Data Storage Research Articles

Machine Learning-Enhanced Fabrication of Three-Dimensional Co-Pt Microstructures via Localized Electrochemical Deposition

This paper presents a novel method for fabricating three-dimensional (3D) microstructures of cobalt–platinum (Co-Pt) permanent magnets using a localized electrochemical deposition (LECD) technique. The method involves the use of an electrolyte and a micro-nozzle to control the deposition process. However, traditional methods face significant challenges in controlling the thickness and uniformity of deposition layers, particularly in the manufacturing of magnetic materials. To address these challenges, this paper proposes a method that integrates machine learning algorithms to optimize the electrochemical deposition parameters, achieving a Co:Pt atomic ratio of 50:50. This optimized ratio is crucial for enhancing the material’s magnetic properties. The Co-Pt microstructures fabricated exhibit high coercivity and remanence magnetization comparable to those of bulk Co-Pt magnets. Our machine learning framework provides a robust approach for optimizing complex material synthesis processes, enhancing control over deposition conditions, and achieving superior material properties. This method opens up new possibilities for the fabrication of 3D microstructures with complex shapes and structures, which could be useful in a variety of applications, including micro-electromechanical systems (MEMSs), micro-robots, and data storage devices.

Possible structures of skyrmion states in chiral ferromagnetic films with spatially modulated uniaxial anisotropy.

In this paper, the stabilization conditions, structure, and properties of possible vortex-like inhomogeneities, including kπ-skyrmions k = 0, 1, 2, 3, 4, in a uniaxial multilayer disk with a columnar defect in the center are investigated based on micromagnetic modeling. Their stability diagrams depending on the Dzyaloshinskii-Moriya interaction, the magnitude of magnetic anisotropy and the defect parameters are determined. New types of vortex-like inhomogeneities that can arise in such samples are found. The obtained data can be used to create artificial regions of nucleation, capture and pinning of magnetic skyrmions, which can provide greater reliability of data storage in spintronic logical devices.&#xD.

Π-shaped pixel pattern for shift multiplexing surface holograms in holographic data storage

In this study, a method for shift multiplexing surface holograms was proposed for data storage systems. Shift multiplexing of surface holograms is inhibited by noise specific to Raman–Nath diffraction. We proposed a model to analyze the influence of noise. Subsequently, we proposed a method for noise suppression to arrange signal and reference pixels in a shape similar to the Greek letter “Π.” The proposed method is generally applicable to thin holograms in which Raman–Nath diffraction occurs. The effectiveness of noise suppression using the proposed method was experimentally demonstrated. We theoretically estimated that a shift multiplexing surface holographic data storage system using the proposed method could achieve a significantly higher data transfer rate than conventional optical discs while maintaining a comparable storage density.

Strain Fluctuations Unlock Ferroelectricity in Wurtzites

AbstractFerroelectrics are of practical interest for non‐volatile data storage due to their reorientable, crystallographically defined polarization. Yet efforts to integrate conventional ferroelectrics into ultrathin memories have been frustrated by film‐thickness limitations, which impede polarization reversal under low applied voltage. Wurtzite materials, including magnesium‐substituted zinc oxide (Zn,Mg)O, have been shown to exhibit scalable ferroelectricity as thin films. In this work, the origins of ferroelectricity in (Zn,Mg)O are explained, showing that large strain fluctuations emerge locally in (Zn,Mg)O and can reduce local barriers to ferroelectric switching by more than 40%. Concurrent experimental and computational evidence of these effects are provided by demonstrating polarization switching in ZnO/(Zn,Mg)O/ZnO heterostructures featuring built‐in interfacial strain gradients. These results open up an avenue to develop scalable ferroelectrics by controlling strain fluctuations atomistically.

Beyond Photochromism: Alternative Stimuli to Trigger Diarylethenes Switching.

Diarylethenes (DAEs) are typical photochemically reversible type (P-type) photochromic materials with excellent thermal stability and high fatigue resistance and are widely exploited as photo-switches for various applications in molecular devices, data storage, photoresponsive materials, and bioimaging, etc. In recent years, there is an increasing number of reports using heat, acid, electrochemistry, etc. to drive the isomerization reaction of DAEs. The response to two or more different stimuli enables multi-functionality within a single DAE molecule, which would facilitate complex logic-gate operations, multimode data storage, and increased information density. Herein, the recent advances in DAE systems utilizing stimuli "beyond photo" to trigger the isomerization processes from three perspectives: acidochromism, thermochromism, and electrochromism are reviewed. Emphasis is placed on the molecule design strategies and the underlying mechanisms for cyclization and cycloreversion processes addressed by the alternative stimulus. Then the noticeable applications made in multi-stimuli responsive DAE systems are summarized. Additionally, the challenges and opportunities of DAE switches driven by stimuli "beyond photo" in the future are also discussed.

O IMPACTO DA INTELIGÊNCIA ARTIFICIAL NA SOCIEDADE DIANTE DA LEI GERAL DE PROTEÇÃO DE DADOS: A LIMITAÇÃO JURÍDICA DA INTELIGÊNCIA ARTIFICIAL DIANTE DA LEI Nº 13.709/18

This is a scientific article whose theme is the impact of artificial intelligence on society in light of the General Data Protection Law. The LGPD defines the liability of data processing agents, who are controllers and operators, for damages caused by the exercise of the processing activity, in a manner similar to the system of the Consumer Defense Code (CDC). By providing citizens with rights over their data, the LGPD also tends to increase public transparency regarding data collection and analysis. Thus, it will not be restricted to private companies; in the public sphere, the State will also have to be clearer about how it handles citizen data. The aforementioned law establishes rules for the storage, sharing, use, and collection of citizen data, whether by public or private companies. The article aims to demonstrate how the uncontrolled use of artificial intelligence affects society as a whole, such as the new personal data protection legislation, protecting users and democracy, as well as highlighting the main difficulties faced by companies in the process of adapting and complying with the LGDP standards and the legal limitations of Artificial Intelligence. As a theoretical basis, articles, conventions and laws that corroborate the Brazilian legal system were adopted. The methodology used was a descriptive and exploratory literature review.

Enhancing the Thermal Stability of Skyrmion in Magnetic Nanowires for Nanoscale Data Storage.

Magnetic skyrmion random switching and structural stability are critical limitations for storage data applications. Enhancing skyrmions' magnetic properties could improve their thermal structural stability. Hence, micromagnetic calculation was carried out to explore the thermal nucleation and stability of skyrmions in magnetic nanodevices. Different magnetic properties such as uniaxial magnetic anisotropy energy (Ku), saturation magnetization (Ms) and Dzyaloshinskii-Moriya interaction (DMI) were used to assess the thermal stability of skyrmions in magnetic nanowires. For some values of Ms and Ku, the results verified that the skyrmion structure is stable at temperatures above 800 K, which is higher than room temperature. Additionally, manipulating the nanowire geometry was found to have a substantial effect on the thermal structural stability of the skyrmion in storage nanodevices. Increasing the nanowire dimensions, such as length or width, enhanced skyrmions' structural stability against temperature fluctuations in nanodevices. Furthermore, the random nucleation of the skyrmions due to the device temperature was examined. It was shown that random skyrmion nucleation occurs at temperature values greater than 700 K. These findings make skyrmion devices suitable for storage applications.

A 2DEG‐Based GaN‐on‐Si Terahertz Modulator with Multi‐Mode Switchable Control

AbstractAs terahertz (THz) technology has been widely considered as a key candidate for future sixth‐generation wireless communication networks, THz modulators show profound significance in wireless communication, data storage, and imaging. In special, dynamic tuning of THz waves through 2D electron gas (2DEG) incorporated with a hybrid design of metasurface has attracted keen interest due to the combined merits of deliberate structural design, rapid switching speed and the process compatibility. Current meta‐modulator enables very high modulation depth but encounter limited bandwidth. In this paper, by taking into account the co‐functional effects of temperature and voltage‐dependent dynamic control on transmission amplitude, a 2DEG‐based GaN‐on‐Si modulator with two switchable operational states (or four modes) of active wave control is proposed. Under cryogenic temperature conditions, the proposed device exhibits prominent 2D plasmons characteristics with switchable transitions between the gated mode and ungated mode for active control. Under room temperature conditions, the proposed device exhibits non‐resonance broadband spectra characteristics with tunable transitions between the linearity mode and depletion mode for transmission control. The scheme provides an option for the development of the actively tunable THz meta‐modulator and paves a way for the robust multifunctionality of electrically controllable THz switching, and biosensors.

Harnessing farmer engagement to develop a 10-point plan to control Johne's disease in dairy herds

Since the launch of the voluntary National Johne's Management Plan (NJMP) in 2015, the within-herd prevalence of Johne's disease (JD) in the UK has decreased from 8.49% to 2.68%, this reduction occurred by 2022. As part of the NJMP, veterinarians and farmers are required to conduct a risk assessment, examine the herd JD status and formulate a management plan within which farmers commit to one of six management strategies. In response to the success of the NJMP, completion of the NJMP or equivalent scheme has been mandatory under the Red Tractor assurance scheme since 2019. However, levels of engagement with the NJMP among both veterinarians and farmers, and progress with respect to JD prevalence, vary considerably. This paper uses a mixture of literature and expert opinions to discuss these issues and generate the JD Control 10-Point Plan. Failing to control JD is generally not associated with technical issues or inadequate supporting science, but with attitudes, beliefs and communications. The JD Control 10-Point Plan is a practical step-by-step guide for veterinary practices detailing how to develop JD control plans. In summary, veterinary practices should agree on a database which can be used to store data, develop a ‘Johne's disease champion’, conduct knowledge exchange events and follow up with individual farmers to better understand the attitudes and beliefs of their clients. Then, in line with the NJMP, use risk assessment and initial surveillance data to discuss and develop a JD control plan which is to be reviewed annually.

Schema Extraction in NoSQL Databases: A Systematic Literature Review

Introduction: Nowadays, NoSQL databases have taken on an increasingly important role in the storage of massive data within companies. Due to a common property called schema-less, NoSQL databases offer great flexibility, particularly for the storage of data in different formats. However, despite their success in data storage, schema-less databases are a major obstacle in areas requiring precise knowledge of this schema, especially in the field of data integration. Method: This study presents a Systematic Literature Review (SLR) to explore, evaluate, and discuss relevant existing research and endeavors using novel schema extraction approaches. Furthermore, we conducted this study using a well-defined methodology to examine and study the problem of schema extraction from NoSQL databases. Results: Our research results highlight and emphasize the scheme extraction approaches and provide knowledge to researchers and practitioners by proposing schema extraction approaches and their limitations, which contributes to inventing new, more efficient approaches. Conclusion: In our future work, inspired by the recent advances in quantum computing and the emergence of post-quantum cryptography (PQC), we aim to propose a schema extraction approach that blends cutting-edge technologies with a strong focus on database security.

Recent Progress in Two-Dimensional Magnetic Materials.

The giant magnetoresistance effect in two-dimensional (2D) magnetic materials has sparked substantial interest in various fields; including sensing; data storage; electronics; and spintronics. Their unique 2D layered structures allow for the manifestation of distinctive physical properties and precise performance regulation under different conditions. In this review, we present an overview of this rapidly developing research area. Firstly, these 2D magnetic materials are catalogued according to magnetic coupling types. Then, several vital effects in 2D magnets are highlighted together with theoretical investigation, such as magnetic circular dichroism, magneto-optical Kerr effect, and anomalous Hall effect. After that, we forecast the potential applications of 2D magnetic materials for spintronic devices. Lastly, research advances in the attracting magnons, skyrmions and other spin textures in 2D magnets are discussed.

Hybrid-Layer Data Storage with High-Orthogonality Random Meta-Channels

Optical data storage (ODS) is a low-cost and high-durability counterpart of traditional electronic or magnetic storage. As a means of enhancing ODS capacity, the multiple recording layer (MRL) method is more promising than other approaches such as reducing the recording volume and multiplexing technology. However, the architecture of current MRLs is identical to that of recording data into physical layers with rigid space, which leads to either severe interlayer crosstalk or finite recording layers constrained by the short working distances of the objectives. Here, we propose the concept of hybrid-layer ODS, which can record optical information into a physical layer and multiple virtual layers by using high-orthogonality random meta-channels. In the virtual layer, 32 images are experimentally reconstructed through holography, where their holographic phases are encoded into 16 printed images and complementary images in the physical layer, yielding a capacity of 2.5 Tbit·cm−3. A higher capacity is achievable with more virtual layers, suggesting hybrid-layer ODS as a possible candidate for next-generation ODS.

On-the-fly clustering for exascale molecular dynamics simulations

Computational resources have experienced exponential growth in the last decades enabling the simulation of complex physical problems at the cost of a massive increase in data storage. This is especially true for N-body simulations now reaching billions or trillions particles in certain cases. To overcome the drawbacks of data storage on disk for post-processing purposes, on-the-fly analysis has gained momentum but still represents a challenge in both its implementation and efficiency without impacting the simulation engine performances. This work provides a new in-situ procedure for features detection in massive N-body simulations, leveraging state-of-the-art techniques from various fields. Based on a discrete-to-continuum paradigm shift, particles and their respective physical quantities are projected onto a 3D regular grid before applying image analysis algorithms to group voxels based on specific user-defined criteria. A significant extension to the hybrid parallelism of connected component analysis within the image processing community is also introduced in the present study. Traditionally operating in shared memory parallelism, this extension now incorporates both distributed and shared memory approaches. The implementation is carried out within the exaStamp classical Molecular Dynamics code, a variant of the open-source exaNBody platform (see section 6). This adaptation allows for the on-the-fly analysis of multi-billion atoms samples with at most a 1.3% overhead. In addition, the entire framework is benchmarked up to 32768 cores. The applicability of the present approach is demonstrated on the case of a spall fracture in a tantalum sample as well as high velocity impact of a tin droplets on a rigid surface.

Study of Structural, Magnetic, and Thermoelectric Properties of Rare Earth-based CdCe2X4 (X = S, Se, Te) Spinels for Spintronic and Energy Harvesting Applications

Controlling the spin degree of freedom in electronics paves the way for novel approaches to employ, relocate, and store data at accelerated rates. In this regard, an in-depth examination of the structural, electronic, magnetic, and transport behaviour of CdCe2X4 (X = S, Se, Te) is undertaken. It is observed that ferromagnetic states exhibit higher energy release compared to antiferromagnetic states. Room temperature ferromagnetism is characterized by the Tc and spin-polarized density of states. The underlying mechanism in ferromagnetic behaviour is elicited in terms of crystal field energy, double exchange mechanism, exchange energies, and constants. The magnetic moment shift from Ce to other NM sites (Cd, X) is identified as a mechanism sustaining ferromagnetic character through electron exchange, thereby preventing clustering. Furthermore, the temperature-dependent thermoelectric properties are investigated, encompassing electrical and thermal conductivity, Seebeck coefficient, and power factor, recommending exploration of spinels as potential candidates for sustainable energy devices.

Model management to support systems engineering workflows using ontology-based knowledge graphs

System engineering has been shifting from document-centric to model-based approaches, where assets are becoming more and more digital. Although digitisation conveys several benefits, it also brings several concerns (e.g., storage and access) and opportunities. In the context of Cyber-Physical Systems (CPS), we have experts from various domains executing complex workflows and manipulating models in a plethora of different formalisms, each with their own methods, techniques and tools. Storing knowledge on these workflows can reduce considerable effort during system development not only to allow their repeatability and replicability but also to access and reason on data generated by their execution. In this work, we propose a framework to manage modelling artefacts generated from workflow executions. The basic workflow concepts, related formalisms and artefacts are formally defined in an ontology specified in OML (Ontology Modelling Language). This ontology enables the construction of a knowledge graph that contains system engineering data to which we can apply reasoning. We also developed several tools to support system engineering during the design of workflows, their enactment, and artefact storage, considering versioning, querying and reasoning on the stored data. These tools also hide the complexity of manipulating the knowledge graph directly. Finally, we have applied our proposed framework in a real-world system development scenario of a drivetrain smart sensor system. Results show that our proposal not only helped the system engineer with fundamental difficulties like storage and versioning but also reduced the time needed to access relevant information and new knowledge that can be inferred from the knowledge graph.

Adoption and Use of Electronic Human Resources Management Systems for Service Delivery in Tanzania: A Case to Tanzania Airports Authority

This articles explores the adoption and utilization of Electronic Human Resources Management Systems (e-HRMS) for service delivery at the Tanzania Airports Authority (TAA). General objective was to assess the adoption and use of electronic human resource management systems for HR service delivery at Tanzania Airports Authority. The specific objectives of the study were to examine the practice of eHRMS adopted to support service delivery in the Tanzania Airports Authority, to examine the effort made by the government to enhance the usage and adoption eHRMS in service delivery at Tanzania Airports Authority and to identify the challenges in using e-HRMS in service delivery in Tanzania. The study utilized the Technology Acceptance Model (TAM) to understand user acceptance behaviour and the Diffusion of Innovations Theory to explore how e-HRMS spreads within the organization. Research adopted an explanatory research design and population of study was 60 staff. Data was collected through questionnaires from a purposively selected sample of 52 staff with qualitative data from interviews conducted with HR and IT officers. Quantitative data was analysed using descriptive analysis, while thematic analysis was applied to qualitative data. Findings reveal that TAA has implemented various e-HRMS practices, including digital storage of employee data, automated payroll systems, and streamlined recruitment and onboarding processes. Government support has been instrumental in these efforts through policy implementation, financial support and infrastructure development. However, several challenges hinder the full potential of e-HRMS at TAA, such as limited access to technology, unreliable power supply, skills gaps, resistance to change, and cost considerations. The study concludes that e-HRMS has significantly improved HR service delivery at TAA. Nonetheless, continuous efforts are necessary to address existing challenges. Enhancing technological infrastructure, providing comprehensive training, and implementing effective change management strategies are crucial for optimizing the benefits of e-HRMS. The articles recommends that TAA invest in reliable internet connectivity and IT hardware, provide ongoing training for employees, and develop robust change management plans.

Perceptions of Postgraduates Towards Using Citation Management Software in Academic Writing: A Case Study in a Vietnamese University

Citation management software (CMS), especially Mendeley, has been suggested for researchers to automatically manage bibliographic information thanks to its complementary version with significant space for data storage. However, little research has been conducted regarding the applicability of Mendeley to the academic writing of postgraduates, especially in Vietnam. This study examined postgraduates’ perspectives toward utilizing Mendeley in academic writing during their language master’s programs at a public university in Vietnam using a mixed method. Data was collected through pre- and post-survey questionnaires of 45 postgraduates majoring in foreign languages and in-depth interviews for a thorough investigation. The findings indicated that Mendeley enhanced the participants’ research productivity and quality, but technological issues and a lack of training limit its use. Also, the study recommended that the institution organize workshops, seminars, and fundamental training courses in Mendeley for postgraduates to use it efficiently.

Multi-Mode Data Organization and File Retrieval Based on a Primer Library in Large-Scale Digital DNA Storage

At present, the polymerase chain reaction (PCR) amplification-based file retrieval method is the most commonly used and effective means of DNA file retrieval. The number of orthogonal primers limits the number of files that can be accurately accessed, which in turn affects the density in a single oligo pool of digital DNA storage. In this paper, a multi-mode DNA sequence design method based on PCR file retrieval in a single oligonucleotide pool is proposed for high-capacity DNA data storage. Firstly, by analyzing the maximum number of orthogonal primers at each predicted primer length, it was found that the relationship between primer length and the maximum available primer number does not increase linearly, and the maximum number of orthogonal primers is on the order of 104. Next, this paper analyzes the maximum address space capacity of DNA sequences with different types of primer binding sites for file mapping. In the case where the capacity of the primer library is R (where R is even), the number of address spaces that can be mapped by the single-primer DNA sequence design scheme proposed in this paper is four times that of the previous one, and the two-level primer DNA sequence design scheme can reach [R2∙(R2-1)]2 times. Finally, a multi-mode DNA sequence generation method is designed based on the number of files to be stored in the oligonucleotide pool, in order to meet the requirements of the random retrieval of target files in an oligonucleotide pool with large-scale file numbers. The performance of the primers generated by the orthogonal primer library generator proposed in this paper is verified, and the average Gibbs free energy of the most stable heterodimer formed between the orthogonal primers produced is –1 kcal∙(mol∙L−1)−1 (1 kcal = 4.184 kJ). At the same time, by selectively PCR-amplifying the DNA sequences of the two-level primer binding sites for random access, the target sequence can be accurately read with a minimum of 103 reads, when the primer binding site sequences at different positions are mutually different. This paper provides a pipeline for orthogonal primer library generation and multi-mode mapping schemes between files and primers, which can help achieve precise random access to files in large-scale DNA oligo pools.

A Remote Monitoring System for Wind Speed and Direction Based on Non-Contact Triboelectric Nanogenerator

Wind speed and wind direction sensors are crucial sensor categories in the Internet of Things (IoT), particularly vital in fields such as meteorological monitoring, construction engineering, transportation engineering, and ocean engineering. However, power supply remains a key limiting factor for the widespread application of these sensors in large-scale sensor networks. In this paper, a self-powered, non-contact wind speed and direction sensor based on the triboelectric nanogenerator (SD-TENG) is proposed. The optimized wind speed measurement structure has a start-up wind speed as low as 0.2m/s and exhibits good linearity in the range of 0.2-29m/s. Additionally, the sensor demonstrates high temperature and humidity resistance, with a voltage attenuation of 2.4% at 45°C ambient temperature and 9.8% at 95% relative humidity. For wind direction measurement, the design of non-uniform electrodes enhances the recognition capability of different channels. To meet the demands of remote monitoring, we have designed an advanced signal processing circuit that can directly convert the raw output of a wind speed sensor into wind speed information and upload it to a cloud platform via a host. This system not only records and displays wind speed data in real-time but also features historical data storage and alarm functionalities, enhancing the intelligence and automation levels of wind speed monitoring. Additionally, users can access and analyze wind speed data through both computer and mobile devices, ensuring the system's efficiency and reliability. This work provides crucial technical support for the advancement of smart cities, clean energy, and environmental monitoring, thereby promoting the application and dissemination of IoT technology in the environmental field.

Cr3+-Activated Deep Trap Electron-Trapping Biphasic Mixture of Zn (Al,Ga)2O4 and Zn2GeO4 for Multilevel Information Storage by Trap Multiplexing and Wavelength Multiplexing.

Double wavelength emitting phosphors with hypersensitive thermal response are important for optical/thermal sensors and multiplexing optical data storage technology. However, it is a daunting challenge to develop multicolor electron-trapping materials with superheat sensitivity and anomalous quenching luminescence characteristics for information storage. Here, based on the selection of host lattice and the control of doping ion types, we have designed Mn2+- and/or Cr3+-activated persistent materials with excellent fluorescence properties. Among these phosphors, Mn,Cr co-activated biphasic mixture exhibits not only sensitive anomalous thermosensitive fluorescence properties but also multicolor and multimode fluorescence emission characteristics derived from Mn and Cr simultaneously. The corresponding multimode fluorescence mechanism is proposed based on afterglow energy transfer and deepening trap effect. Especially, based on the excellent fluorescence performances, these phosphors as information storage medium demonstrate multilevel information storage by a combination of the trap multiplexing and wavelength multiplexing technologies. The study here provides not only the ideas for designing and synthesizing new electronic materials but also a material foundation for the fourth generation of optical information storage and encryption.