Systematic measurements pertinent to the magnetocaloric effect and nature of magnetic transition around the transition temperature are performed in the 10 nm Pr0.5Ca0.5MnO3 nanoparticles (PCMO10) . Maxwell relation is employed to estimate the change
in magnetic entropy. At Curie temperature TC, 83.5 K, the change in magnetic entropy discloses a typical variation with a value 0.57 J/kg K, and is found to be magnetic field dependent. From the area under the curve Delta S vs T, the refrigeration capacity is calculated at TC, 83.5 K and it is found to be 7.01 J/kg. Arrott plots infer that due to the competition between the ferromagnetic and anti ferromagnetic interactions, the magnetic phase transition in PCMO10 is broadly spread over both in temperature as well as in magnetic field coordinates. Upon tuning the particle size, size distribution, morphology, and relative fraction of magnetic phases, it may be possible to enhance the magnetocalorific effect further in PCMO10.
The dynamics of magnetic hysteresis, including the training effect and the field sweep rate dependence of the exchange bias, is experimentally investigated in exchange-coupled potassium split graphene nanoribbons (GNRs). We find that, at low field sw
eep rate, the pronounced absolute training effect is present over a large number of cycles. This is reflected in a gradual decrease of the exchange bias with the sequential field cycling. However, at high field sweep rate above 0.5 T/min, the training effect is not prominent. With the increase in field sweep rate, the average value of exchange bias field grows and is found to follow power law behavior. The response of the exchange bias field to the field sweep rate variation is linked to the difference in the time it takes to perform a hysteresis loop measurement compared with the relaxation time of the anti-ferromagnetically aligned spins. The present results may broaden our current understanding of magnetism of GNRs and would be helpful in establishing the GNRs based spintronic devices.
Two types of graphene nanoribbons: (a) potassium-split graphene nanoribbons (GNRs), and (b) oxidative unzipped and chemically converted graphene nanoribbons (CCGNRs) were investigated for their magnetic properties using the combination of static magn
etization and electron spin resonance measurements. The two types of ribbons possess remarkably different magnetic properties. While the low temperature ferromagnet-like feature is observed in both types of ribbons, such room temperature feature persists only in potassium-split ribbons. The GNRs show negative exchange bias, but the CCGNRs exhibit a positive exchange bias. Electron spin resonance measurements infer that the carbon related defects may responsible for the observed magnetic behaviour in both types of ribbons. Furthermore, proton hyperfine coupling strength has been obtained from hyperfine sublevel correlation experiments performed on the GNRs. Electron spin resonance provides no indications for the presence of potassium (cluster) related signals, emphasizing the intrinsic magnetic nature of the ribbons. Our combined experimental results may infer the coexistence of ferromagnetic clusters with anti-ferromagnetic regions leading to disordered magnetic phase. We discuss the origin of the observed contrast in the magnetic behaviours of these two types of ribbons.
We report on isothermal pulsed (20 ms) field magnetization, temperature dependent AC - susceptibility, and the static low magnetic field measurements carried out on 10 nm sized Pr0.5Ca0.5MnO3 nanoparticles (PCMO10). The saturation field for the magne
tization of PCMO10 (~ 250 kOe) is found to be reduced in comparison with that of bulk PCMO (~300 kOe). With increasing temperature, the critical magnetic field required to melt the residual charge-ordered phase decays exponentially while the field transition range broadens, which is indicative of a Martensite-like transition. The AC - susceptibility data indicate the presence of a frequency-dependent freezing temperature, satisfying the conventional Vogel-Fulcher and power laws, pointing to the existence of a spin-glass-like disordered magnetic phase. The present results lead to a better understanding of manganite physics and might prove helpful for practical applications.
We report on exchange bias effects in 10 nm particles of Pr0.5Ca0.5MnO3 which appear as a result of competing interactions between the ferromagnetic (FM)/anti-ferromagnetic (AFM) phases. The fascinating new observation is the demonstration of the tem
perature dependence of oscillatory exchange bias (OEB) and is tunable as a function of cooling field strength below the SG phase, may be attributable to the presence of charge/spin density wave (CDW/SDW) in the AFM core of PCMO10. The pronounced training effect is noticed at 5 K from the variation of the EB field as a function of number of field cycles (n) upon the field cooling (FC) process. For n > 1, power-law behavior describes the experimental data well; however, the breakdown of spin configuration model is noticed at n geq 1.
Electron spin resonance (ESR) investigation of graphene nanoribbons (GNRs) prepared through longitudinal unzipping of multiwalled carbon nanotubes (MWCNTs) indicates the presence of C-related dangling bond centers, exhibiting paramagnetic features. E
SR signal broadening from pristine or oxidized graphene nanoribbons (OGNRs) is explained in terms of unresolved hyperfine structure, and in the case of reduced GNRs (RGNRs), the broadening of ESR signal can be due to enhancement in conductivity upon reduction. The spin dynamics observed from ESR linewidth-temperature data reflect a variable range hopping (VRH) mechanism through localized states, consistent with resistance-temperature data.
Wireless sensor networks (WSNs) can be a valuable decision-support tool for farmers. This motivated our deployment of a WSN system to support rain-fed agriculture in India. We defined promising use cases and resolved technical challenges throughout a
two-year deployment of our COMMON-Sense Net system, which provided farmers with environment data. However, the direct use of this technology in the field did not foster the expected participation of the population. This made it difficult to develop the intended decision-support system. Based on this experience, we take the following position in this paper: currently, the deployment of WSN technology in developing regions is more likely to be effective if it targets scientists and technical personnel as users, rather than the farmers themselves. We base this claim on the lessons learned from the COMMON-Sense system deployment and the results of an extensive user experiment with agriculture scientists, which we describe in this paper.
