Boosting thermoelectric performance of HfSe monolayer by selectivity chemical adsorption.

In this work, a strategy to boosting thermoelectric (TE) performance of 2D materials is explored. We find that, appropriate chemical adsorption of atoms can effectively increase the TE performance of HfSe monolayer. Our results show that the adsorption of Ni atom on HfSe monolayer (Ni-HfSe) can improve the optimal power factor PF and ZT at 300 K, increased by more than ∼67% and ∼340%, respectively.

Strain Tunable Thermoelectric Material: Janus ZrSSe Monolayer.

Thermoelectric (TE) performance of the Janus ZrSSe monolayer under biaxial strain is systematically explored by the first-principles approach and Boltzmann transport theory. Our results show that the Janus ZrSSe monolayer has excellent chemical, dynamical, thermal, and mechanical stabilities, which provide a reliable platform for strain tuning. The electronic structure and TE transport parameters of the Janus ZrSSe monolayer can be obviously tuned by biaxial strain.

Climate network stability measures of El Niño variability.

One of the crucial aspects that is currently limiting the success of El Niño predictions is the stability of the slowly varying Pacific climate state. This property determines whether or not sea surface temperature perturbations will be amplified by coupled ocean-atmosphere feedbacks. The so-called Bjerknes stability index has been developed for this purpose, but its evaluation is severely constrained by data availability.

Unified functional network and nonlinear time series analysis for complex systems science: The pyunicorn package.

We introduce the pyunicorn (Pythonic unified complex network and recurrence analysis toolbox) open source software package for applying and combining modern methods of data analysis and modeling from complex network theory and nonlinear time series analysis. pyunicorn is a fully object-oriented and easily parallelizable package written in the language Python. It allows for the construction of functional networks such as climate networks in climatology or functional brain networks in neuroscience representing the structure of statistical interrelationships in large data sets of time series and, subsequently, investigating this structure using advanced methods of complex network theory such as measures and models for spatial networks, networks of interacting networks, node-weighted statistics, or network surrogates.

[Study on weightlessness dynamics simulated by neutral buoyancy in air-driven shell].

Objective: To provide theoretical support for weightlessness experiment simulated by neutral buoyancy.

Method: An air-driven shell structure was simplified into a rigid body with constant mass and variable volume. Then, rigid body dynamic model and gasdynamic model of air-driven spherical shell were established.

[Application of sensitivity analysis method in mode analysis of hypergravitation training facility].

Objective: To increase the natural frequencies of hypergravitation training facility.

Method: The natural frequencies of the hypergravitation training facility were modified by using sensitivity analysis method.

Result: The natural frequencies of the hypergravitation training facility were improved by modification of physical and geometrical parameters of sensitive elements.