Polarizability Tensors of Macromolecules

Fragment-Based Deep Learning for Simultaneous Prediction of Polarizabilities and NMR Shieldings of Macromolecules and Their Aggregates

Simultaneous prediction of the molecular response properties, such as polarizability and the NMR shielding constant, at a low computational cost is an unresolved issue. We propose to combine a linear-scaling generalized energy-based fragmentation (GEBF) method and deep learning (DL) with both molecular and atomic information-theoretic approach (ITA) quantities as effective descriptors. In GEBF, the total molecular polarizability can be assembled as a linear combination of the corresponding quantities calculated from a set of small embedded subsystems in GEBF. In the new GEBF-DL(ITA) protocol, one can predict subsystem polarizabilities based on the corresponding molecular wave function (thus electron density and ITA quantities) and DL model rather than calculate them from the computationally intensive coupled-perturbed Hartree-Fock or Kohn-Sham equations and finally obtain the total molecular polarizability via a linear combination equation. As a proof-of-concept application, we predict the molecular polarizabilities of large proteins and protein aggregates. GEBF-DL(ITA) is shown to be as accurate enough as GEBF, with mean absolute percentage error <1%. For the largest protein aggregate (>4000 atoms), GEBF-DL(ITA) gains a speedup ratio of 3 compared with GEBF. It is anticipated that when more advanced electronic structure methods are used, this advantage will be more appealing. Moreover, one can also predict the NMR chemical shieldings of proteins with reasonably good accuracy. Overall, the cost-efficient GEBF-DL(ITA) protocol should be a robust theoretical tool for simultaneously predicting polarizabilities and NMR shieldings of large systems.

Accurate and Efficient Prediction of Post-Hartree-Fock Polarizabilities of Condensed-Phase Systems

To accurately and efficiently predict the molecular response properties (such as polarizability) at post-Hartree-Fock levels for condensed-phase systems under periodic boundary conditions (PBC) is still an unaccomplished and ongoing task. We demonstrate that static isotropic polarizabilities can be cost-effectively predicted at post-Hartree-Fock levels by combining the linear-scaling generalized energy-based fragmentation (GEBF) and information-theoretic approach (ITA) quantities. In PBC-GEBF, the total molecular polarizability of an extended system is obtained as a linear combination of the corresponding quantities of a series of small embedded subsystems of several monomers. Here, we show that in the PBC-GEBF-ITA framework, one can obtain the molecular polarizabilities and establish linear relations to ITA quantities. Once these relations are established for smaller subsystems, one can predict the polarizabilities of larger subsystems directly from the molecular wavefunction (or electron density) via ITA quantities. Alternatively, one can determine the total molecular polarizability via a linear combination equation in PBC-GEBF. We have corroborated that this newly proposed PBC-GEBF-ITA protocol is much more efficient than the original PBC-GEBF approach but is not much less accurate and that this conclusion holds for both many-body perturbation theory and the coupled cluster calculations. Good efficiency and transferability of the PBC-GEBF-ITA protocol are demonstrated for periodic systems with several hundred atoms in a unit cell.

Excited-State Polarizabilities: A Combined Density Functional Theory and Information-Theoretic Approach Study

Accurate and efficient determination of excited-state polarizabilities (α) is an open problem both experimentally and computationally. Following our previous work, (Phys. Chem. Chem. Phys. 2023, 25, 2131−2141), in which we employed simple ground-state (S0) density-related functions from the information-theoretic approach (ITA) to accurately and efficiently evaluate the macromolecular polarizabilities, in this work we aimed to predict the lowest excited-state (S1) polarizabilities. The philosophy is to use density-based functions to depict excited-state polarizabilities. As a proof-of-principle application, employing 2-(2′-hydroxyphenyl)benzimidazole (HBI), its substituents, and some other commonly used ESIPT (excited-state intramolecular proton transfer) fluorophores as model systems, we verified that either with S0 or S1 densities as an input, ITA quantities can be strongly correlated with the excited-state polarizabilities. When transition densities are considered, both S0 and S1 polarizabilities are in good relationships with some ITA quantities. The transferability of the linear regression model is further verified for a series of molecules with little or no similarity to those molecules in the training set. Furthermore, the excitation energies can be predicted based on multivariant linear regression equations of ITA quantities. This study also found that the nature of both the ground-state and excited-state polarizabilities of these species are due to the spatial delocalization of the electron density.

Efficient and accurate density-based prediction of macromolecular polarizabilities

Accurately and efficiently predicting macromolecules' polarizabilities is an open problem. In this work, we employ a few simple density-based quantities from the information-theoretic approach (ITA) to predict polarizability of proteins. We first build quantitative structure/property relationships between molecular polarizabilities and ITA quantities. We then verify the broad applicability of ITA quantities for polarizability prediction for inorganic, organic, and biological systems with both localized and delocalized electronic structure. As a proof-of-concept application, we predict the molecular polarizabilities of complex proteins. Based on the linear regression equations for 20 natural amino acid residues, 400 dipeptides, and 8000 tripeptides, one then predicts the molecular polarizability of a larger peptide or even a protein once the molecular wavefunction is obtained. Because it is extremely costly to determine the wavefunction for a macromolecule like a protein, we propose to combine the ITA with the linear-scaling generalized energy-based fragmentation (GEBF) method to predict the macromolecular polarizability. In GEBF, the total molecular polarizability is obtained as a linear combination of the corresponding quantities from a series of small subsystems. We can predict them based on the subsystem wavefunction and linear regression equations rather than compute them from the nearly-intractable coupled-perturbed Hartree-Fock or Kohn-Sham equations for the whole macromolecule. Computational results showcase that the GEBF-ITA protocol should be an inexpensive yet accurate theoretical tool for predicting macromolecular polarizabilities.

A Density Functional Theory and Information-Theoretic Approach Study of Interaction Energy and Polarizability for Base Pairs and Peptides

Using density functional theory (DFT) and the information-theoretic approach (ITA) quantities to appreciate the energetics and properties of biopolymers is still an unaccomplished and ongoing task. To this end, we studied the building blocks of nucleic acid base pairs and small peptides. For base pairs, we have dissected the relative importance of energetic components by using two energy partition schemes in DFT. Our results convincingly show that the exchange-correlation effect predominantly governs the molecular stability of base pairs while the electrostatic potential plays a minor but indispensable role, and the steric effect is trivial. Furthermore, we have revealed that simple density-based ITA functions are in good relationships with molecular polarizabilities for a series of 30 hydrogen-bonded base pairs and all 20 natural α-amino acids, 400 dipeptides, and 8000 tripeptides. Based on these lines, one can easily predict the molecular polarizabilities of larger peptides, even proteins as long as the total molecular wavefunction is available, rather than solving the computationally demanding coupled-perturbed Hartree–Fock (CPHF) equation or its DFT counterpart coupled-perturbed Kohn–Sham (CPKS) equation.

A Systematic and Comparative Analysis of Four Major Classes of DFT Functionals to Compute Linear and Nonlinear Optical Properties of Benchmark Molecules

This study spotlights the fundamental insights about the systematic and comparative analysis of four famous hybrid classes of density functional theory (DFT) methods and their efficacy to calculate the linear and nonlinear optical (NLO) polarizabilities. For this study, urea and para-nitroaniline ([Formula: see text]-NA) molecular geometries are used as prototypes to calculate their linear and NLO properties. For comparative purposes, these molecules are often used as reference organic molecules for determination of NLO response properties and there is a dire need for such a benchmark database to be utilized by the researchers. We report systematically a range of functionals including hybrid (B3LYP, PBE1PBE, BH and HLYP), meta-hybrid (M06, M06-2X, M06-HF, M06-L), long-range corrected (CAM-B3LYP, LC-BLYP, LC-B97D, LC-B97D3) and functional with dispersion correction ([Formula: see text]B97, [Formula: see text]B97X, [Formula: see text]B97XD, HSEH1PBE). These groups are evaluated and their efficiency to calculate linear and NLO properties is graphically compared with each other. Overall, there are less deviations among different functionals for calculating dipole moments of [Formula: see text]-NA and urea while these deviations enhance as one moves from dipole moment to linear polarizability and nonlinear hyperpolarizabilities. In general, if we look at the trends, the polarizability values of B3LYP, M06-L, CAM-B3LYP and HSEH1PBE are relatively large and can be compared with each other. The dispersion corrected and long-range corrected functionals show more systematic deviations. For instance, among dispersion corrected functionals, the amplitudes of dipole moments, linear polarizability and NLO polarizabilities show an increasing trend as [Formula: see text]. It is also important to note that LC-B97D and LC-B97D3 of long-range corrected functional have observed exactly the same values of all the calculated parameters. A good agreement is being observed in static first and second hyperpolarizabilities of urea (B3LYP, M06-L, M06 and HSEH1PBE) and [Formula: see text]-NA (B3LYP, M06, M06-L, CAM-B3LYP and HSEH1PBE). Thus, we believe that the current investigation will provide the benchmark data of reference NLO molecules at different methods for theoretical community and molecular level insights for experimental community to design better NLO materials for hi-tech NLO applications.

Preparation and Characterization of Transparent Polyimide Nanocomposite Films with Potential Applications as Spacecraft Antenna Substrates with Low Dielectric Features and Good Sustainability in Atomic-Oxygen Environments

Optically transparent polyimide (PI) films with good dielectric properties and long-term sustainability in atomic-oxygen (AO) environments have been highly desired as antenna substrates in low earth orbit (LEO) aerospace applications. However, PI substrates with low dielectric constant (low-D_k), low dielectric dissipation factor (low-D_f) and high AO resistance have rarely been reported due to the difficulties in achieving both high AO survivability and good dielectric parameters simultaneously. In the present work, an intrinsically low-D_k and low-D_f optically transparent PI film matrix, poly[4,4′-(hexafluoroisopropylidene)diphthalic anhydride-co-2,2-bis(4-(4-aminophenoxy)phenyl)hexafluoropropane] (6FPI) was combined with a nanocage trisilanolphenyl polyhedral oligomeric silsesquioxane (TSP-POSS) additive in order to afford novel organic–inorganic nanocomposite films with enhanced AO-resistant properties and reduced dielectric parameters. The derived 6FPI/POSS films exhibited the D_k and D_f values as low as 2.52 and 0.006 at the frequency of 1 MHz, respectively. Meanwhile, the composite films showed good AO resistance with the erosion yield as low as 4.0 × 10⁻²⁵ cm³/atom at the exposure flux of 4.02 × 10²⁰ atom/cm², which decreased by nearly one order of magnitude compared with the value of 3.0 × 10⁻²⁴ cm³/atom of the standard PI-ref Kapton^® film.

Benchmarking Correlated Methods for Static and Dynamic Polarizabilities: The T145 Data Set Evaluated with RPA, RPA(D), HRPA, HRPA(D), SOPPA, SOPPA(CC2), SOPPA(CCSD), CC2, and CCSD

Due to the importance of predicting static and dynamic polarizabilities, the performance of various correlated linear response methods including random phase approximation (RPA), RPA(D), higher-order random phase approximation (HRPA), HRPA(D), second-order polarization propagator approximation (SOPPA), SOPPA(CC2), SOPPA(CCSD), CC2, and CCSD has been evaluated against CCSD(T) (static case) and CCSD (dynamic cases) for the T145 set of 145 organic molecules. The benchmark reveals that the HRPA(D) method has the best performance for both static and dynamic polarizabilities apart from CCSD. RPA(D) ranks second for the dynamic cases and third for the static case. Using coupled-cluster amplitudes in SOPPA(CCSD) and SOPPA(CC2), the SOPPA results are significantly improved. The HRPA method has the largest deviations from the reference values for both cases. In general, according to the performance and computational cost of the methods, the HRPA(D) and RPA(D) methods are proposed for calculations of static and dynamic polarizabilities of this and similar sets of molecules.

Intrinsic high-k–low-loss dielectric polyimides containing ortho-position aromatic nitrile moieties: reconsideration on Clausius–Mossotti equation

Intrinsic high-k–low-loss dielectric polyimides containing ortho-position aromatic nitrile moieties were synthesized. 2CN-BTDA shows a D_k of 4.80, D_f of 1.57 × 10⁻³ at 1 kHz (25 °C), E_B of 219.4 kV mm⁻¹ with energy density of 1.023 J cm⁻³ and T_g of 325 °C.

Variations in Proteins Dielectric Constants

Using a new semi-empirical method for calculating molecular polarizabilities and the Clausius-Mossotti relation, we calculated the static dielectric constants of dry proteins for all structures in the protein data bank (PDB). The mean dielectric constant of more than 150,000 proteins is ϵ r = 3 . 23 with a standard deviation of 0.04, which agrees well with previous measurement for dry proteins. The small standard deviation results from the strong correlation between the molecular polarizability and the volume of the proteins. We note that non-amino acid cofactors such as Chlorophyll may alter the dielectric environment significantly. Furthermore, our model shows anisotropies of the dielectric constant within the same molecule according to the constituents amino acids and cofactors. Finally, by changing the amino acid protonation states, we show that a change of pH does not have a significant effect on the dielectric constants of proteins.

Controlled beams of shock-frozen, isolated, biological and artificial nanoparticles

X-ray free-electron lasers promise diffractive imaging of single molecules and nanoparticles with atomic spatial resolution. This relies on the averaging of millions of diffraction patterns of identical particles, which should ideally be isolated in the gas phase and preserved in their native structure. Here, we demonstrated that polystyrene nanospheres and Cydia pomonella granulovirus can be transferred into the gas phase, isolated, and very quickly shock-frozen, i.e., cooled to 4 K within microseconds in a helium-buffer-gas cell, much faster than state-of-the-art approaches. Nanoparticle beams emerging from the cell were characterized using particle-localization microscopy with light-sheet illumination, which allowed for the full reconstruction of the particle beams, focused to < 100   μ m , as well as for the determination of particle flux and number density. The experimental results were quantitatively reproduced and rationalized through particle-trajectory simulations. We propose an optimized setup with cooling rates for particles of few-nanometers on nanosecond timescales. The produced beams of shock-frozen isolated nanoparticles provide a breakthrough in sample delivery, e.g., for diffractive imaging and microscopy or low-temperature nanoscience.