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Using these optimized basis sets, we systematically converge the AFQMC calculations to the complete basis set and thermodynamic limit and find excellent agreement with experiment for the systems studied. Although we focus on AFQMC, our basis set generation procedure is independent of the subsequent correlated wavefunction method used.Temperature-dependent thermal conductivities are reported for one-dimensional (1D) hydrogen-bonding ferroelectric crystals of isostructural compounds NH4HSO4 and RbHSO4. As the temperature was decreased from 300 K, at which point they were paraelectric in the P21/n space group, their thermal conductivities decreased, similar to those of glassy materials. At the ferroelectric transition points (T1A = 270 K for NH4HSO4 and T1R = 264 K for RbHSO4), a change from P21/n to Pn space groups was observed, and the thermal conductivity of the NH4HSO4 crystal decreased without any anomalies, whereas that of RbHSO4 increased, similar to that of crystalline materials. At the second ferroelectric-to-paraelectric transition point of NH4HSO4 (T2A = 154 K), the thermal conductivity increased from 1.00 W m-1 K to 1.32 W m-1 K and increased with a subsequent decrease in temperature, similar to that of crystalline materials. [https://www.selleckchem.com/products/kartogenin.html selleck] Single-crystal x-ray structure analyses revealed that the thermal conductivity transition of RbHSO4 at T1R = 264 K corresponds to the rotational motion excitation of the HSO4- chains. The abrupt thermal conductivity jump of NH4HSO4 was likely related to the order-disorder type transition in NH4+ ions, accompanied by lattice vibration excitation, coupled with internal rotation. At the T2A ferroelectric-to-paraelectric phase transition of NH4HSO4, 21 crystal symmetry recovery was observed, similar to the Rochelle salt, and the space group at low temperatures was P21/n. For the RbHSO4 crystals, the thermal conductivity parallel to the 1D chains was 1.5-times higher than the corresponding perpendicular orientation.Broken-symmetry calculations of diradicals exploit the mean-field energies of determinants that are not eigenfunctions of the Ŝ2 operator, the mean value of which is close to 1 for the ms = 0 solution. This spin contamination must be corrected. Two different contributions affect ⟨Ŝ2⟩, namely, the mixing between neutral and ionic valence bond components, the so-called kinetic exchange, which decreases ⟨Ŝ2⟩, and the spin polarization of the supposedly closed shell orbitals, which increases ⟨Ŝ2⟩. The popular Yamaguchi formula is valid for the first effect but irrelevant for the second one. From a few constrained broken-symmetry calculations, one may treat separately the two contributions and apply their specific spin decontamination correction. This work proposes a consistent spin-decontaminated procedure for the evaluation of singlet-triplet gaps in diradicals.We have used diffusion Monte Carlo (DMC) to perform calculations on the L7 benchmark set. DMC is a stochastic numerical integration scheme in real-space and part of a larger set of quantum Monte Carlo methods. The L7 set was designed to test the ability of electronic structure methods to include dispersive interactions. While the agreement between DMC and quantum-chemical state-of-the-art methods is excellent for some of the structures, there are significant differences in others. In contrast to wavefunction-based quantum chemical methods, DMC is a first-principle many-body method with the many-body wavefunction evolving in real space. It includes explicitly all electron-electron interactions and is relatively insensitive to the size of the basis set.Single-molecule experimental techniques track the real-time dynamics of molecules by recording a small number of experimental observables. Following these observables provides a coarse-grained, low-dimensional representation of the conformational dynamics but does not furnish an atomistic representation of the instantaneous molecular structure. Takens's delay embedding theorem asserts that, under quite general conditions, these low-dimensional time series can contain sufficient information to reconstruct the full molecular configuration of the system up to an a priori unknown transformation. By combining Takens's theorem with tools from statistical thermodynamics, manifold learning, artificial neural networks, and rigid graph theory, we establish an approach, Single-molecule TAkens Reconstruction, to learn this transformation and reconstruct molecular configurations from time series in experimentally measurable observables such as intramolecular distances accessible to single molecule Förster resonance energy transfer. We demonstrate the approach in applications to molecular dynamics simulations of a C24H50 polymer chain and the artificial mini-protein chignolin. The trained models reconstruct molecular configurations from synthetic time series data in the head-to-tail molecular distances with atomistic root mean squared deviation accuracies better than 0.2 nm. This work demonstrates that it is possible to accurately reconstruct protein structures from time series in experimentally measurable observables and establishes the theoretical and algorithmic foundations to do so in applications to real experimental data.Electrodeposition and stripping are fundamental electrochemical processes for metals and have gained importance in rechargeable Li-ion batteries due to lithium metal electrodes. The electrode kinetics associated with lithium metal electrodeposition and stripping is crucial in determining the performance at fast discharge and charge, which is important for electric vertical takeoff and landing (eVTOL) aircraft and electric vehicles (EV). In this work, we show the use of Marcus-Hush-Chidsey (MHC) kinetics to accurately predict the Tafel curve data from the work of Boyle et al. [ACS Energy Lett. 5(3), 701 (2020)]. We discuss the differences in predictions of reorganization energies from the Marcus-Hush and the MHC models for lithium metal electrodes in four solvents. The MHC kinetic model is implemented and open-sourced within Cantera. Using the reaction kinetic model in a pseudo-2D battery model with a lithium anode paired with a LiFePO4 cathode, we show the importance of accounting for the MHC kinetics and compare it to the use of Butler-Volmer and Marcus-Hush kinetic models.