Gope, K. ; Livshits, E. ; Bittner, D. M. ; Baer, R. ; Strasser, D. Absence of Triplets in Single-Photon Double Ionization of Methanol
. The Journal of Physical Chemistry Letters 2020
, 8108–8113. Publisher's VersionAbstract
Despite the abundance of data concerning single-photon double ionization of methanol, the spin state of the emitted electron pair has never been determined. Here we present the ﬁrst evidence that identiﬁes the emitted electron pair spin as overwhelmingly singlet when the dication forms in low-energy conﬁgurations. The experimental data show that while the yield of the CH2O+ + H3+ Coulomb explosion channel is abundant, the metastable methanol dication is largely absent. According to high-level ab initio simulations, these facts indicate that photoionization promptly forms singlet dication states, where they quickly decompose through various channels, with signiﬁcant H3+ yields on the low-lying states. In contrast, if we assume that the initial dication is formed in one of the low-lying triplet states, the ab initio simulations exhibit a metastable dication, contradicting the experimental ﬁndings. Comparing the average simulated branching ratios with the experimental data suggests a \textgreater3 order of magnitude enhancement of the singlet:triplet ratio compared with their respective 1:3 multiplicities.
Arnon, E. ; Rabani, E. ; Neuhauser, D. ; Baer, R. Efficient Langevin dynamics for "noisy" forces
. J. Chem. Phys. 2020
, 161103. Publisher's VersionAbstract
Efficient Boltzmann-sampling using first-principles methods is challenging for extended systems due to the steep scaling of electronic structure methods with the system size. Stochastic approaches provide a gentler system-size dependency at the cost of introducing "noisy" forces, which serve to limit the efficiency of the sampling. In the first-order Langevin dynamics (FOLD), efficient sampling is achievable by combining a well-chosen preconditioning matrix S with a time-step-bias-mitigating propagator (Mazzola et al., Phys. Rev. Lett., 118, 015703 (2017)). However, when forces are noisy, S is set equal to the force-covariance matrix, a procedure which severely limits the efficiency and the stability of the sampling. Here, we develop a new, general, optimal, and stable sampling approach for FOLD under noisy forces. We apply it for silicon nanocrystals treated with stochastic density functional theory and show efficiency improvements by an order-of-magnitude.