Computational studies of crystal nucleation can be impacted by finite size effects, primarily due to unphysical interactions between crystalline nuclei and their periodic images. It is, however, not always feasible to systematically investigate the sensitivity of nucleation kinetics and mechanism to system size due to large computational costs of nucleation studies. Here, we use jumpy forward flux sampling to accurately compute the rates of heterogeneous ice nucleation in the vicinity of square-shaped model structureless ice nucleating particles (INPs) of different sizes and identify three distinct regimes for the dependence of rate on the INP dimension, L. For small INPs, the rate is a strong function of L due to the artificial spanning of critical nuclei across the periodic boundary. Intermediate-sized INPs, however, give rise to the emergence of non-spanning "proximal" nuclei that are close enough to their periodic images to fully structure the intermediary liquid. While such proximity can facilitate nucleation, its effect is offset by the higher density of the intermediary liquid, leading to artificially small nucleation rates overall. The critical nuclei formed at large INPs are neither spanning nor proximal. Yet, the rate is a weak function of L, with its logarithm scaling linearly with 1/L. The key heuristic emerging from these observations is that finite size effects will be minimal if critical nuclei are neither spanning nor proximal and if the intermediary liquid has a region that is structurally indistinguishable from the supercooled liquid under the same conditions.We present a reduced scaling and exact reformulation of state specific complete active space second-order perturbation (CASPT2) analytical gradients in terms of the MP2 and Fock derivatives using the supporting subspace method. This work follows naturally from the supporting subspace formulation of the CASPT2 energy in terms of the MP2 energy using dressed orbitals and Fock builds. For a given active space configuration, the terms corresponding to the MP2-gradient can be evaluated with O(N5) operations, while the rest of the calculations can be computed with O(N3) operations using Fock builds, Fock gradients, and linear algebra. When tensor-hyper-contraction is applied simultaneously, the computational cost can be further reduced to O(N4) for a fixed active space size. The new formulation enables efficient implementation of CASPT2 analytical gradients by leveraging the existing graphical processing unit (GPU)-based MP2 and Fock routines. We present benchmark results that demonstrate the accuracy and performance of the new method. Example applications of the new method in ab initio molecular dynamics simulation and constrained geometry optimization are given.The complete-active-space self-consistent field (CASSCF) method is a canonical electronic structure theory that holds a central place in conceptualizing and practicing first principles simulations. For application to realistic molecules, however, the CASSCF must be approximated to circumvent its exponentially scaling computational costs. Applying the many-body expansion-also known as the method of increments-to CASSCF (iCASSCF) has been shown to produce a polynomially scaling method that retains much of the accuracy of the parent theory and is capable of treating full valence active spaces. Due to an approximation made in the orbital gradient, the orbital parameters of the original iCASSCF formulation could not be variationally optimized, which limited the accuracy of its nuclear gradient. Herein, a variational iCASSCF is introduced and implemented, where all parameters are fully optimized during energy minimization. This method is able to recover electronic correlations from the full valence space in large systems, produce accurate gradients, and optimize stable geometries as well as transition states. Demonstrations on challenging test cases, such as the oxoMn(salen)Cl complex with 84 electrons in 84 orbitals and the automerization of cyclobutadiene, show that the fully variational iCASSCF is a powerful tool for describing challenging molecular chemistries.Surface plasmon resonance microscopy (SPRM) has been widely used as a sensitive imaging platform for chemical and biological analysis. The SPRM system inevitably suffers from focus inhomogeneity and drifts, especially in long-term recordings, leading to distorted images and inaccurate quantification. Traditional focus correction approaches require additional optical parts to detect and adjust focal conditions. Herein, we propose a deep-learning-based image processing method to gain autofocused SPRM images, without increasing the complexity of the optical systems.  https://www.selleckchem.com/btk.html  We trained a generative adversarial network (GAN) model with thousands of SPRM images of nanoparticles acquired at different focal distances. The trained model was able to directly generate focused SPRM images from single-shot defocused images, with no prior knowledge of the focus conditions during recording. Experiments using Au nanoparticles show that this method is effective in both static and time-lapse monitoring. The proposed autofocus technique thus provides an approach for improving the consistency among SPRM studies and for long-term monitoring.Transition metal catalysis that utilizes N-heterocyclic carbenes as noninnocent ligands in promoting transformations has not been well studied. We report here a cyclic (alkyl)(amino)carbene (CAAC) ligand-promoted nitro deoxygenative hydroboration with cost-effective chromium catalysis. Using 1 mol % of CAAC-Cr precatalyst, the addition of HBpin to nitro scaffolds leads to deoxygenation, allowing for the retention of various reducible functionalities and the compatibility of sensitive groups toward hydroboration, thereby providing a mild, chemoselective, and facile strategy to form anilines, as well as heteroaryl and aliphatic amine derivatives, with broad scope and particularly high turnover numbers (up to 1.8 × 106). Mechanistic studies, based on theoretical calculations, indicate that the CAAC ligand plays an important role in promoting polarity reversal of hydride of HBpin; it serves as an H-shuttle to facilitate deoxygenative hydroboration. The preparation of several commercially available pharmaceuticals by means of this strategy highlights its potential application in medicinal chemistry.