Quantum Manifestations of Graphene Edge Stress and Edge Instability: A First-Principles Study

We have performed first-principles calculations of graphene edge stresses, which display two interesting quantum manifestations absent from the classical interpretation: the armchair edge stress oscillates with a nanoribbon width, and the zigzag edge stress is noticeably reduced by spin polarization. Such quantum stress effects in turn manifest in mechanical edge twisting and warping instability, showing features not captured by empirical potentials or continuum theory. Edge adsorption of H and Stone-Wales reconstruction are shown to provide alternative mechanisms in relieving the edge compression and hence to stabilize the planar edge structure.Comment: 5figure

Anharmonic effect on lattice distortion, orbital ordering and magnetic properties in Cs2AgF4

We develop the cluster self-consistent field method incorporating both electronic and lattice degrees of freedom to study the origin of ferromagnetism in Cs$_{2}$AgF$_{4}$. After self-consistently determining the harmonic and anharmonic Jahn-Teller distortions, we show that the anharmonic distortion stabilizes the staggered x$^{2}$-z$^{2}$/y$^{2}$-z$^{2}$ orbital and ferromagnetic ground state, rather than the antiferromagnetic one. The amplitudes of lattice distortions, Q$_{2}$ and Q$_{3}$, the magnetic coupling strengthes, J$_{x,y}$, and the magnetic moment, are in good agreement with the experimental observation.Comment: 13 pages, 5 figure

Protocol for dissecting cascade computational components in neural networks of a visual system

Finding the complete functional circuits of neurons is a challenging problem in brain research. Here, we present a protocol, based on visual stimuli and spikes, for obtaining the complete circuit of recorded neurons using spike-triggered nonnegative matrix factorization. We describe steps for data preprocessing, inferring the spatial receptive field of the subunits, and analyzing the module matrix. This approach identifies computational components of the feedforward network of retinal ganglion cells and dissects the network structure based on natural image stimuli.For complete details on the use and execution of this protocol, please refer to Jia et al. (2021).

Local Electronic and Magnetic Studies of an Artificial La2FeCrO6 Double Perovskite

Through the utilization of element-resolved polarized x-ray probes, the electronic and magnetic state of an artificial La2FeCrO6 double perovskite were explored. Applying unit-cell level control of thin film growth on SrTiO3 (111), the rock salt double perovskite structure can be created for this system, which does not have an ordered perovskite phase in the bulk. We find that the Fe and Cr are in the proper 3+ valence state, but, contrary to previous studies, the element-resolved magnetic studies find the moments in field are small and show no evidence of a sizable magnetic moment in the remanent state.Comment: 3 pages, 4 figure

Demonstrate the removal efficiency and capacity of MOF materials for krypton recovery

Metal organic framework materials (MOFs) were developed and tested in support of the U.S. Department of Energy Office of Nuclear Energy, Fuel Cycle Technology Separations and Waste Forms Campaign. Specifically, materials are being developed for the removal of xenon (Xe) and krypton (Kr) from gaseous products of nuclear fuel reprocessing unit operations. Two metal organic framework structures were investigated in greater detail to demonstrate the removal efficiency and capacity of MOF materials for krypton recovery. Our two bed breakthrough measurements on NiDOBDC and FMOFCu indicate these materials can capture and separate parts per million levels of Xe and Kr from air. The removal efficiency and adsorption capacity for Kr on these two MOFs were further increased upon removal of Xe upfront

A Spike-Timing Pattern Based Neural Network Model for the Study of Memory Dynamics

It is well accepted that the brain's computation relies on spatiotemporal activity of neural networks. In particular, there is growing evidence of the importance of continuously and precisely timed spiking activity. Therefore, it is important to characterize memory states in terms of spike-timing patterns that give both reliable memory of firing activities and precise memory of firing timings. The relationship between memory states and spike-timing patterns has been studied empirically with large-scale recording of neuron population in recent years. Here, by using a recurrent neural network model with dynamics at two time scales, we construct a dynamical memory network model which embeds both fast neural and synaptic variation and slow learning dynamics. A state vector is proposed to describe memory states in terms of spike-timing patterns of neural population, and a distance measure of state vector is defined to study several important phenomena of memory dynamics: partial memory recall, learning efficiency, learning with correlated stimuli. We show that the distance measure can capture the timing difference of memory states. In addition, we examine the influence of network topology on learning ability, and show that local connections can increase the network's ability to embed more memory states. Together theses results suggest that the proposed system based on spike-timing patterns gives a productive model for the study of detailed learning and memory dynamics

Magnetic properties of a novel Pr Fe Ti phase

In a systematic study of the (Pr1−xTix)Fe5 alloy series, the (Pr0.65Ti0.35)Fe5 alloy has been found to have a dominant phase with either the rhombohedral Th2Zn17 structure or the newly discovered Nd2(Fe,Ti)19 (S. J. Collocott, R. K. Day, J. B. Dunlop, and R. L. Davis, in Proceedings of the Seventh International Symposium on Magnetic Anisotropy and Coercivity in R‐T Alloys, Canberra, July 1992, p. 437) structure, depending on the annealing procedure. Powder‐x‐ray‐diffraction patterns and scanning electron microscopy show that the sample annealed at a temperature of 850 °C followed by 1000 °C has the 2:17 structure whereas annealing at 1000 °C directly leads to the new 2:19 structure. Energy‐dispersive x‐ray analysis yields Pr:Fe:Ti ratios of 10.7:86.2:3.1 for the Pr2(Fe,Ti)17 phase and 9.2:85.9:4.9 for the Pr2(Fe,Ti)19 phase. 57 Fe Mössbauer spectroscopy (at 295 K) gives values for the average 57 Fe hyperfine field of 15.7 T for the 2:17 phase and 17.5 T for the 2:19 phase, respectively