Heterogeneously structured phase-change materials and memory

Phase-change memory (PCM), a non-volatile memory technology, is considered the most promising candidate for storage class memory and neuro-inspired devices. It is generally fabricated based on GeTe-Sb2Te3 pseudo-binary alloys. However, natively, it has technical limitations, such as noise and drift in electrical resistance and high current in operation for real-world device applications. Recently, heterogeneously structured PCMs (HET-PCMs), where phase-change materials are hetero-assembled with functional (barrier) materials in a memory cell, have shown a dramatic enhancement in device performance by reducing such inherent limitations. In this Perspective, we introduce recent developments in HET-PCMs and relevant mechanisms of operation in comparison with those of conventional alloy-type PCMs. We also highlight corresponding device enhancements, particularly their thermal stability, endurance, RESET current density, SET speed, and resistance drift. Last, we provide an outlook on promising research directions for HET-PCMs including PCM-based neuromorphic computing

Thermal Model Developments for Electrified Vehicles

Argonne National Laboratory has analyzed the control behavior of advanced vehicles, such as hybrid electric vehicles (HEVs), plug-in hybrid electric vehicles (PHEVs), and battery electric vehicles (BEVs), to develop simulation models and to reproduce the performance of vehicles with simulation techniques. Since many of the novel and advanced studies about transportation technologies done at Argonne use these simulation techniques, they must be well-validated to conduct and support these studies. To improve its research ability, Argonne built a new testing facility that can test vehicles under different thermal conditions (e.g., –7°C or 35°C), and it has analyzed the controls and performance of several advanced vehicles under these conditions. Further, Argonne has used the analyzed results to develop thermal component models that reproduce the thermal behavior of the vehicles. A main reason to develop thermal models is that the thermal conditions have such a significantly large impact on vehicle performance, especially with regard to advanced vehicles like HEVs or PHEVs. For instance, engine and battery efficiencies must decrease at low temperatures since the battery might not be able to provide enough power if it is very cold. Moreover, the climate control system still has a great demand for additional energy under very cold weather conditions even if the engine is not operating at all. The test data obtained from Argonne’s Advanced Powertrain Research Facility (APRF) are analyzed in order to understand the thermal impacts on controls and performance, and the thermal models are developed based on the analyzed results and validated with the test data. In comparative studies, the simulation models have been found to reproduce fuel consumption that is very close to the fuel consumption obtained from the tests

Half-metallic ferromagnetism and metal–insulator transition in Sn-doped SrRuO3 perovskite oxides

We investigate the electronic and magnetic properties of SrRu1-xSnxO3 by carrying out density-functional-theory calculations to show that a half-metallic ferromagnetic ground state emerges for the Sn doping of x≳0.5. To examine the effect of on-site Coulomb interactions for the Ru d orbitals, which was suggested to enhance the half-metallicity in SrRuO3, we employed both the local spin-density approximation (LSDA) as well as the LSDA + U method. For all the possible configurations of Sn doping for x=1/8,1/4,1/2,5/8,3/4, and 7/8 within the 2×2×2 unit cell, we monitor the Ru t2g bandwidth as well as the valence band maximum in the majority-spin channel and demonstrate that the Ru d electron hopping is blocked by the Sn-substituted sites so that the Ru t2g bandwidth becomes reduced as the doping x increases. For x0.7, the Ru t2g bandwidth gets so narrow that even a small on-site Coulomb interaction, e.g., Ueff=1.0 eV induces a band-gap, which indeed corresponds to a gap of the Ru impurity bands in the SrSnO3 oxide semiconductor. © 2018 Elsevier B.

Methodology for Finding Maximum Performance and Improvement Possibility of Rule-Based Control for Parallel Type-2 Hybrid Electric Vehicles

Hybrid electric vehicles (HEVs) require supervisory controllers to distribute the propulsion power from sources like an engine and motors. Control concepts based on optimal control theories such as dynamic programming (DP) and Pontryagin’s minimum principle (PMP) have been studied to maximize fuel efficiencies. These concepts are, however, not practical for real-world applications because they guarantee optimality only if future driving information is given prior to the actual driving. Instead, heuristic rule-based control concepts are widely used in real-world applications. Those concepts are not only simple enough to be designed based on existing vehicle control concepts, but also allow developers to easily intervene in the control to enhance other vital aspects of real-world vehicle performances, such as safety and drivability. In this study, a rule-based control for parallel type-2 HEVs is developed based on representative control concepts of real-world HEVs, and optimal control parameters are determined by optimization processes. The performance of the optimized rule-based control is evaluated by comparing it with the optimal results obtained by PMP, and it shows that the rule-based concepts can achieve high fuel efficiencies, which are close, typically within 4%, to the maximum values obtained by PMP