Magnetic Recording Systems Research Articles

Tuning the structural, morphological, optical, dielectric, and magnetic properties of PVA via embedding with CoFe2O4:CuO nanoparticles

Polyvinyl alcohol (PVA) embedded CoFe2O4: CuO (CC) nanocomposites (NC) were prepared by casting technique. The prepared CoFe2O4 (CFO) sample have crystallite size in the range of 20.10-29.08 nm, whereas the crystallite sizes of CuO were found in the range of 20.29-23.68 nm, respectively. TEM images revealed the spherical shape morphology of CC nanocomposite with an average particle size distribution of 15 nm. The Urbach energy of the PCC films increased from 0.44 to 2.590 eV, whereas the direct optical band gaps decreased from 5.584 to 4.345 eV, respectively. The refractive indices of the PCC films were found to be in the range of 1.9 -2.6, depending on the different models. Room Temperature-dependent saturation magnetization and coercive field for the prepared nanocomposites were found to be 0.52-1.296 (emu/g) and 1210-1340 (Oe), respectively. The uniaxial magnetic anisotropic constant of PCC films was remarkably enhanced from 0.654x103 to 3.826x103 (erg/cm3) for PCC2, PCC3, and PCC4, correspondingly. The enhanced values of dielectric and magnetic parameters of the prepared nanocomposites suggest their suitability for magnetic recording and memory systems.

A study on acceleration of SP decoder using reliability of recording sequence by neural network based on parity check result in SMR system

We study signal processing methods to realize ultra-high-density hard disk drives (HDDs). Among them, we have applied the neural network to improve decoding performance in low-density parity-check (LDPC) coding and iterative decoding in the shingled magnetic recording (SMR) system. In this study, we realize acceleration of the sum-product (SP) decoding by updating the decoding reliability of the SP decoding using the reliability of the recording sequence calculated by the neural network based on the parity check results. As a result, the proposed system achieved error-free with the fewest number of iterations in the SP decoder compared to our previous studies.

Bit-island arrangement and signal processing in double-layer magnetic recording technology

The escalating demand for high-density storage of hard disk drives has prompted the innovation of advanced technologies to significantly boost an areal density (AD). Among these, three-dimensional magnetic recording systems incorporating double recording layers and bit-patterned magnetic recording (BPMR) have currently emerged as one promising solution. Therefore, this article investigates the integration of double-layer magnetic recording and BPMR technologies which is called double-layer BPMR, aiming for a substantial increase in AD. The primary focus lies on minimizing inter-layer interference and mitigating two-dimensional interferences by optimizing bit-island sizes for both upper and lower layers under the incorporation of staggered-like recording media arrangement and an array of magneto-resistive readers. Moreover, we also employ a rate-5/6 modulation code for compensating these effects. Detailed examinations reveal that our proposed system has a superior bit-error rate performance compared with conventional single-layer BPMR system.

Multilayer perceptron-based array reader optimization for ultra-high density magnetic recording

We have previously presented a utilization of a long-short-term memory (LSTM) network to improve the reliability of the log-likelihood ratios (LLRs) in a coded three-head/three-track bit-patterned magnetic recording (BPMR) system. To continuously enhance a bit error rate (BER) performance; therefore, this article introduces a novel LLR flipper utilizing a multilayer perceptron (MLP), which operates under the optimization of input numbers of array reader positions. We first optimize an input number of MLP-based soft-information flippers with varying the number of recording bits in various data patterns. Then, the right positions of an array reader under the operation of our proposed MPL flipper are also optimized to obtain better BER performance. The simulation results demonstrate that the proposed MLP flipper significantly improves BER performance compared to the previous LSTM flipper using the same input number. Moreover, our proposed system still provides superior performance when it is operated under an optimal input number and can be higher when working with the right array reader positions.

Recording media configurations for double-layered bit-patterned magnetic recording

The current magnetic recording technology is approaching its recording density limit. Recently, concepts focused on vertically stacking multiple recording media have gained momentum, driven by the potential to significantly expand recording density. The key challenge for such a system involves methods capable of efficiently separating data originating from the upper and lower layers within a single readback signal. To address this challenge, we first propose two distinct configurations of recording media in bit-patterned magnetic recording (BPMR) system with double recording layers. In both configurations, the centers of islands on the lower layer are positioned at the gaps between magnetic islands on the upper layer. This achieves the separation of the individual layer signals since the centers of islands in both layers are deliberately misaligned. Moreover, the equalizer design that takes the input data from both layers into consideration is also proposed. Simulation results demonstrate that when employing the same detector, the proposed configurations of the double-layered BPMR systems achieve better performance than the single-layered BPMR system.

Method of liquid consumption measuring in nuclear magnetic flowmeters-relaxometers

The need to expand the functionality of systems for monitoring the parameters of the flow of liquid media is substantiated. The advantages of using meters based on the phenomenon of nuclear magnetic resonance to control the parameters of the flow of liquid media are noted. Let us consider the problems that arise during the operation of nuclear magnetic flowmeters-relaxometers operating in two measurement modes (pulse and with periodic modulation of the magnetic field in the nuclear magnetic resonance signal recording system - modulation technique). It is noted that the main problem in the operation of these devices is associated with an increase in the error in measuring liquid flow or the termination of its measurement process with rapid changes in liquid flow. The use of a magnetic tag mode, which allows us to solve this problem, significantly limits the possibilities of using nuclear magnetic resonance flowmeters-relaxometers when used to monitor the parameters of other liquids or with a large increase in the temperature of the flowing medium. A method for creating a magnetic mark at the noise level for measuring liquid flow is proposed. In the method, changing the composition of the flowing medium (including the liquid itself) does not have a significant effect on the formation of a magnetic mark at the noise level in a strong inhomogeneous magnetic field. The results of experimental studies of the nutation line from changes in magnetic field inhomogeneity are presented. A mathematical model has been developed based on the modified Bloch equations and relationships between the magnetic field parameters have been established to implement the magnetic mark mode in the nuclear magnetic resonance signal with magnetization inversion at the noise level. The use of a method makes it possible to make the influence of rapid changes in the value of liquid flow (by a factor of 10 or more) on the flow measurement error insignificant.

A Study on Accelerating SP Decoding by Neural Network in SMR System

We have previously studied low-density parity-check (LDPC) coding and iterative decoding in the shingled magnetic recording (SMR) system as a signal processing method to realize ultra-high-density hard disk drives (HDD). In addition, we have proposed the application of the neural network to improve decoding performance and realize the automation of iterative decoding. In this study, we apply a neural network to accelerate iterative decoding in the sum-product (SP) decoder. As the result, the SP decoder with the neural network realized ”no errors” at the fewest times of the iterative decoding compared to our previous studies.

A Graded Precompensation Scheme by Pattern Classification on Nonlinear Transition Shift for Perpendicular Magnetic Recording

To achieve higher magnetic recording areal densities, signal distortions caused by the crosstalk among consecutive magnetized transitions that lead to nonlinear transition shifts (NLTS) must be eliminated. We calculated and sorted the transition shifts of different recorded patterns and classified corresponding patterns based on an analytical method. We proposed a graded write precompensation scheme according to the classified patterns and compared the detecting performance of a perpendicular magnetic recording system using the graded compensation and traditional pattern-aware compensation during the writing process. Simulation results show our proposed graded precompensation can effectively mitigate the nonlinear distortion effect caused by NLTS and outperforms the traditional pattern-aware compensation method. The detecting BER decreases by 14.7% when the SNR of electronic noise is only 20 dB and the bit length is 10nm.

Effect of water on mechano-chemical reactions of perfluoropolyether lubricant films in heat-assisted magnetic recording: A reactive molecular dynamics study

A comprehensive understanding of the decomposition of perfluoropolyether (PFPE) films is crucial for establishing effective lubrication of heat-assisted magnetic recording (HAMR) systems. In this study, to examine the combined influence of heat, mechanical stress, and water, we conducted nonequilibrium reactive molecular dynamics simulations using our ReaxFF force field for the PFPE D-4OH films mixed with water. We thoroughly analyzed the reaction rates, types, pathways, and products, and identified vulnerable bonds. The results demonstrate that water significantly accelerates the reactions of D-4OH, particularly at lower normal pressures. We found that water molecules form clusters and are surrounded by the D-4OH end groups. Consequently, water induces hydrolysis of D-4OH or catalyzes reactions between D-4OH by dissociating C–O bonds in the end groups.

Design Considerations Including Rotating Head Technique for Shingled Heat-Assisted Magnetic Recording

Predictions for Signal-to-Noise Ratio (SNR) and User Density (UD) are presented for a large variety of shingled Heat Assisted Magnetic Recording (HAMR) systems. Calculations are performed using a micromagnetic simulation that treats the heated media cells using renormalized spin blocks. Varied parameters include grain pitch, heat spot Full Width Half Maximum, reader width, and shield to shield spacing. Results are optimized with respect to bit length and grain pitch. Unlike previous work, the base condition feature systems already available experimentally (to allow for comparison), extending to media and heads that allow greatly extended capacities. We also discuss the benefits of a rotated read head for these geometries.

ASIC Implementation of Nonlinear CNN-Based Data Detector for TDMR System in 28 nm CMOS at 200 Mbits/s Throughput

In this work, we present the first application-specific integrated circuit (ASIC) implementation of a convolutional neural network (CNN)-based data detection channel for the two-dimensional magnetic recording (TDMR) system in hard disk drive (HDD). This chip is fabricated in TSMC 28 nm complementary metal–oxide–semiconductor (CMOS). TDMR signals captured from a real HDD are used to train and test the network, and the chip is designed to make inferences only. This work presents a systematic pipeline to codesign the neural network structure and the corresponding hardware implementation. To meet the high-throughput requirement, the CNN is fully unrolled with dedicated silicon for each convolution layer using systolic arrays. Quantization-aware training algorithms are used to help improve power efficiency without comprising accuracy. Overall, our chip achieves 200 Mbits/s throughput at 0.9 V supply voltage. In addition, it achieves improved detection accuracy compared to the physical-model-based conventional channel. Our chip consumes 173–219 mW power at 200 M3 clock rate for supply voltage 0.8–0.9 V, respectively.

Multidimensional Signal Processing for High Areal Density Heated-Dot Magnetic Recording

In this article, a new multidimensional signal processing scheme for a heated-dot magnetic recording (HDMR) system using double-layered bit-patterned media (BPM) is proposed. This proposed signal processing scheme is capable of simultaneously detecting data sequences recorded on two tracks in each layer sequentially. The effective transmission rate of the HDMR system with two-track simultaneous log-likelihood ratio (LLR) detection and double-layered recording can be increased about four times that of the HDMR system with single-track LLR detection and single-layered recording if the data sequence recorded on each track has the same rate. It is shown that the error rate performance of the HDMR system with two-track simultaneous LLR detection and double-layered recording shows a significant improvement over the HDMR system with single-track LLR detection and single-layered recording by computer simulation.

Breaking the Computational Bottleneck: Probabilistic Optimization of High-Memory Spatially-Coupled Codes

Spatially-coupled (SC) codes, known for their threshold saturation phenomenon and low-latency windowed decoding algorithms, are ideal for streaming applications and data storage systems. SC codes are constructed by partitioning an underlying block code, followed by rearranging and concatenating the partitioned components in a convolutional manner. The number of partitioned components determines the memory of SC codes. In this paper, we investigate the relation between the performance of SC codes and the density distribution of partitioning matrices. While adopting higher memories results in improved SC code performance, obtaining finite-length, high-performance SC codes with high memory is known to be computationally challenging. We break this computational bottleneck by developing a novel probabilistic framework that obtains (locally) optimal density distributions via gradient descent. Starting from random partitioning matrices abiding by the obtained distribution, we perform low-complexity optimization algorithms that minimize the number of detrimental objects to construct high-memory, high-performance quasi-cyclic SC codes. We apply our framework to various objects of interest, from the simplest short cycles, to more sophisticated objects such as concatenated cycles aiming at finer-grained optimization. Simulation results show that codes obtained through our proposed method notably outperform state-of-the-art SC codes with the same constraint length and optimized SC codes with uniform partitioning. The performance gain is shown to be universal over a variety of channels, from canonical channels such as additive white Gaussian noise and binary symmetric channels, to practical channels underlying flash memory and magnetic recording systems.

Optimization of two-dimensional generalized partial response target using multi-layer perceptron for bit-patterned media recording systems

In magnetic storage systems, the read signal that is the output of the magnetic recording channel is passed through the equalizer to convert it into the desired partial response (PR) target signal. However, mapping between the output of the recording channel and the PR target signal is a non-linear problem. Therefore, many multilayer perceptron (MLP) equalizers have been proposed. In this paper, we propose an optimization scheme of two-dimensional generalized PR target using MLP for improving the detection performance of the bit-patterned magnetic recording (BPMR) systems. The simulation results show that the proposed scheme outperforms the previous methods.

Track Misregistration Mitigation Using CNN-Based Method on Single-Reader/Two-Track Reading BPMR Systems

One of the problems that cause a decrease in the performance of the ultra-high bit-patterned magnetic recording (BPMR) system is track misregistration (TMR). Since the gap between data tracks is extremely narrow, it easily affects keeping the reader in the desired position. Therefore, this paper proposes the track misregistration mitigation included the estimation and correction techniques on single-reader/two-track reading (SRTR) BPMR using only a readback signal. The TMR estimation technique uses the convolutional neural network (CNN) to estimate the TMR level by the histograms of the readback signal enabling minimization of the complexity of the CNN structure and amount of training time. The estimated TMR levels obtained from the proposed CNN-histogram-based method will then be utilized to detect the estimated recorded bit by the CNN-based data detector. The simulation shows that our proposed system provides better TMR prediction accuracy even though the system has to face higher media noise. Furthermore, the CNN-based data detectors perform superior to the partial response maximum likelihood (PRML) based data detector, especially in strong electronic noise situations and the severe imperfection of recording media.

Effects of Oxygen on Smear Formation in Heat Assisted Magnetic Recording System

Heat-assisted magnetic recording (HAMR) is expected to be a realistic next-generation technology for increasing the recording density of hard disks. However, the magnetic layer is heated above the Curie temperature, and, as a result, the heated lubricant is desorbed from the disk by decomposition and evaporation, which causes a problem as it adheres to the air-bearing surface (ABS) as a smear. In this study, pyrolysis gas chromatography/mass spectrometry (Py-GC/MS) analysis was performed in helium and air environments to investigate the decomposition mechanism of perfluoropolyether (PFPE) lubricant D-4OH by heating and in the presence of oxygen. In the helium environment, thermal decomposition of the end groups was confirmed at 350°C and above with a possibility of main chain decomposition at 450°C. In the air environment, decomposition of the end group was confirmed at 250°C and above, and decomposition of the main chain was confirmed at 450°C. Experiments using a pin-on-disk tester were conducted to confirm what happens to the area of smear when a thin film of D-4OH lubricant coated on an actual disk is laser heated. As a result, it was confirmed that the area of smear decreased even at an oxygen concentration of 5%.

A Study of Three-Dimensional Equalization for Reproducing a Double-Layer Magnetic Recording Medium

To increase the recording density of hard disk drives (HDD), three-dimensional (3-D) magnetic recording with multiple recording layers is attracting much attention as a next-generation recording method. We have reported that the two-dimensional (2-D) partial response maximum likelihood (PRML) can achieve a good BER performance using the PR channel obtained from the differential-phase bit response in the 3-D magnetic recording system with a double recording layer. In this study, we realize the 3-D equalization by the 2-D finite impulse response (FIR) (2-D FIR) filter and 2-D PRML system over two layers and evaluate the 3-D equalization to further increase the recording density. The transfer function of the 2-D PR channels is determined by the response for the in-phase or differential-phase bits in a double-layer magnetic recording medium. The results show that the 2-D PRML channels with 3-D equalization based on the differential-phase transfer function achieve a good bit error rate (BER) performance for system noise.

Models of advanced recording systems: A multi-timescale micromagnetic code for granular thin film magnetic recording systems

Micromagnetic modelling provides the ability to simulate large magnetic systems reliably without the computational cost limitation imposed by atomistic modelling. Through micromagnetic modelling it is possible to simulate systems consisting of thousands of grains over a time range of nanoseconds to years, depending upon the solver used. Here we present the creation and release of an open-source multi-timescale micromagnetic code combining three key solvers: Landau-Lifshitz-Gilbert; Landau-Lifshitz-Bloch; Kinetic Monte Carlo. This code, called MARS (Models of Advanced Recording Systems), is capable of accurately simulating the magnetisation dynamics in large and structurally complex single- and multi-layered granular systems as is shown by comparison to established atomistic simulation results. The short timescale simulations are achieved for systems far from and close to the Curie point via the implemented Landau-Lifshitz-Gilbert and Landau-Lifshitz-Bloch solvers respectively. This enables read/write simulations for general perpendicular magnetic recording and also state of the art heat assisted magnetic recording (HAMR). The long timescale behaviour is simulated via the Kinetic Monte Carlo solver, enabling investigations into signal-to-noise ratio and data longevity. The combination of these solvers opens up the possibility of multi-timescale simulations within a single software package. For example the entire HAMR process from initial data writing and data read back to long term data storage is possible via a single simulation using MARS. The use of atomistic parameterisation for the material input of MARS enables highly accurate material descriptions which provide a bridge between atomistic simulation and real world experimentation. Thus MARS is capable of performing simulations for all aspects of recording media research and development. This ranges from material characterisation and optimisation to system design and implementation. The object orientated nature of MARS is structured to facilitate quick and simple development and easy implementation of user defined custom simulation types which can utilise either timescale or a combination of both timescales. Program summaryProgram title: MARSCPC Library link to program files:https://doi.org/10.17632/8mx7cndcdx.1Developer's repository link:https://bitbucket.org/EwanRannala/mars/Code Ocean capsule:https://codeocean.com/capsule/2549929Licensing provisions: MITProgramming language: C++Supplementary material: MARS testing methodology (PDF), HAMR simulation example video.Nature of problem: A combined model that enables the complete modelling of magnetic recording processes at elevated temperatures covering all time scales from writing (nanoseconds) up to long term data storage (years). The model must also accurately describe the granular nature of the recording media as grain sizes are reduced to a few nanometres.Solution method: Short timescale behaviours are captured via the Landau-Lifshitz-Gilbert and Landau-Lifshitz-Bloch solvers for low and high temperature systems respectively. The long time scale behaviours are captured via a kinetic Monte Carlo solver. To enable complex models which account for mixed timescale behaviours the solvers are implemented as a single class structure which allows for dynamic solver selection. The granular structure is generated via a Laguerre-Voronoi tessellation with a custom implemented packing algorithm to produce highly realistic grain size distributions. Complex thermal dependencies of materials can be incorporated via atomistic parameterisation forming a multi-timescale model of the material.

Track width measurement in heat-assisted magnetic recording systems using the cross-track DC noise method

This paper uses a cross-track DC noise measurement technique to determine the written track width in heat-assisted magnetic recording (HAMR). The method is approached as a simple, no-extra-hardware-required technique on a spin-stand to determine the written track width as well as the DC noise amplitude at the center track in a HAMR system. The track width data show the expected trends with changing laser operating current () and write current (), and they are strongly correlated with track density capabilities and physical near-field transducer (NFT) peg width. The written track width is essentially defined by the which increases as increases. The method is useful for comparing the magnetic responses of different writer pole or NFT peg geometries, as well as media design comparison to provide insight into the head/component necessary to improve HAMR system performance, which is useful HAMR recording parameters for head/media designers and test engineers.

A Study on Performance Evaluation With Neural Network Detector in SMR System

We previously applied a neural network detector (NND) to the low-density parity-check (LDPC) coding and iterative decoding system in a shingled magnetic recording (SMR) system. In this study, we evaluate the performance of iterative decoding using a new NND by computer simulation. The conventional NND gets the log-likelihood ratio (LLR) as the reliability of the sequence recorded from the two-dimensional finite impulse response (TD-FIR) filter output and the sum-product (SP) decoder output, but the new NND finds the LLR by adding the SP decoder input in order to consider the difference between the SP decoder input and the decoding result. Furthermore, we clarify that the new NND brings the almost same effect as the a posteriori probability (APP) decoder in the iterative decoding system.