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Earlier sources: Hardware
Hardware is the physical foundation of computing: chips, sensors, devices, networks, and the processes that manufacture them. Follow semiconductor research, compute architectures, and engineering developments alongside their software and energy connections.
SYMTRI organizes observations from public sources into a living map. Connections reflect shared subject matter; they do not establish causation or endorse a source.
Open in the map ↗520 classified signals in the fourteen-day window. Recent momentum: steady. These counts include signals awaiting readable evidence.
Earlier sources
Up to ten sources with readable evidence, ordered by their feed timestamp. These archive sources can be older than the live fourteen-day window. This list is a sample, not a measure of total activity. Dates distinguish paper publication, repository creation, model/dataset activity, Hacker News posts, and KEV catalog additions. “First archived” records when SYMTRI first stored the signal.
- OpenAlex · Published · First archived
Optimisation of wire-arc additive manufacturing parameters for processing SS316L using finite element analysis and artificial neural networks ↗
This study investigated the influence of WAAM process parameters on the thermo-mechanical behaviour of SS316L using finite element analysis and a bidirectional Artificial Neural Network (ANN). Simufact Welding was used to simulate multi-layer wall deposition and predict distortion behaviour. Experimental validation showed that the unclamped substrate ends experienced a maximum distortion of 4.50 mm due to thermal shrinkage and bending effects. The ANN demonstrated high prediction capability, with the forward model achieving a root mean square error of 1.24 mm. The backward model predicted opti…
- OpenAlex · Published · First archived
Integrated Approaches for Development of Gas Sensors: From Nanomaterials and Simulated Environment to Application in Smart Cities ↗
Reliable transition of laboratory-developed gas-sensing nanomaterials into environmental monitoring systems remains limited by the lack of integrated testing platforms capable of reproducing realistic operating conditions while providing automated, high-quality sensor characterization. In this work, we present a comprehensive framework for environmental gas sensor development centered on a custom-designed gas sensor chamber (GSC) and its connection to standalone measuring stations (sMSs) intended for smart city air quality monitoring. The GSC was developed as a dedicated platform for controlle…
- OpenAlex · Published · First archived
Energy-based characterization of sparse sensor interactions ↗
Abstract Large-dimensional empirical data in science and engineering frequently have a low-rank structure and can be represented as a combination of just a few eigenmodes. Because of this structure, we can use just a few spatially localized sensor measurements to reconstruct the full state of a complex system. The quality of this reconstruction, especially in the presence of sensor noise, depends significantly on the spatial configuration of the sensors. Multiple algorithms based on gappy interpolation and QR factorization have been proposed to optimize sensor placement. Here, instead of an al…
- OpenAlex · Published · First archived
Dynamic Skill Demand Prediction for New Energy Manufacturing Using a Knowledge Graph-Enhanced Spatiotemporal Graph Neural Network ↗
Accurate and forward-looking skill demand prediction is critical for workforce planning, curriculum development, and talent cultivation in the rapidly evolving new energy manufacturing sector. Existing approaches often rely on static occupational categories, retrospective skill taxonomies, or purely temporal models and therefore struggle to capture heterogeneous semantic dependencies, temporal evolution, and event-driven demand shocks. This study proposes an integrated framework that combines a point-in-time New Energy Manufacturing Skill Knowledge Graph (NEM-SKG) with a knowledge-graph-enhanc…
- OpenAlex · Published · First archived
Regulation of threshold and resistive switching in nitrogen-doped vanadium oxide devices for neuromorphic applications ↗
Nitrogen-doped vanadium oxide (N:VO x ) based memristors are promising candidates for neuromorphic applications by combining volatile threshold switching for neuron-like dynamics with non-volatile switching for synaptic weight modulation, providing a simple and efficient route towards neuromorphic hardware implementation . Here, we report the dual switching behavior of Pt/Ti/N:VO x /p + -Si devices and demonstrate their potential application in neuromorphic computing. In this work, a VO 2 phase-dominant N:VO x thin film was fabricated by converting a sputtered vanadium nitride (VN) thin film t…
- OpenAlex · Published · First archived
An On-Chip-Calibrated Coarse-Fine FPGA Time-to-Digital Converter for Single-Photon LiDAR: Design and Experimental Validation ↗
Long-range single-photon LiDAR requires both a wide time-of-flight (ToF) dynamic range and fine temporal resolution, while the nonuniform fine-time bins of FPGA carry-chain tapped delay lines (TDLs) can introduce systematic errors into time reconstruction. This work presents a coarse-fine FPGA time-to-digital converter (TDC) with on-chip code-density calibration implemented on a Xilinx Kintex-7 XC7K325T device. A 250 MHz coarse counter is combined with a CARRY4-based TDL for sub-cycle fine-time quantization, and code-density accumulation, lookup-table (LUT) construction, and calibrated time re…
- OpenAlex · Published · First archived
Long-Term Stability and Blood Pressure Change Tracking with a Cuffless Wearable Device in Hypertensive Patients ↗
BACKGROUND: Demonstrating reliable tracking of short- and long-term blood pressure (BP) changes is one of the conditions necessary for clinical use of cuffless devices requested by international hypertension societies. This study evaluates the stability of BP estimation over a 6-week period using CSEM's wearable cuffless photoplethysmographic (PPG) BP monitor, and its ability in tracking BP changes in hypertensive patients when compared to a validated oscillometric monitor (Microlife WatchBP Home A). METHODS: In this method-comparison/feasibility study, thirty patients attended 4 visits over s…
- OpenAlex · Published · First archived
Machine learning enabled cross-stage prediction of cathode performance using manufacturing parameters and measured electrode descriptors ↗
Optimisation of lithium-ion battery manufacturing has traditionally relied on time-consuming and resource-intensive experimental trial-and-error. Here, we fabricated LiNi 0.8 Mn 0.1 Co 0.1 O 2 (NMC811) cathodes using varied manufacturing parameters, generating an experimentally measured laboratory dataset comprising 160 electrodes and 99 coin cells across varied manufacturing conditions. Group A and Group B cathodes were matched within manufacturing batches. Group A was uncalendered, whereas Group B was calendered. We built gradient boosting regressor (GBR) models to predict the cathode proper…
- OpenAlex · Published · First archived
Tunneling Magnetoresistance Current Sensors for Power and Energy Systems: A Critical Review of Architectures, Error Mechanisms, and Design Trade-Offs ↗
Current measurement in Power and Energy Systems must accommodate direct-current components, converter harmonics, fast transients, wide dynamic ranges, and strong electromagnetic interference. Tunneling magnetoresistance (TMR) sensors offer high field sensitivity, broad intrinsic bandwidth, compact size, and low power consumption, but these device-level advantages do not directly translate into system-level accuracy or usable bandwidth. The principal contribution of this review is a unified framework organized around sensor architecture that connects magnetic tunnel junction transfer characteri…
- OpenAlex · Published · First archived
Unraveling the dielectric heterogeneity response of cell lines under electroporation: a microfluidic single-cell on-chip system ↗
In the clinical application of irreversible electroporation for tumor therapy, individual differences in cellular electrical responses often lead to the reliance on empirically selected treatment parameters, which easily cause over/under-treatment in patients and hinder the development of precision tumor therapy. To clarify the response mechanism induced by single-cell individual differences, this study developed an experimental platform integrating microfluidic chip technology, dielectrophoresis (DEP), electrorotation (EROT), and electroporation (PEF) technologies, enabling the full process o…
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Check each original source for its methods, release status, limitations, and supporting data. A repository announcement, a preprint, and a published study provide different kinds of evidence. SYMTRI’s subject classification helps discovery; it does not independently validate the source’s claims.
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