Carpenter, M. A. | Search NASA

DOE OSTI2022

Magnetoelastic properties of multiferroic hexagonal ErMnO 3

Here, the strength and dynamics of magnetoelastic coupling through the paramagnetic (PM) – antiferromagnetic (AFM) – ferrimagnetic (FIM) transitions in multiferroic hexagonal ErMnO 3 have been investigated by Resonant Ultrasound Spectroscopy. Elastic stiffening by up to 2% below the PM – AFM transition at 80 K arises from biquadratic coupling between strain and the magnetic order parameter with relaxation times longer than ~10 -6 s for the response of spins to changes in strain. In contrast with YMnO 3 , the PM – AFM transition in ErMnO 3 is accompanied by a peak in acoustic loss immediately below the Néel point which is interpreted in terms of strain relaxation accompanying ordering of spins of Er 3+ at 4b sites. Changes in the magnetic ordering scheme at the AFM – FIM transition near 3 K are accompanied by elastic softening of ~0.03 %. During poling of the low temperature ferrimagnetic structure round magnetic hysteresis loops, small changes in elastic stiffness which arise due to the contribution of piezomagnetic and/or piezoelectric moduli are detected. Contributions of piezoelectric moduli to acoustic resonance frequencies also permit changes in the configuration of ferroelectric domains to be detected in response both to cycling through this transition and to application of a magnetic field. A peak in acoustic loss in the vicinity of 250 K is attributed to strain-mediated pinning/freezing of some aspect of the domain microstructure with an activation energy of ~0.25–0.3 eV. A return to the original elastic properties on heating to temperatures above ~250 K is interpreted in terms of backswitching of domains to the configuration they had at the start. These observations confirm the existence of subtle variations in magnetoelastic coupling behaviour relating to both the magnetic order parameters and magnetic domain structures.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Bio-inspired gas sensing: boosting performance with sensor optimization guided by “machine learning”

The performance of existing gas sensors often degrades in field conditions because of the loss of measurement accuracy in the presence of interferences. Thus, new sensing approaches are required with improved sensor selectivity. We are developing a new generation of gas sensors, known as multivariable sensors, that have several independent responses for multi-gas detection with a single sensor. In this study, we analyze the capabilities of natural and fabricated photonic three-dimensional (3-D) nanostructures as sensors for the detection of different gaseous species, such as vapors and non-condensable gases. We employed bare Morpho butterfly wing scales to control their gas selectivity with different illumination angles. Next, we chemically functionalized Morpho butterfly wing scales with a fluorinated silane to boost the response of these nanostructures to the vapors of interest and to suppress the response to ambient humidity. Further, we followed our previously developed design rules for sensing nanostructures and fabricated bioinspired inorganic 3-D nanostructures to achieve functionality beyond natural Morpho scales. These fabricated nanostructures have embedded catalytically active gold nanoparticles to operate at high temperatures of ≈300 °C for the detection of gases for solid oxide fuel cell (SOFC) applications. Our performance advances in the detection of multiple gaseous species with specific nanostructure designs were achieved by coupling the spectral responses of these nanostructures with machine learning (a.k.a. multivariate analysis, chemometrics) tools. Our newly acquired knowledge from studies of these natural and fabricated inorganic nanostructures coupled with machine learning data analytics allowed us to advance our design rules for sensing nanostructures toward the required gas selectivity for numerous gas monitoring scenarios at room and high temperatures for industrial, environmental, and other applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗