Quantification of the Interaction Field in Arrays of Magnetic Nanowires from the Remanence Curves

Stadler

2020

Nano Ex.

First-order reversal curve (FORC) measurements are broadly used for the characterization of complex magnetic nanostructures, but they can be inconclusive when quantifying the amount of different magnetic phases present in a sample. In this paper, we first establish a framework for extracting quantitative parameters from FORC measurements conducted on samples composed of a single type of magnetic nanostructure to interpret their magnetic properties. We then generalize our framework for the quantitative characterization of samples that are composed of 2-4 types of FeCo magnetic nanowires to determine the most reliable and reproducible parameters for a detailed analysis of samples. Finally, we conclude that the parameter with the best quantification potential, backfield remanence coercivity, does not require the full FORC measurement. Our approach provides an insightful path for fast, quantitative analysis of complex magnetic nanostructures, especially determination of the ratios of magnetic subcomponents present in multi-phase samples.

Section: Resultsmentioning

confidence: 99%

Beyond the qualitative description of complex magnetic nanoparticle arrays using FORC measurement

Stadler

2020

Nano Ex.

“…Therefore, the BRM shift in the combinations determines the amounts of each MNW present. Two features characterize BRM as a signature [47][48][49][50] : (I) the field where it is zero, which is average coercivity of the MNWs, and (II) its overall slope which is correlated to the interaction fields. The fourth parameter in Table 1 has the results of volume ratio calculations.…”

Section: Resultsmentioning

confidence: 99%

Facile decoding of quantitative signatures from magnetic nanowire arrays

Ghoreyshi

Visscher

et al. 2020

Sci Rep

Magnetic nanoparticles have been proposed as contact-free minimal-background nanobarcodes, and yet it has been difficult to rapidly and reliably decode them in an assembly. Here, high aspect ratio nanoparticles, or magnetic nanowires (MNWs), are characterized using first-order reversal curves (FORC) to investigate quantitative decoding. We have synthesized four types of nanowires (differing in diameter) that might be used for barcoding, and identified four possible “signature” functions that might be used to quickly distinguish them. To test this, we have measured the signatures of several combination samples containing two or four different MNW types, and fit them to linear combinations of the individual type signatures to determine the volume ratios of the types. We find that the signature which determines the ratios most accurately involves only the slope of each FORC at its reversal field, which requires only 2–4 data points per FORC curve, reducing the measurement time by a factor of 10 to 50 compared to measuring the full FORC.

“…In contrast, the curvature of the BRM spectra determines the intrinsic response of the magnetic nanobarcodes related to its coercivity ( H c ), standard deviation of H c , interaction field ( H u ), and their correlations. [ 44–46 ] In fact, the balance between the H u and the MNWs H c is an important factor also that directly affects the BRM spectra of the magnetic nanobarcodes. In other words, since the BRM spectra are measured at H = 0 , the total field applied on each MNW inside the nanobarcode is simply the H u from the neighboring MNWs.…”

Section: Resultsmentioning

confidence: 99%

Magnetic Nanowires toward Authentication

Part & Part Syst Charact

Stadler

2020

Magnetic nanowires (MNWs) have been shown to be promising candidates for nanobarcoding and biolabeling over decades. However, surprisingly, they have never been realized successfully for these applications due to the lack of a reliable encoding strategy that allows reliable decoding of readout signatures. Here, a novel encoding/decoding approach is reported by tailoring the MNWs remanence spectrum that makes decoding the magnetic nanobarcodes feasible even though there is no prior knowledge regarding the readout remanence spectrum. The remanence spectra of several MNWs is tuned by varying their composition, dimensions, and arrangements to generate several distinct nanobarcodes. Furthermore, a simple automated decoding algorithm is illustrated to identify and verify the type and number of MNWs in unknown remanence spectra. The experimental and analytical approaches show that the remanence spectrum is a strong probe for reliable encoding/decoding because it employs three authentication factors that significantly enhance their security performance in nanobarcoding and biolabeling.