The Spin-Transfer Torque Magnetic Random Access Memory (STT-MRAM) is on its way to commercialization. However, the development of high-quality test solutions for STT-MRAMs poses challenges due to the specific working mechanism of the core element of the STT-MRAM bit cells, i.e., the magnetic tunnel junction (MTJ), which involves both a magnetic field and spin-transfer torque. This property can introduce defects unique to MTJs which may escape from test programs that consist solely of functional write and read operations, like march tests. Hence, it is important to develop test solutions that go beyond conventional march tests. This paper explores the effect of applying an external magnetic field (H_ext) on the test quality and test time of STT-MRAMs, which could be achieved by integrating one or more magnets in the Automated Test Equipment (ATE) setup. A framework for these so-called H_ext-assisted tests is presented and implemented for all known conventional and unique defects. The paper demonstrates that the H_ext-assisted tests offer superior coverage and/or lower test time compared to regular functional tests, like march tests. The effectiveness of these tests are validated through silicon measurements.

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Guaranteeing high-quality test solutions for Spin-Transfer Torque Magnetic RAM (STT-MRAM) is a must to speed up its high-volume production. A high test quality requires maximizing the fault coverage. Detecting permanent faults is relatively simple compared to intermittent faults; the latter are faults (caused by non-environmental conditions) that appear and disappear as a function of time, and are therefore hard to detect. Testing for such faults in STT-MRAMs is even worse considering the Magnetic Tunneling Junction inherent property ‘intrinsic switching stochasticity’, which results in inevitable random write errors. This paper presents a novel Design-for-Testability (DFT) scheme for detecting intermittent faults in STT-MRAMs; it is based on monitoring the write current. The strength of the write current is inversely correlated to the write error rate; when the write current is smaller than the specification, the device is considered faulty. A reduction in the write current can be caused by any defect in the write path of the memory (e.g., interconnects and contacts). Simulation results based on industrial design show that applying DFT yields a superior coverage of intermittent faults compared to functional test methods, such as march tests.@en

Spin-Transfer Torque Magnetic RAMs (STT-MRAMs) are on their way to commercialization. However, obtaining high-quality test and diagnosis solutions for STT-MRAMs is challenging due to the existence of unique defects in Magnetic Tunneling Junctions (MTJs). Recently, the Device-Aware Test (DA-Test) method has been put forward as an effective approach mainly for detecting unique defecting STT-MRAMs. In this study, we propose a further advancement based on the DA-Test framework, introducing the Device-Aware Diagnosis (DA-Diagnosis) method. This method comprises two steps: a) defining distinctive features of each unique defect by characterization and physical analysis of defective MTJs, and b) utilizing march algorithms to extract distinctive features. The effectiveness of the proposed approach is validated in an industrial setting with real devices and data measurement.

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The development of Spin-transfer torque magnetic RAM (STT-MRAM) mass production requires high-quality dedicated test solutions, for which understanding and modeling of manufacturing defects of the magnetic tunnel junction (MTJ) is crucial. This paper introduces and characterizes a new defect called Back-Hopping (BH); it also provides its fault models and test solutions. The BH defect causes MTJ state to oscillate during write operations, leading to write failures. The characterization of the defect is carried out based on manufactured MTJ devices. Due to the observed non-linear characteristics, the BH defect cannot be modelled with a linear resistance. Hence, device-aware defect modeling is applied by considering the intrinsic physical mechanisms; the model is then calibrated based on measurement data. Thereafter, the fault modeling and analysis is performed based on circuit-level simulations; new fault primitives/models are derived. These accurately describe the way the STT-MRAM behaves in the presence of BH defect. Finally, dedicated march test and a Design-for-Test solutions are proposed.

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The manufacturing process of STT-MRAM requires unique steps to fabricate and integrate magnetic tunnel junction (MTJ) devices which are data-storing elements. Thus, understanding the defects in MTJs and their faulty behaviors are paramount for developing high-quality test solutions. This article applies the advanced device-aware test to intermediate (IM) state defects in MTJ devices based on silicon measurements and circuit simulations. An IM state manifests itself as an abnormal third resistive state, which differs from the two bi-stable states of MTJ. We performed silicon measurements on MTJ devices with diameter ranging from 60nm to 120nm; the results show that the occurrence probability of IM state strongly depends on the switching direction, device size, and bias voltage. We demonstrate that the conventional resistor-based fault modeling and test approach fails to appropriately model and test such a defect. Therefore, device-aware test is applied. We first physically model the defect and incorporate it into a Verilog-A MTJ compact model and calibrate it with silicon data. Thereafter, this model is used for a systematic fault analysis based on circuit simulations to obtain accurate and realistic faults in a pre-defined fault space. Our simulation results show that an IM state defect leads to intermittent write transition faults. Finally, we propose and implement a device-aware test solution to detect the IM state defect.

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The popularity of perpendicular magnetic tunnel junction (pMTJ)-based spin-transfer torque magnetic random access memories (STT-MRAMs) is growing very fast. The performance of such memories is very sensitive to magnetic fields, including both internal and external ones. This article presents a magnetic-field-aware compact model of pMTJ, named the MFA-magnetic tunnel junction (MTJ) model, for magnetic/electrical co-simulation of MTJ/CMOS circuits. Magnetic measurement data of MTJ devices, with diameters ranging from 35 to 175 nm, are used to calibrate an in-house magnetic coupling model. This model is subsequently integrated into our developed compact pMTJ model, which is implemented in Verilog-A. The superiority of the proposed MFA-MTJ model for device/circuit co-design of STT-MRAM is demonstrated by simulating a single pMTJ as well as STT-MRAM full circuits. The design space is explored under PVT variations and various configurations of magnetic fields.

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Understanding the manufacturing defects in magnetic tunnel junctions (MTJs), which are the data-storing elements in STT-MRAMs, and their resultant faulty behaviors are crucial for developing high-quality test solutions. This paper introduces a new type of MTJ defect: synthetic anti-ferromagnet flip (SAFF) defect, wherein the magnetization in both the hard layer and reference layer of MTJ devices undergoes an unintended flip to the opposite direction. Both magnetic and electrical measurement data of SAFF defect in fabricated MTJ devices is presented; it shows that such a defect reverses the polarity of stray field at the free layer of MTJ, while it has no electrical impact on the single isolated device. The paper also demonstrates that using the conventional fault modeling and test approach fails to appropriately model and test such a defect. Therefore device-Aware fault modeling and test approach is used. It first physically models the defect and incorporate it into a Verilog-A MTJ compact model, which is afterwards calibrated with silicon data. The model is thereafter used for fault analysis and modeling within an STT-MRAM array; simulation results show that a SAFF defect may lead to an intermittent Passive Neighborhood Pattern Sensitive Fault (PNPSF1i) when all neighboring cells are in logic '1' state. Finally, test solutions for such fault are discussed.

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Understanding the defects in magnetic tunnel junctions (MTJs) and their faulty behaviors are paramount for developing high-quality tests for STT-MRAM. This paper characterizes and models intermediate (IM) state defects in MTJs; IM state manifests itself as an abnormal third resistive state, apart from the two bi-stable states of MTJ. We performed silicon measurements on MTJ devices with diameter ranging from 60 nm to 120 nm; the results reveal that the occurrence probability of IM state strongly depends on the switching direction, device size, and applied bias voltage. To test such defect, appropriate fault models are needed. Therefore, we use the advanced device-aware modeling approach, where we first physically model the defect and incorporate it into a Verilog-A MTJ compact model and calibrate it with silicon data. Thereafter, we use a systematic fault analysis to accurately validate a theoretically predefined fault space and derive realistic fault models. Our simulation results show that the IM state defect causes intermittent write transition faults. This paper also demonstrates that the conventional resistor-based fault modeling and test approach fails in appropriately modeling IM defects, and hence incapable of detecting such defects.@en

As a unique mechanism for MRAMs, magnetic coupling needs to be accounted for when designing memory arrays. This paper models both intra- and inter-cell magnetic coupling analytically for STT-MRAMs and investigates their impact on the write performance and retention of MTJ devices, which are the data-storing elements of STT-MRAMs. We present magnetic measurement data of MTJ devices with diameters ranging from 35 nm to 175 nm, which we use to calibrate our intra-cell magnetic coupling model. Subsequently, we extrapolate this model to study inter-cell magnetic coupling in memory arrays. We propose the inter-cell magnetic coupling factor Ψ to indicate coupling strength. Our simulation results show that Ψ≈2% maximizes the array density under the constraint that the magnetic coupling has negligible impact on the device's performance. Higher array densities show significant variations in average switching time, especially at low switching voltages, caused by inter-cell magnetic coupling, and dependent on the data pattern in the cell's neighborhood. We also observe a marginal degradation of the data retention time under the influence of inter-cell magnetic coupling.@en

STT-MRAM mass production is around the corner as major foundries worldwide invest heavily on its commercialization. To ensure high-quality STT-MRAM products, effective yet cost-efficient test solutions are of great importance. This article presents a systematic device-aware defect and fault modeling framework for STT-MRAM to derive accurate fault models which reflect the physical defects appropriately, and thereafter optimal and high-quality test solutions. An overview and classification of manufacturing defects in STT-MRAMs are provided with an emphasis on those related to the fabrication of magnetic tunnel junction (MTJ) devices, i.e., the data-storing elements. Defects in MTJ devices need to be modeled by adjusting the affected technology parameters and subsequent electrical parameters to fully capture the defect impact on both the device's electrical and magnetic properties, whereas defects in interconnects can be modeled as linear resistors. In addition, a complete single-cell fault space and nomenclature are defined, and a systematic fault analysis methodology is proposed. To demonstrate the use of the proposed framework, resistive defects in interconnect and pinhole defects in MTJ devices are analyzed for a single 1T-1MTJ memory cell. Test solutions for detecting these defects are also discussed.

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This paper proposes a new test approach that goes beyond cell-aware test, i.e., device-aware test. The approach consists of three steps: defect modeling, fault modeling, and test/DfT development. The defect modeling does not assume that a defect in a device (or a cell) can be modeled electrically as a linear resistor (as the traditional approach suggests), but it rather incorporates the impact of the physical defect on the technology parameters of the device and thereafter on its electrical parameters. Once the defective electrical model is defined, a systematic fault analysis (based on fault simulation) is performed to derive appropriate fault models and subsequently test solutions. The approach is demonstrated using two memory technologies: resistive random access memory (RRAM) and spin-transfer torque magnetic random access memory (STT-MRAM). The results show that the proposed approach is able to sensitize faults for defects that are not detected with the traditional approach, meaning that the latter cannot lead to high-quality test solutions as required for a defective part per billion (DPPB) level. The new approach clearly sets up a turning point in testing for at least the considered two emerging memory technologies.@en

The STT-MRAM manufacturing process involves not only traditional CMOS process steps, but also the integration of magnetic tunnel junction (MTJ) devices, the data-storing elements. This paper demonstrates a paradigm shift in fault modeling for STT-MRAMs by performing defect modeling and fault analysis for MTJ pinhole defects which are seen as a key type of STT-MRAM manufacturing defects. A Verilog-A compact model for defect-free MTJ devices is built and calibrated with electrical measurements on actual MTJ wafers. MTJs with a pinhole defect are extensively characterized, both during manufacturing test (t=0) and in the field (t>0), and the data is used to extend our defect-free MTJ compact model to include parameterized pinhole defects. The model is then used to perform single-cell static fault analysis and this shows not only what kind of faults can occur in an STT-MRAM, but also that the conventional fault modeling approach based on linear resistors cannot catch such behavior.@en

Spin-transfer-torque magnetic RAM (STT-MRAM) is one of the most promising emerging memory technologies. As various manufacturing vendors make significant efforts to push it to the market, appropriate STT-MRAM testing is of
great importance. In this paper, we demonstrate that conventional STT-MRAM defect modeling, which is based on linear resistors, is too pessimistic in representing the real nature of physical defects. It may result in incorrect fault models, which in turn can lead to low-quality test solutions. In addition, we propose a generic defect modeling methodology which captures the nonlinear behavior of STT-MRAM defects accurately; a defect is modeled by adjusting the affected STT-MRAM technology parameters. The methodology is illustrated by two examples, namely a pinhole defect and a sidewall redeposition defect, which are simulated for accurate fault modeling. In case of a pinhole defect, the STT-MRAM suffers from a fast transition between magnetic tunnel junction (MTJ) states with increased write current, making the MTJ more vulnerable to breakdown. However, with the conventional linear resistor as defect model the memory shows a slow transition or even a transition failure. Similarly, a sidewall redeposition defect causes a fast transition without current elevation, which is not observed when using the conventional approach.@en