Scanning probe imaging of coexistent ferromagnetism and ferroelectricity at room temperature

Room temperature coexistence of ferromagnetism and ferroelectricity in a thin film of a novel material of nominal composition PbTi0.5Fe0.5O3-d is probed by standard ferroelectric and ferromagnetic hysteresis loop measurements and by scanning probe microscopy of various kinds. Both magnetic domains and ferroelectric domains are observed in the same spatial region of the material, implying phase coexistence in this system. For both order parameters, sample morphology strongly affects roughness of the domain walls.Comment: 15 pages, 5 figure

Machine Learning Approach for Carbon Capture and Utilization – a Prelimenary Investigation

Due to the increase in the industrialization the environment is deteriorating. The major concern is to identify the sources those are contributing to the environment change. One of the major sources of interest is carbon in this domain. The carbon capture has been carried out with different methods and data is analyzed. The process of performing real time experiments is time consuming and sometimes the accurate results may not be obtained. In order to overcome the issues mentioned, a combined approach with machine learning is presented by the authors in this article. The present work provides a detailed overview of the laboratory processes for Carbon Capture and Utilization (CCU). In addition to this a detailed investigation of machine learning along with its probable implementation is presented. The combined approach will be beneficial as it efficient, quick and safe. The proposed approach will be beneficial to the industries as well as environment

Magneto-Seebeck effect in spin-valve with in-plane thermal gradient

We present measurements of magneto-Seebeck effect on a spin valve with in-plane thermal gradient. We measured open circuit voltage and short circuit current by applying a temperature gradient across a spin valve stack, where one of the ferromagnetic layers is pinned. We found a clear hysteresis in these two quantities as a function of magnetic field. From these measurements, the magneto-Seebeck effect was found to be 0.82%.Comment: 10 Pages, 7 figure

Magnetoelectricity at room temperature in Bi0.9-xTbxLa0.1FeO3 system

Magnetoelectric compounds with the general formula, Bi0.9-xRxLa0.1FeO3 (R =Gd, Tb, Dy, etc.), have been synthesized. These show the coexistence of ferroelectricity and magnetism, possess high dielectric constant and exhibit magnetoelectric coupling at room temperature. Such materials may be of great significance in basic as well as applied research.Comment: 11 pages of text and figure

Dielectric properties characterization of La- and Dy-doped BiFeO3 thin films

The dielectric response of La- and Dy- doped BiFeO3 thin films at microwave frequencies (up to 12 GHz) has been monitored as a function of frequency, direct current (dc) electric field, and magnetic field in a temperature range from 25 to 300 °C. Both the real and imaginary parts of the response have been found to be non-monotonic (oscillating) functions of measuring frequency. These oscillations are not particularly sensitive to a dc electric field; however, they are substantially dampened by a magnetic field. The same effect has been observed when the volume of the characterized sample is increased. This phenomenon is attributed to the presence of a limited number of structural features with a resonance type response. The exact origin of these features is unknown at present. Leakage current investigations were performed on the whole set of films. The films were highly resistive with low leakage current, thereby giving us confidence in the microwave measurements. These typically revealed ‘N'-type I-V characteristic

Evaluating end-to-end optimization for data analytics applications in weld

Modern analytics applications use a diverse mix of libraries and functions. Unfortunately, there is no optimization across these libraries, resulting in performance penalties as high as an order of magnitude in many applications. To address this problem, we proposed Weld, a common runtime for existing data analytics libraries that performs key physical optimizations such as pipelining under existing, imperative library APIs. In this work, we further develop the Weld vision by designing an automatic adaptive optimizer for Weld applications, and evaluating its impact on realistic data science workloads. Our optimizer eliminates multiple forms of overhead that arise when composing imperative libraries like Pandas and NumPy, and uses lightweight measurements to make data-dependent decisions at run-time in ad-hoc workloads where no statistics are available, with sub-second overhead. We also evaluate which optimizations have the largest impact in practice and whether Weld can be integrated into libraries incrementally. Our results are promising: using our optimizer, Weld accelerates data science workloads by up to 23X on one thread and 80X on eight threads, and its adaptive optimizations provide up to a 3.75X speedup over rule-based optimization. Moreover, Weld provides benefits if even just 4--5 operators in a library are ported to use it. Our results show that common runtime designs like Weld may be a viable approach to accelerate analytics