Dynamics of hydration water is essential for the function of biomacromolecules. Previous studies have demonstrated that water molecules exhibit subdiffusion on the surface of biomacromolecules; yet the microscopic mechanism remains vague. Here, by performing neutron scattering, molecular dynamics simulations, and analytic modeling on hydrated perdeuterated protein powders, we found water molecules jump randomly between trapping sites on protein surfaces, whose waiting times obey a broad distribution, resulting in subdiffusion. Moreover, the subdiffusive exponent gradually increases with observation time towards normal diffusion due to a many-body volume-exclusion effect.

The ion transportation mechanism in a high-concentration solution remains unclear due to the complexity of the strong ion–ion/ion–solvent interaction, resulting in the invalidation of most ionic conducting theories based on diluted solutions. Here, a superconcentrated electrolyte (water-in-salt) is investigated by multiple experimental techniques, including advanced tools (NMR, synchrotron X-ray diffraction, and spallation neutron scattering), combined with molecular dynamics (MD) simulation to draw out its unique microstructure and uncover its intrinsic relationship with the ionic transportation. Based on the results, we firstly proposed the ionic transport model for the water-in-salt electrolyte, where the solid-like nano-anion clusters construct a superfluid framework and the lithium ion is able to move freely like in an ionic atmosphere. Our model gives a unified explanation to the unique phenomena previously discovered in water-in-salt electrolytes, including the decoupling of conductivity–viscosity and the nanophase separation between the anion and water. Our findings on the microstructure of the super-high-concentrated electrolyte and the involved unique Li-conducting mechanism can fill in the gap between a solid-state conductor and a dilute liquid electrolytic solution.

Coulomb interaction, following an inverse-square force-law, quantifies the amount of force between two stationary and electrically charged particles. The long-range nature of Coulomb interactions poses a major challenge to molecular dynamics simulations, which are major tools for problems at the nano-/micro-scale. Various algorithms are developed to calculate the pairwise Coulomb interactions to a linear scale, but poor scalability limits the size of simulated systems. Here, we use an efficient molecular dynamics algorithm with the random batch Ewald method on all-atom systems where the complete Fourier components in the Coulomb interaction are replaced by randomly selected mini-batches. By simulating the N-body systems up to 108 particles using 10 000 central processing unit cores, we show that this algorithm furnishes O(N) complexity, almost perfect scalability, and an order of magnitude faster computational speed when compared to the existing state-of-the-art algorithms. Further examinations of our algorithm on distinct systems, including pure water, a micro-phase separated electrolyte, and a protein solution, demonstrate that the spatiotemporal information on all time and length scales investigated and thermodynamic quantities derived from our algorithm are in perfect agreement with those obtained from the existing algorithms. Therefore, our algorithm provides a promising solution on scalability of computing the Coulomb interaction. It is particularly useful and cost-effective to simulate ultra-large systems, which is either impossible or very costly to conduct using existing algorithms, and thus will be beneficial to a broad range of problems at nano-/micro-scales.

Dynamic neutron scattering directly probes motions in biological systems on femtosecond to microsecond timescales. When combined with molecular dynamics simulation and normal mode analysis, detailed descriptions of the forms and frequencies of motions can be derived. We examine vibrations in proteins, the temperature dependence of protein motions, and concepts describing the rich variety of motions detectable using neutrons in biological systems at physiological temperatures. New techniques for deriving information on collective motions using coherent scattering are also reviewed.

We develop an accurate, highly efficient, and scalable random batch Ewald (RBE) method to conduct molecular dynamics simulations in the isothermal–isobaric ensemble (the NPT ensemble) for charged particles in a periodic box. After discretizing the Langevin equations of motion derived using suitable Lagrangians, the RBE method builds the mini-batch strategy into the Fourier space in the Ewald summation for the pressure and forces such that the computational cost is reduced to [Formula: see text] per time step. We implement the method in the Large-scale Atomic/Molecular Massively Parallel Simulator package and report accurate simulation results for both dynamical quantities and statistics for equilibrium for typical systems including all-atom bulk water and a semi-isotropic membrane system. Numerical simulations on massive supercomputing cluster are also performed to show promising central processing unit efficiency of the RBE.