Central Unit Research Articles

Uranium-Mediated Thiourea/Urea Conversion on Chelating Ligands

2,6-Dipicolinoylbis(N,N-dialkylthioureas) and H2LR2 react with uranyl salts and a supporting base (e.g., NEt3) under formation of monomeric or oligomeric complexes of the compositions [UO2(LR2)(solv)] (solv = donor solvents) or [{UO2(LR2)(µ2-OMe)}2]2–. In such complexes, the uranyl ions are commonly coordinated by the “hard” O,N,O or N,N,N donor atom sets of the central ligand unit and the lateral sulfur donor atoms remain uncoordinated. Their individual structures, however, depend on the reaction conditions, particularly on the equivalents of NEt3 used. An unprecedented, selective hydrolysis of the uranium-coordinating bis(thioureato) ligands results in an S/O donor atom exchange at exclusively one thiourea side-arm, when an excess of NEt3 is used. The resulting trimeric uranyl complexes are isolated in fair yields and have a composition of [(UO2)3(L2Et2)2(µ2–OR)(µ3-O)]–. H2L2Et2 represents the newly formed 2,6-dipicolinoyl(N,N-diethylthiourea)(N,N-diethylurea) and R = H, Me, or Et. {L2Et2}2– binds to the uranyl units via the pyridine ring, the dialkylurea arm, and the central carbonyl groups, while the thiourea unit remains uncoordinated. The central cores of the products consist of oxido-centered triangular {(UO2)3O}4+ units. The observed reactivity is metal-driven and corresponds mechanistically most probably to a classical metal-catalyzed hydrodesulfurization. The hydrolytic thiourea/urea conversion is only observed in the presence of uranyl ions. The products were isolated in crystalline form and studied spectroscopically and by X-ray diffraction. The experimental findings are accompanied by DFT calculations, which help to understand the energetic implications in such systems.

Patients Monitoring and Data Management System for Hospitals

This work concerns creating a monitoring system for a smart hospital using Raspberry Pi to measure vital signs. The readings are continually sent to central monitoring units outside the room instead of being beside the patients, to ensure less contacting between the medical staff and patients, also the cloud is used for those who leave the hospital, as the design can track on their medical cases. Data presentation and analysis were accomplished by the LabVIEW program. A Graphical User Interface (GUI) has been created by the Virtual-Instrument (VI) of this program that offer real-time access to monitor patients' measurements. If unhealthy states are detected, the design triggers alerts and sends SMS message to the doctor. furthermore, the clinicians can scan a QR code (which is assigned to each patient individually) to access its real-time measurements. The system also utilizes Electrocardiography (ECG) to detect abnormalities and identify specific heart diseases based on its extracted parameters to encourage patients to seek timely medical attention, while aiding doctors in making well-informed decisions. To evaluate the system's performance, it is tested in the hospital on many patients of different ages and diseases as well. According to the results, the accuracy measurement of SpO2 was about 98.39%, 97.7% for (heart rate) and 98.7% for body temperature. This shows that the system can offer many patients receiving health services from various facilities, and it ensures efficient data management, access control, real-time monitoring, and secure patient information aligning with healthcare standards.

Measuring butterfly persistence in the face of deep uncertainty: a case study using the regal fritillary

Scientists have documented effects of climate and land use change across a range butterfly species. However, incorporating future climate and land use change into butterfly conservation plans is a difficult task. These difficulties arise mainly from assumptions that future processes are the same as past processes (stationarity) and because scientists cannot reliably predict the future (deep uncertainty). In this case study, I used land use and climate change scenarios to compare possible futures for the regal fritillary, a grassland butterfly in the central United States. My analysis indicated that climate and land use change have the potential to influence species persistence, but that climate change has the larger effect. Moderate warming scenarios may improve the possibility of persistence, whereas extreme warming reduces this possibility. My analysis demonstrates the importance of considering nonstationarity and alternative plausible futures in butterfly conservation planning.

Strong Electrochemiluminescence Response Derived from Ionic Chiral Covalent Organic Frameworks for Enantioselective Discrimination of Amino Acid Enantiomers via an Electrostatic Attraction Effect.

Porous chiral materials accompanied by electrochemiluminescence (ECL) activity are rarely reported for enantioselective discrimination because of the big challenges to integrate the stereogenic center and ECL-active unit in the backbone. In the present study, ionic chiral covalent organic frameworks (iCCOFs) consisting of the pyridinium unit as the ECL-active species were prepared by a facile strategy. We were amazed that such iCCOFs could display strong cathodic ECL responses. Meanwhile, the as-prepared ECL-active iCCOFs performed enantioselective ECL quenching toward amino acid enantiomers, attributed to the enhanced photoinduced electron transfer process derived from the formed complex between the iCCOFs and amino acids via an electrostatic attraction effect. The iCCOF with an (S)-configuration was prone to interact with l-amino acids, producing a lower ECL intensity. The maximum intensity ratio between the d- and l-enantiomers was 33.0. Finally, the enantiomeric compositions of the measured amino acids presented a good linear relation with the obtained ECL intensity, which was fit for the determination of samples with unknown enantiomeric purity. In brief, the obtained results convince us that this study advances a new generation of ECL-active iCCOFs and displays great potential in enantioselective sensing.

A Survey on Design Space Exploration Approaches for Approximate Computing Systems

Approximate Computing (AxC) has emerged as a promising paradigm to enhance performance and energy efficiency by allowing a controlled trade-off between accuracy and resource consumption. It is extensively adopted across various abstraction levels, from software to architecture and circuit levels, employing diverse methodologies. The primary objective of AxC is to reduce energy consumption for executing error-resilient applications, accepting controlled and inherently acceptable output quality degradation. However, harnessing AxC poses several challenges, including identifying segments within a design amenable to approximation and selecting suitable AxC techniques to fulfill accuracy and performance criteria. This survey provides a comprehensive review of recent methodologies proposed for performing Design Space Exploration (DSE) to find the most suitable AxC techniques, focusing on both hardware and software implementations. DSE is a crucial design process where system designs are modeled, evaluated, and optimized for various extra-functional system behaviors such as performance, power consumption, energy efficiency, and accuracy. A systematic literature review was conducted to identify papers that ascribe their DSE algorithms, excluding those relying on exhaustive search methods. This survey aims to detail the state-of-the-art DSE methodologies that efficiently select AxC techniques, offering insights into their applicability across different hardware platforms and use-case domains. For this purpose, papers were categorized based on the type of search algorithm used, with Machine Learning (ML) and Evolutionary Algorithms (EAs) being the predominant approaches. Further categorization is based on the target hardware, including Field-Programmable Gate Arrays (FPGAs), Application-Specific Integrated Circuits (ASICs), general-purpose Central Processing Units (CPUs), and Graphics Processing Units (GPUs). A notable observation was that most studies targeted image processing applications due to their tolerance for accuracy loss. By providing an overview of techniques and methods outlined in existing literature pertaining to the DSE of AxC designs, this survey elucidates the current trends and challenges in optimizing approximate designs.

Inferring TLB Configuration with Performance Tools

Modern computing systems are primarily designed for maximum performance, which inadvertently introduces vulnerabilities at the micro-architecture level. While cache side-channel analysis has received significant attention, other Central Processing Units (CPUs) components like the Translation Lookaside Buffer (TLB) can also be exploited to leak sensitive information. This paper focuses on the TLB, a micro-architecture component that is vulnerable to side-channel attacks. Despite the coarse granularity at the page level, advancements in tools and techniques have made TLB information leakage feasible. The primary goal of this study is not to demonstrate the potential for information leakage from the TLB but to establish a comprehensive framework to reverse engineer the TLB configuration, a critical aspect of side-channel analysis attacks that have previously succeeded in extracting sensitive data. The methodology involves detailed reverse engineering efforts on Intel CPUs, complemented by analytical tools to support TLB reverse engineering. This study successfully reverse-engineered the TLB configurations for Intel CPUs and introduced visual tools for further analysis. These results can be used to explore TLB vulnerabilities in greater depth. However, when attempting to apply the same methodology to the IBM Power9, it became clear that the methodology was not transferable, as mapping functions and performance counters vary across different vendors.

Non-fused Nonfullerene Acceptors with an Asymmetric Benzo[1,2-b:3,4-b', 6,5-b"]trithiophene (BTT) Donor Core and Different AcceptorTerminal Units for Organic Solar Cells.

Here in, we have designed two new unfused non-fullerene small molecules using asymmetric benzo[1,2-b:3.4-b', 6,5-b"]trithiophene (BTT) as the central donor core and different terminal units i. e., 2-(3-oxo-2,3-dihydro-1H-inden-1-ylidene)malononitrile (NFA-4) and 1,3-diethyl-2-thioxodi hydropyrimidine-4,6 (1H,5H)-dione (NFA-5) and examined their optical and electrochemical properties. Using a wide band-gap copolymer D18, organic solar cells (OSCs) based on bulk heterojunction of D18:NFA-4 and D18:NFA-5 showed overall power conversion efficiency (PCE) of about 17.07 % and 11.27 %, respectively. The increased PCE for the NFA-4-based OSC, compared to NFA-5 counterpart, is due higher value of short circuit current (JSC), open circuit voltage (VOC), and fill factor (FF). Following the addition of small amount of NFA-5 to the binary bulk heterojunction D18:NFA-4, the ternary organic solar cells attained a PCE of 18.05 %, surpassing that of the binary counterparts due to the higher values of which is higher than that for the binary counterparts and attributed to the increased values of JSC, FF, and VOC. The higher value of JSC is linked to the efficient use to excitons transferred from NFA-5 to NFA-4 with a greated dipole moment than NFA-5 and subsequently dissociated into a free charge carrier efficiently.

Lower Energy Consumption in Multi-CPU Cell-Free Massive MIMO Systems

Under the ideal assumption of deploying only one central processing unit (CPU) in the entire system, cell-free (CF) systems can achieve significant macro-diversity gain, thereby providing uniformly reliable service to each user equipment (UE). However, due to limitations in system scalability and the feasibility of strict phase synchronization, CF systems require a multi-CPU setup and perform coherent transmission at a smaller scale. Moreover, conventional CF systems typically operate in time-division duplex (TDD) mode and utilize statistical channel state information (CSI) for downlink (DL) decoding, but the channel hardening effect is not significant. These factors reduce downlink spectral efficiency (SE) and increase DL transmission time, leading to higher energy consumption in CF systems. To address these issues, we introduce downlink channel estimation (DLCE) in multi-CPU CF systems and derive the approximate achievable DL SE. To reduce DL pilot overhead, we propose an uplink–pilot-reuse-constrained DL pilot allocation principle. Based on this principle, we develop a farthest distance pilot allocation (FDPA) algorithm to mitigate pilot contamination. In addition, leveraging the characteristics of the heuristic distributed power allocation algorithm, we propose two access point (AP) clustering algorithms: one based on CSI (BCSI) and the other based on coherent group size (BCGS). Simulation results indicate that the introduction of DLCE significantly improves DL SE in multi-CPU CF massive MIMO systems, while the proposed FDPA algorithm further enhances DL SE. The BCSI and BCGS algorithms also effectively improve DL SE and help reduce energy consumption. By combining DLCE, the FDPA algorithm, and the proposed AP clustering algorithms, the energy consumption of multi-CPU CF systems can be significantly reduced.

Fuzzy task assignment in heterogeneous distributed multi-robot system

This study addresses the problem of coordination in cooperative multi-robot systems performing complex tasks. An analysis of cooperative behavior in mobile multi-robot systems in terms of task execution accuracy by heterogeneous robots is carried out. In addition, we evaluate the capacity and compatibility of tasks assigned to robots to optimize task execution without using direct communication with the robots or a central decision-making unit. A model for task selection in heterogeneous distributed multi-robot systems is proposed. It is based on two processes: the first decomposes complex tasks into elementary tasks, and the second assigns elementary tasks to mobile robots for real-time execution. The distribution of elementary tasks is NP-hard, which leads us to recommend approximate solutions. A fuzzy system called Fuzzy Decision Making in Task Selection is proposed, which uses fuzzy logic to solve this problem. This system allows robots to choose to perform any task in the future. An approach is presented that uses two cascading fuzzy systems. The first calculates the utility of the robot and then activates the second fuzzy system to calculate the utility of the task. By using the output of the fuzzy decision system in our model, each robot will be able to decide for itself which tasks to perform. The results of a simulation of mobile robots transporting goods demonstrate the effectiveness of this fuzzy decision-maker.

Rebuilding Peripheral F, Cl, Br Footprints on Acceptors Enables Binary Organic Photovoltaic Efficiency Exceeding 19.7.

Given homomorphic fluorine, chlorine and bromine atoms are featured with gradually enlarged polarizability/atomic radius but decreased electronegativity, the rational screen of halogen species and location on small molecular acceptors (SMAs) is quite essential for acquiring desirable molecular packing to boost efficiency of organic solar cells (OSCs). Herein, three isomeric SMAs (CH-F, CH-C and CH-B) are constructed by delicately rebuilding peripheral F, Cl, Br footprints on both central and end units. Such a re-permutation of peripheral halogens could not only maintain the structural symmetry of SMAs to the maximum, but also acquire extra asymmetric benefits of enhanced dipole moment and intramolecular charge transfer, etc. Moreover, central brominating enhances molecular crystallinity of CH-B without introducing undesirable steric hindrance on end groups, thus rendering a better balance between high crystallization and domain size control in PM6:CH-B blend. Further benefitting from the large dielectric constant, small exciton binding energy, optimized molecular packing and great electron transfer integral, CH-B affords the first class binary OSC efficiency of 19.78%, moreover, the highest efficiency of 18.35% thus far when increasing active layer thickness to ~300 nm. Our successful screening in rebuilding peripheral halogen footprints provides the valuable insight into further rational design of SMAs for record-breaking OSCs.

Rebuilding Peripheral F, Cl, Br Footprints on Acceptors Enables Binary Organic Photovoltaic Efficiency Exceeding 19.7%

Given homomorphic fluorine, chlorine and bromine atoms are featured with gradually enlarged polarizability/atomic radius but decreased electronegativity, the rational screen of halogen species and location on small molecular acceptors (SMAs) is quite essential for acquiring desirable molecular packing to boost efficiency of organic solar cells (OSCs). Herein, three isomeric SMAs (CH‐F, CH‐C and CH‐B) are constructed by delicately rebuilding peripheral F, Cl, Br footprints on both central and end units. Such a re‐permutation of peripheral halogens could not only maintain the structural symmetry of SMAs to the maximum, but also acquire extra asymmetric benefits of enhanced dipole moment and intramolecular charge transfer, etc. Moreover, central brominating enhances molecular crystallinity of CH‐B without introducing undesirable steric hindrance on end groups, thus rendering a better balance between high crystallization and domain size control in PM6:CH‐B blend. Further benefitting from the large dielectric constant, small exciton binding energy, optimized molecular packing and great electron transfer integral, CH‐B affords the first class binary OSC efficiency of 19.78%, moreover, the highest efficiency of 18.35% thus far when increasing active layer thickness to ~300 nm. Our successful screening in rebuilding peripheral halogen footprints provides the valuable insight into further rational design of SMAs for record‐breaking OSCs.

Analog Implementation of a Spiking System for Performing Arithmetic Logic Operations on Mixed‐Signal Neuromorphic Processors

In recent years, physical limitations in the integration of transistors in computers have forced the search for low‐computational‐power alternatives in hardware design. Although doubts may arise regarding the limit of the relationship between performance and power consumption in computers, these disappear when considering the brain, which is one of the most efficient computing systems. In this way, bioinspired applications try to benefit from the low‐power consumption present in the biological nervous system. Previous work has shown the feasibility of implementing spiking neural networks that operate in a Boolean manner on digital platforms, such as SpiNNaker, using basic logic gates and a spiking memory, which suggests the potential for constructing a low‐power consumption spiking computer. This work takes a first step in the implementation of a spiking central processing unit by developing an arithmetic logic unit, which is an essential block for instruction execution, demonstrating its correct operation on Dynap‐SE1. The results confirm the feasibility of using this Boolean approach on this platform, despite certain limitations in the number of inputs and operating frequencies of the blocks, and pave the way for the construction of a spiking computer.

Improving subseasonal forecast skill in the Norwegian Climate Prediction Model using soil moisture data assimilation

AbstractThis study shows the importance of soil moisture (SM) in subseasonal-to-seasonal (S2S) predictions at mid-latitudes. We do this through introducing the Norwegian Climate Prediction Model Land (NorCPM-Land), a land reanalysis framework tailored for integration with the Norwegian Climate Prediction Model (NorCPM). NorCPM-Land assimilates blended SM data from the European Space Agency’s Climate Change Initiative into a 30-member offline simulation of the Community Land Model with fluxes from the coupled model. The assimilation of SM data reduces error in SM by 10.5 % when validated against independent SM observations. It also improves latent heat flux estimates, illustrating that the adjustment of underlying SM significantly augments the capacity to model land surface dynamics. We evaluate the added value of land initialisation for subseasonal predictions, by comparing the performance of hindcasts (retrospective prediction) using the standard NorCPM with a version where the land initial condition is taken from NorCPM-Land reanalysis. The hindcast covers the period 2000 to 2019 with four start dates per year. Land initialisation enhances SM predictions, reducing error by up to 2.5-month lead time. Likewise, the error for precipitation and temperature shows improvement up to a lead time of 1.5-month. The largest improvements are observed in regions with significant land-atmospheric coupling, such as the Central United States, the Sahel, and Central India. This method further enhances the prediction of extreme temperature variations, both high and low, with the most notable improvements seen in regions at mid and high latitudes, including parts of Europe, the United States, and Asia. Overall, our study provides further evidence for the significant role of SM content in enhancing the accuracy of subseasonal predictions. This study introduces a technique for improved land initialisation, utilising the same model employed in climate predictions.

Using contrasts in horizontal P-wave reflectivity to map the base of the continental lithosphere: Results for the central and eastern U.S.

Vertical-incidence seismic reflection profiles generated from global phases for 16 earthquakes recorded by stations of the Transportable Array (TA) show distinctive patterns of P-wave reflectivity in the uppermost mantle beneath the central and eastern United States. The overall distribution of reflections identified objectively using the sign test statistic applied to bootstrapped stacks is consistent with a westward increase in depth of the lithosphere-asthenosphere boundary (LAB) from roughly 110 to 250 km that is marked within the lower lithosphere by piecewise continuous segments of elevated horizontal P-wave reflectivity. For some profiles, the onsets of zones of increased reflectivity closely match depths corresponding to the maximum negative S-wave velocity gradients found by surface-wave tomography, suggesting that P-wave reflectivity can be used to help characterize properties of the lower lithosphere. We suggest that the vertical change in horizontal reflectivity straddles the lithosphere-asthenosphere transition, encompassing a broad zone of layering caused by increased strain in the lower lithosphere as well as drag-induced flow in the asthenosphere. Some of the lines also show waveforms that fall within the depth range of arrivals identified as midlithospheric discontinuities (MLDs) in overlapping Sp receiver-function profiles. The reflection waveforms observed in the TA lines are mostly multicyclic with a mix of polarities indicating a layered transition, consistent with previous observations and model studies that show the breakup of single Sp waveforms into a series of less prominent, shorter-period P-wave reflections as the dominant frequency of incident energy is increased.

Thiourea-linked covalent triazine frameworks enable efficient and selective gold recovery from e-waste leachate

The surging electronic waste (e-waste) has been stimulating the unremitting exploration about the advanced gold recycling technology, which is of great significance to alleviate the shortage of metal resources and minimize the negative environmental impact. Herein, the thiourea-linked covalent triazine frameworks (denoted as PbTu-CTFs) have been designed and constructed by the nucleophilic substitution between cyanuric chloride (CC) and 1,4-phenylene bis(thiourea) (named PbTu) for gold recovery from the actual e-waste leachate. Benefiting from the unique structural characteristics, including large surface areas, abundant porosity, excellent chemical stability, and high-density S, N coordinative sites, the fabricated PbTu-CTFs afford ultrahigh gold adsorption capacity up to 2255 mg/g and fast kinetics, as reflected by 99 % of Au recovery efficiency within 5 min. Meanwhile, satisfactory recyclability and regeneration are maintained after six rounds of consecutive adsorption/desorption tests. Furthermore, the resulting adsorbent is well competent for highly efficient and selective gold recovery from the acidic leaching solution of wasted central processing unit (CPU), exemplify its promising actual application potential.

Tensor power flow formulations for multidimensional analyses in distribution systems

In this paper, we present two multidimensional power flow formulations based on a fixed-point iteration (FPI) algorithm to efficiently solve hundreds of thousands of Power flows (PFs) in distribution systems. The presented algorithms are the base for a new TensorPowerFlow (TPF) tool and shine for their simplicity, benefiting from multicore Central processing unit (CPU) and Graphics processing unit (GPU) parallelization. We also focus on the mathematical convergence properties of the algorithm, showing that its unique solution is at the practical operational point. The proof is validated using numerical simulations showing the robustness of the FPI algorithm compared to the classical Newton–Raphson (NR) approach. In the case study, a benchmark with different PF solution methods is performed, showing that for applications requiring a yearly simulation at 1-minute resolution, the computation time is decreased by a factor of 164, compared to the NR in its sparse formulation. Finally, a set of applications is described, highlighting the potential of the proposed formulations over a wide range of analyses in distribution systems.

IoT Based Sign to Speech Converter System

The idea introduces a system for facilitating communication between the deaf and the non-signing community through a wearable device called IoT based Sign-to-Speech Converter System. The System consist of glove & it utilizes Internet of Things (IoT) technology to bridge the communication gap by translating sign language (gestures) into spoken language in real-time. The core functionality of the system is augmented by seamless integration with an Android application, enhancing user experience and accessibility. The proposed system leverages a combination of sensors embedded within the glove to capture intricate hand movements and gestures commonly used in sign language. These data are transmitted wirelessly to a central processing unit, to interpret the gestures and generates corresponding spoken language output. The Android application serves as a user interface, allowing for customization of settings and additional features such as text-based communication. Effectiveness and practicality of the proposed system have been demonstrated, opening-up new avenues for inclusive communication and empowerment of the deaf community.

Measuring temperament in developmental research: A thin-slice approach to capturing temperament in infants and toddlers.

Temperament is a key factor in early development and predicts several key developmental outcomes. The ability to capture temperament in a variety of settings and ages is thus increasingly useful. Recent work has demonstrated the utility, reliability, and validity of thin-slice assessments in which brief snapshots of children's behavior are used to make inferences about general traits (Tackett et al., 2016). Thin-slice has been effective for assessing personality in older children (over 7-years; Tackett et al., 2016, 2017) and preschoolers 3-6 years old (Whalen et al., 2021) when engaging in lab tasks or clinical assessments. However, no work has examined the use of thin-slice for temperament in younger, typically developing infants/toddlers during lab-based tasks. The present study aims to test a downward extension of a modified thin-slice approach to assess temperament using archived videos of 516 infants/toddlers (nfemale = 255; Mage = 27.51 months, Rangeage = 17-47 months). Children were originally recruited from a range of socioeconomic backgrounds across the central United States and completed a short play session, which incorporated standard language and cognition tasks that were not designed to elicit temperament; caregivers also reported their children's temperament using the Early Child Behavior Questionnaire (Putnam & Rothbart, 2006). Naive raters scored the videos using a modification of the thin-slice approach. We find evidence of good reliability and validity for temperament scores using this approach suggesting thin-slice assessments are another method for measuring temperament in infants and toddlers. Moreover, thin-slice allows for post assessment of temperament even when it had not been formally assessed. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

A chip thermal management method realizing integrated applications of cooling, power generation and heat flow measurement based on thermoelectric effect

Thermoelectric cooling, power generation and heat flow measurement are widely used in frontier domains while each of them is still in an isolated state. They are now widely used in fields such as electronic cooling, wearable device, sensors and so on. This paper proposes a method of thermoelectric effect combined with pulse width modulation (PWM) to achieve integrating thermoelectric applications. In a PWM cycle, the integration of thermoelectric applications makes it possible to realize three different operations of temperature control, energy recovery and heat flow measurement through a single thermoelectric module. The experimental results indicate that increasing the input voltage of the thermoelectric module extends the duration for power generation and heat flow measurement, while also enhancing the energy recovery rate. When the target temperature is higher than the ambient temperature, although the temperature control accuracy slightly decreases with the increase of the target temperature, the average temperature fluctuation range of the whole experimental group is −0.09∼+0.1℃ and energy recovery rate increases by 79.9 %. When the target temperature is lower than the ambient temperature, the system can still achieve efficient energy recovery. Applying the method to the computer central processing unit(CPU), the experimental results present that the heat dissipation of CPU can be monitored by measuring heat flow. Compared with the CPU + FPU working, the total power generation is increased by 0.285 W and energy recovery rate is increased by 78.3 % when the CPU is idle.

Logic Diagnosis Based on Logic Built-In Self-Test Signatures Collected In-Field from Failing System-on-Chips

Modern embedded nanoelectronic devices, particularly in safety-critical sectors, require high dependability throughout their lifecycle. To address this, designers have started integrating extra circuitry for on-device self-testing, such as the Logic Built-In Self-Test (LBIST). However, while automatic test equipment (ATE) ensures exhaustive testing during manufacturing, in-field testing capabilities are limited. This study introduces a novel methodology for in-field data collection of failure information from LBIST engines and a subsequent logic diagnosis strategy to facilitate failure analysis of field returns. The information is collected from key-on and key-off self-tests, executed by central processing units (CPUs) with a fixed seed and different frequency configurations, primarily addressing transition delay (TRN) faults. The proposed approach capitalizes on the constrained in-field configurability of LBIST and does not require a custom architecture, making it highly practical and readily applicable to real-world devices. The logic diagnosis strategy significantly reduces the number of candidate faults by exploiting the first failing pattern index found during the in-field testing and data collection. Reducing fault candidates could enhance accuracy during failure analysis, especially when field return devices exhibit a “No Trouble Found” (NTF) behavior. The experimental results are reported for ITC’99 benchmarks and an industrial automotive system-on-chip (SoC) produced by STMicroelectronics, with about 20 million gates.