On-site rapid monitoring of the permanganate index (CODMn) is critical for assessing the distribution and transformation of dissolved organic matter (DOM) in surface water. Herein, we proposed a portable field test kit for rapid, visual, and cost-effective CODMn detection, complemented by an unmanned vessel for automated sampling. The method exploits the solid-phase fluorescence filter effect (SPFFE) between carbon dots (CDs) and iodine, enabling the quantification of residual KMnO4 (calculated as CODMn). A smartphone-based reader and a user-friendly fluorescence reference card were developed for quantitative analysis of CODMn and water quality classification. Under optimal conditions, a limit of detection (LOD) of 0.04 mg L-1 was obtained for CODMn with relative standard deviations (RSDs) better than 2.0%. In a field application, 33 water samples were collected and analyzed across a 133,300 m2 lake within 2 h. The results demonstrated a strong agreement with the standard method, exhibiting enhanced sensitivity, reproducibility, and portability. Spatial mapping further revealed that CODMn distribution patterns were influenced by local environmental features. This work establishes a mechanism-driven analytical strategy that couples a previously unexplored SPFFE modulation with field-deployable test kit design and autonomous sampling, advancing practical CODMn measurement for decentralized water quality monitoring and providing a scalable solution for real-time environmental surveillance.

Sexually transmitted infections (STIs) disproportionately affect adolescents and young adults (AYAs), yet testing rates in this group remain low. STI self-collection kits may potentially increase testing uptake. We sought to characterize barriers to using self-collection kits among AYAs. This cross-sectional study examined preferences and barriers related to STI self-collection kits among 445 sexually active AYAs aged 15-24 years across high STI incidence counties in the United States (U.S.). Data was collected via social media recruitment and analyzed using descriptive and inferential statistics. The study revealed disparities in comfort levels regarding receiving STI self-collection kits at home and other household members seeing them. Most participants preferred their kit to be delivered to their home, though participants aged 15-19 years and AYAs with lower education preferred to pick it up from school. Discreet delivery was perceived as more feasible by participants aged 20-24 years, those who were employed, and those living in the southern U.S. Individuals with less than a high school education were less likely to feel comfortable self-collecting for STI testing. Participants favored written or video instructions for specimen collection and email or text message for results notification. Participants expressed a high likelihood of referring their sexual partners for testing and treatment. These findings underscore the importance of tailoring STI self-collection kit design and delivery to AYA subpopulations. Future research and programs should prioritize AYAs' desires for discreet delivery, clear specimen self-collection instructions, and digital communication options to benefit and optimize STI testing for AYAs.

This work introduces a relaxation oscillator circuit for generating square waves using an active block referred to as the extra-X second-generation current conveyor (EXCCII). The design utilizes a single EXCCII, three resistors, and a single grounded capacitor. The used capacitor is grounded, which aids in parasitic absorption within the circuit. The circuit is designed to provide three simultaneous square wave outputs. The paper provides a comprehensive circuit investigation, covering the thorough ideal, non-ideal and parasitic conditions. To validate the suggested relaxation oscillator’s theoretical concepts, post-layout results with 180-nm generic process design kits (GPDK) technology carried out via Cadence Virtuoso are included. The used active element, EXCCII layout, measures 24 µm × 28 µm only in size. The suggested circuit achieves a high operating frequency of 10 MHz, functions on a low ±1.25 V power supply, and consumes only 0.8 mW of power. It accurately detects capacitor variations across five decades. Besides simulation results, the circuit has been experimentally validated using commercial AD844 ICs, with only two AD844 devices needed for testing.

This article aims to synthesize the current ecosystem of open-source tools for Integrated Circuit (IC) design, covering the entire digital design flow from Register-Transfer Level (RTL) description to fabricable layouts. The survey categorizes and analyzes tools across major stages of design, including code-generation tools, logic synthesis, simulation, and physical design flow. Special emphasis is given to the fabricable open-source Process Design Kit (PDK), which enables the physical realization of open-hardware projects. By examining interoperability, limitations, and maturity across this toolchain, the article provides a comprehensive overview of the Electronic Design Automation (EDA) landscape and identifies the research and educational opportunities that arise from democratizing silicon design through open and reproducible workflows.

A hybrid approach for accelerating detailed routing of very large-scale integration (VLSI) circuits is proposed. The method combines a neural network model based on the U-Net architecture enhanced with Self-Attention and the classical Rip-Up and Reroute (RR) algorithm. Experimental results demonstrate a significant acceleration of the routing process without loss of quality. The proposed solution illustrates the practical efficiency of machine learning methods in the field of physical design automation. The proposed approach represents the detailed routing task in a tensor form that preserves complete spatial information required for constructing routing paths. А modified deep learning segmentation model is developed to predict routing patterns for multiple nets simultaneously within a shared topological region. The predictions of the neural network serve as an initial approximation for the heuristic RR algorithm, which substantially reduces the number of iterations needed to reach convergence. The neural network is trained on data derived from the results of global routing and physical design parameters extracted from LEF/DEF and Guide files. А new data decomposition method is introduced that allows the neural model to be adapted to any process design kit (PDK) by partitioning the routing layers into independent stacks. Tests on real integrated circuits show that the proposed method achieves up to a fivefold speedup compared to the open-source router OpenLane, particularly for large-scale designs. The study highlights the potential of deep learning in reducing the computational cost of detailed routing, one of the most time-consuming stages in VLSI physical synthesis. The approach demonstrates scalability, adaptability to different design rules, and opportunities for further performance gains through model optimization and integration into existing EDA workflows.

In this work, we describe and demonstrate a novel Technology Computer Aided Design (TCAD) driven methodology to re-center room-temperature Process Design Kits (PDKs) for cryogenic operation using a limited set of experimental measurements. Unlike previous approaches that relied on direct fitting of sparse measurements, our technique accounts for process-induced deviations by calibrating TCAD models to both room-temperature and cryogenic data. Compact models for all process corners are extracted from TCAD-generated target characteristics, enabling accurate cryogenic modeling without dedicated foundry support. This scalable, technology-independent method provides a practical path for cryogenic circuit design. • A TCAD-driven method for re-centering room-temperature PDKs to cryogenic conditions. • Minimal cryogenic measurements are used to calibrate TCAD device models. • Compact models are extracted for cryogenic temperatures by fitting TCAD-generated target data. • The approach is scalable and applicable across different technology nodes and architectures.

Standard cell layout generation in advanced semiconductor nodes presents escalating complexity due to stringent design rule constraints, multi-patterning lithographic requirements, and severely diminishing layout flexibility at sub-5nm feature sizes. This paper proposes a diffusion model-based generative framework for automating the synthesis of standard cell layouts at 5nm and below technology nodes, addressing a critical bottleneck in modern electronic design automation (EDA) flows. The proposed approach employs a denoising diffusion probabilistic model (DDPM) conditioned on cell functionalspecifications, parasitic extraction targets, pin accessibility requirements, and design rule check (DRC) parameter vectors extracted directly from process design kits (PDKs). Inspired by the forward-reverse diffusion process originally demonstrated on structured 2D data distributions — wherein a learned reverse Markov chain reconstructs complex geometric patterns from Gaussian noise — the framework applies this principle to recover DRC-compliant multi-layer layout geometries through an iterative denoising trajectory guided by cell-specific conditioning signals. A U-Net denoising backbone with multi-scale encoder-decoder structure and cross-attention conditioning injection captures both local geometric precision and global layout topology simultaneously,enabling the generative model to produce diverse yet constraint-compliantlayout solutions. A DRC-aware auxiliary training loss explicitly penalizes constraint violations at each denoising step, directly embedding rule compliance into the learned score function. Experimental evaluation on an industry-representative benchmark suite of 48 standard cell types atthe 5nm technology node demonstrates that the proposed method achieves a DRC violation rate reduction of 34.2% compared to baseline GAN approaches, generates valid layouts for 98.3% of benchmark cells, and produces performance-power-area (PPA) metrics within 8.3% of reference engineer-designed layouts. The framework reduces average layout generation time to under two minutes per cell on a single GPU, representing an order-of-magnitude improvement over conventional manual workflows. These findings establish diffusion models as a highly promising paradigm for intelligent EDA at advanced technology nodes, with significant implications for standard cell library development timelines and design-technology co-optimization research.

This letter presents a laboratory-level, closed-loop, on-wafer predictive design methodology for emerging-device monolithic microwave integrated circuits (MMICs), enabling rapid prototyping under material/process variability without a commercial process design kit (PDK). The flow integrates broadband nonlinear device modeling, test-structure-based electromagnetic (EM) back-calibration of the passive structure, and EM/circuit co-simulation to predict impedance matching and harmonic generation. A compact zero-bias 30/60 GHz frequency doubler using aligned carbon nanotube (A-CNT) Schottky diodes on high-resistivity silicon (HR-Si) validates the approach. The prototype occupies 1.3 mm<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> and achieves a minimum conversion loss (CL) of 15 dB with −1.9 dBm output power at 60 GHz, representing a clear performance improvement compared with previously reported CNT doublers. The close agreement between simulation and measurement across the intended band validates the method for mm-wave circuit development on emerging platforms.

The use of logic circuits combined with emerging devices has been studied to overcome the limitations of complementary metal-oxide-semiconductor (CMOS) transistors. Among a variety of emerging devices, magnetic tunnel junction (MTJ) is a promising candidate owing to its non-volatility, high endurance, and CMOS compatibility. However, process variations in MTJs and CMOS transistors hinder reliable and precise resistance-to-voltage conversion in hybrid MTJ/CMOS logic circuits. To address this issue, this paper proposes a novel separated pre-charge sense amplifier that achieves fast-sensing, low-power, small-area, and high-reliability. The proposed circuit eliminates intermediate inverters between the discharge and evaluation stages. It incorporates P-channel MOS (PMOS) transistors within the inverter latch, whose gates are directly biased by voltages that reflect the resistance difference between a pair of MTJs. It minimizes its nodes to be charged or discharged during operation. Furthermore, it reduces the total transistor count, including clock-driven transistors. Simulations are performed using Cadence and HSPICE tools with the NCSU CMOS 45nm design kit and a physics-based MTJ SPICE model. Monte Carlo simulations are conducted to check the circuit’s reliability under process, voltage, and temperature (PVT) variations. Post-layout simulation results show that the proposed circuit achieves the fastest sensing delay among the compared circuits except for Separated Pre-Charge Sense Amplifier (SPCSA), lowest power consumption, lowest power-delay product, smallest area overhead, and lowest sensing error rate for a viable usage in hybrid MTJ/CMOS logic memory circuits.

In the architecture of system-on-chip (SoC) design, the bus plays a critical role by facilitating inter-module connections and managing data transmission. Although the commercial bus solutions represented by the Cortex-M System Design Kit (CMSDK) are widely adopted in the industry, they exhibit lower communication efficiency in certain specialized requirements. This research focuses on optimizing the transition from a 32-bit high-speed intra-core bus to a 64-bit low-speed AHB-Lite bus. A new solution (MergFS) for this conversion process is proposed and implemented, which supports request merging and dynamic frequency switching. Experimental results show that, compared to the solution using CMSDK, MergFS reduces clock cycles by approximately 50% to 75% when processing multiple transactions. Additionally, synthesis results under the three different technologies show MergFS introduces ~4.5% area and ~6.02% power overhead on average.

The current mobile health ecosystem reflects substantial fragmentation throughout proprietary platforms, resulting in fundamental hurdles to complete fitness information utilization and clinical integration. Large technology businesses have constructed isolated health data architectures: Apple Health, Google Fit, and Samsung Health alone serve millions of end-users with minimal interoperability among them. Thousands of platform-specific applications have given way to data silos that fundamentally break holistic health monitoring and inhibit healthcare providers from accessing complete patient health profiles. Overcoming these challenges requires complex architecture solutions that include the unification of the data integration layer, modular software development kit design, and cross-platform implementation. Health data integration architectures need to harmonize these different schemas by implementing a systematic mapping protocol, an API standardization framework, and semantic interoperability mechanisms in line with the standards stipulated in Fast Healthcare Interoperability Resources. Modularity patterns allow the decomposition of monolithic wellness applications into independent deployable components, for example, authentication services, synchronization protocols, gamification frameworks, and notification systems. Cross-platform implementation methods balance the advantages of code reusability against the demands that platform-specific user experiences place on the architecture and yield quantifiable developer productivity gains through the centralization of business logic while allowing for compliance with native interface conventions. The architectural frameworks examined herein show promise for decreasing development overhead, simplifying maintenance procedures, and establishing consistency in feature implementation across heterogeneous mobile environments, thereby moving closer to seamless health data integration.

This paper presents an innovative additive manufacturing approach leveraging an organic interposer for low-parasitic and low-loss heterogeneous integration of monolithic microwave integrated circuits (MMICs) at RF and millimeter-wave (mm-wave) frequencies. The methodology involves precise fabrication of patterned cavities within the interposer to seamlessly embed MMICs. Conductive inks, micro-dispensed and cured to form lateral interconnections and integrated chip carriers, are further refined by pico-second pulsed laser micromachining to achieve micrometer-scale accuracy. This laser refinement significantly improves reflection coefficients, facilitating wideband impedance matching. Experimental validation through simulation and measurement of S-parameters for an embedded MMIC distributed amplifier demonstrates superior performance as compared to traditional wire-bonded quad flat no-lead (QFN) packages, with low interconnect attenuation (0.028 dB/mm at 5 GHz, 0.187 dB/mm at 20 GHz, and 0.512 dB/mm at 30 GHz). A system-in-package (SiP) protoype, comprising a cascaded MMIC amplifier and filter as a receiver module, achieved return losses below 10 dB and low package loss. Enhanced laser trimming and de-embedding techniques further reduced return losses beyond 27 dB and decreased insertion losses by 0.5-0.8 dB up to 30 GHz, significantly improving fabrication tolerance and performance consistency. Also, this study introduces and validates an equivalent circuit model for ground-signal-ground (GSG) probe pads up to 40 GHz repeatedly fabricated by laser-enhanced direct-print additive manufacturing (LE-DPAM) for several devices under test (DUTs). The findings offer critical insights for future development and verification of LE-DPAM foundry-compatible process design kits (PDKs), highlighting transformative potentials of additive manufacturing for advanced heterogeneous integration of MMICs, RFICs, and mixed-signal circuits.

The search for next-generation technologies has become essential due to the bottlenecks of complementary metal-oxide-semiconductor (CMOS) technology. As technology evolves, downscaling of CMOS transistors faces challenges like high power consumption, heat dissipation and quantum effects. These issues hinder further performance and efficiency improvements. To address these limitations, researchers are focusing on alternatives such as spintronics, memristors and quantum computing. Magnetic tunnel junctions (MTJs) stand out for their low power consumption, fast interconnects, CMOS compatibility and inherent nonvolatility. These features make them ideal for ultra-dense memory circuits. A hybrid CMOS/MTJ design presents significant opportunities for low-power data-intensive applications. Spin-orbit torque (SOT) offers higher writing endurance than spin-transfer torque (STT) because of its distinct read and write paths. Effective spin manipulation through SOT in MTJs is crucial for enabling low-power logic and memory functions. This paper proposes a novel energy-efficient dual read/write switching circuit with resistor-based biasing, tailored for nonvolatile combinational circuits. The proposed switching circuit is used to design a nonvolatile AND/NAND logic circuit as a case-study implementation. The simulation results are based on a 45-nm CMOS process design kit and a Verilog-A SOT MTJ model integrated into the Cadence Virtuoso platform. The proposed design demonstrates a power-delay-product (PDP) efficiency of 83.4% and an area efficiency of 45.45% based on device count. Monte Carlo (MC) simulations were conducted to account for process variations in CMOS transistors, ensuring the operational stability of the proposed writing circuit.

This study presents a comparative analysis of NOT gate performance using two different process design kits (PDKs): GPDK45 and GPDK180. The research utilizes Cadence Virtuoso software to design and simulate the NOT gate, evaluating key performance metrics such as propagation delay, power consumption, and area. The methodology involves creating the schematic and layout for the NOT gate using both GPDK45 and GPDK180, followed by generating symbols and constructing circuits to observe the gate's behavior under various conditions. The analysis includes input-output characteristics, DC response, and transient analysis to determine the gate's time delay and overall efficiency. Results show significant performance differences, with GPDK45 technology offering superior speed and reduced area at the expense of higher power consumption compared to GPDK180. These findings highlight the trade-offs in selecting a technology node for specific applications, providing valuable insights for designers aiming to optimize digital circuits in advanced semiconductor technologies. This research contributes to the ongoing efforts to scale down semiconductor devices while maintaining high performance and energy efficiency, serving as a reference for engineers and researchers working on digital circuit design.

The commercial power semiconductor market has become fiercely competitive with numerous commercial products each driving unique capabilities yet having overlapping areas of market insertion. Traditionally, when cost was the key driver, silicon-based semiconductors won in value proposition based on the component cost. However, the value wide bandgap devices bring at the system level can result in cost parity to silicon-based systems while maintaining overall performance, volume, and weight advantages. Within the wide bandgap sub-market there exists further overlap and competition between, for example, gallium nitride HEMTs competing up to 1200 V and SiC MOSFETs competing down to 650 V. These are examples of some of the most direct and observable competition in the space, yet one area not discussed as often is the competition within a similar product space like with differing variants of SiC MOSFETs. For instance, a comprehensive analysis of SiC planar MOSFETs (DMOS) compared to trench MOSFETs (TMOS) can highlight where these products stand to make improvements over the next decade. The team at Sandia National Laboratories has been involved in numerous road mapping activities for wide bandgap power semiconductor devices over the past decade [1-3] which has shaped our understanding of the field at large. This body of work will be presented based on our own analysis of the present state of the industry along with some insight for future growth opportunities.The trench MOSFET topology in SiC is desirable due to the ability to shrink cell pitch, with some topologies offering up to a 35% reduction in cell pitch compared to state-of-the-art planar devices. This has a marked impact on specific on-resistance (Ron,sp ) with trench devices demonstrating up to 20% improvement in Ron,sp . Despite this advantage, the SiC DMOS device has been shown to have more stability in Ron,sp over temperature and therefore may outperform trench MOSFETs for sustained high temperature applications. Presently there are no foundries offering a process design kit (PDK) for SiC trench MOSFETs although this is likely to change as trench MOSFET technology continues to edge out DMOS performance. In this talk we will discuss this trend and natural evolution from DMOS to TMOS and highlight some areas to extend the value proposition of the DMOS device topologies. Specifically, we will discuss methods to reduce channel resistance for DMOS devices and motivation to adopt alternate substrates (e.g. poly-SiC) or aggressive substrate thinning to create performance parity between DMOS and TMOS topologies. Finally, we will compare SiC topologies (including JFET devices) to other materials such as vertical GaN (TMOS and JFET) and future ultra-wide bandgap AlGaN devices with a careful look at what has been demonstrated versus what is theoretically possible given realistic limits of each material.

This article advances a field-ready framework that reconceives first-year composition as AI-native coding, translating a complete “design kit” into scholarly method, evaluative protocol, and curriculum architecture. Background: Contemporary composition pedagogy emphasizes process, genre awareness, and collaborative revision; meanwhile, modern software practice operationalizes iteration through version control, test-driven development, and continuous integration. The uploaded kit demonstrates that these cultures are isomorphic: writing stages align with SDLC phases, and automated pipelines can lint prose, execute argument “tests,” and publish artifacts with auditable histories. Approach: The study systematizes that kit into (1) a conceptual map that recasts authorship as orchestration and verification, (2) a pipeline specification that integrates rhetorical linters, claim-evidence checks, retrieval-grounded fact audits, and CI dashboards, and (3) an assessment regime that grades specification quality, revision discipline, and process transparency alongside argument strength and source integration. Significance of results: The framework yields inspectable process evidence that reduces adjudication ambiguity, raises floor quality on conventions through automation, and reallocates instructor attention to higher-order reasoning; it further proposes a mixed-methods research program that couples CI telemetry with blinded ratings to estimate effects on argument adequacy, equity for multilingual writers via audit trails, and transfer across disciplines. By treating “voice” as measurable style alignment under constraints and “authorship” as documented governance over generative systems, the model offers a reproducible answer to integrity, workload, and scalability in an AI-saturated academy. The contribution is a discipline-legible, automation-forward blueprint that programs can adopt in enhanced, driven, or autonomous variants without requiring coding prerequisites, supported by ready-to-deploy rubrics, YAML exemplars, and policy templates. &nbsp;

Abstract Background The increasing prevalence of STIs poses a significant public health challenge, with millions of new cases of chlamydia, gonorrhea, and trichomoniasis reported annually. An innovative approach to address this issue is the use of STI home collection kits. By offering a discreet and convenient testing option, these kits can encourage more individuals to get tested, leading to earlier detection and treatment. This study evaluates the usability of the simpli-COLLECT Urine Collection IUO Kit (sC kit) in a simulated home environment for STI testing using urine samples. Methods The sC kit was assessed through simulated use, knowledge-based questions, and subjective feedback during individual, in-person sessions. Usability data were collected from 162 participants (81 male and 81 female), divided into three age groups: adolescents (14-17 years), adults (18-64 years), and older adults (65+ years). Participants were evaluated on their ability to complete critical tasks (e.g., collecting urine sample, transferring urine to sample tube) and essential tasks (e.g., opening kit, inspecting contents, applying mailing label). Results Across all participants, the mean score for the ease of use of the sC kit was 4.6 out of 5 (SD = 0.52), and the instructional materials scored an average of 4.5 out of 5 (SD = 0.61). The pass rate for critical tasks ranged from 94.4% to 100.0%, while the pass rate for essential tasks ranged from 86.2% to 100.0% across all age groups. The older adult group had the widest range for critical and essential tasks, with ranges of 88.9% to 100.0% and 78.8% to 100.0%, respectively. The adolescent group had the narrowest range for critical and essential tasks, with ranges of 96.2% to 100.0% and 86.8% to 100.0%. Conclusion The sC kit demonstrated high usability across all age groups, with participants successfully completing both critical and essential tasks. The kit design and instructional materials were well-received, with high mean scores for ease of use. While older adults showed slightly lower pass rates, the kit remains accessible overall. These findings support the potential of the sC kit as a convenient option for STI testing at home.

The main objective of this work is to provide a comprehensive explanation of the Register Transfer Level (RTL) to Graphic Data System II (GDSII) flow for designing custom Field-Programmable Gate Array (FPGA) architectures at the 130 nm technology node using the SKY130 Process Design Kit (PDK). By leveraging open-source tools—specifically OpenLane and OpenFPGA—this study details the methodology and implementation steps required to generate a GDSII layout of a custom FPGA. OpenLane offers an integrated RTL-to-GDSII flow by combining multiple Electronic Design Automation (EDA) tools, while OpenFPGA enables the construction of flexible and customizable FPGA architectures. The article covers key aspects of the RTL-to-GDSII workflow, including RTL file configuration, the utilization of configuration variables for physical design, hierarchical chip design, macro and core implementation, chip-level integration, and gate-level simulation. Experimental results validate the proposed workflow, showcasing the successful transformation from RTL to GDSII. The findings of this research provide valuable insights for researchers and engineers in the FPGA design field, advancing the state of the art in FPGA architecture development.

Actuating monolithic photonic components (particularly slab waveguides) requires higher force due to their inherent stiffness. However, two primary constraints must be addressed: actuator footprint and fabrication limits. Increasing the number of fingers to provide the required force is not a viable solution due to space constraints, and we must also adhere to the process design kits of standard fabrications and respect their design limits. Therefore, it is crucial to increase the actuator force output without significantly enlarging the actuator footprint while maintaining the necessary travel range. In order to achieve this, we utilize arrays of electrostatic comb drives, with each repeating cell geometry optimized to produce the highest force per actuator footprint. Our optimization strategy focuses on finger geometry, the arrangement of fingers and arms design in the comb structure, including the number of fingers per arm and arm length, ensuring that each repeating cell delivers maximum force per unit area or force intensity. Co-optimizing a repeatable, footprint-optimized comb-array unit cell (arm length, arm width, finger pitch, finger count) and validating it against an asymmetric slab waveguide load, we reach a maximum pre-pull-in force intensity of about 342 N m−2 at 70 V with about 6 µm travel, confirmed by analytical modeling, numerical simulation, and measurement. Despite fabrication challenges such as over-etching and variations in electrode dimensions, detailed SEM analyses and correction functions ensure that the theoretical models closely match the experimental data, confirming the robustness and accuracy of the design. These optimized actuators, capable of achieving substantial force output without sacrificing travel range or mechanical stability, are particularly effective for applications in optical beam steering for in-plane silicon-photonics and related optical microsystems applications.

Central venous catheters (CVCs) are indispensable to contemporary critical care, perioperative management, and emergency resuscitation, yet their insertion remains fraught with preventable harm and inefficiency. This study aimed to identify all areas of CVC placement that can be improved through device design using human-centered design and qualitative research methods. This qualitative study was a contextual inquiry of CVC placement, which included observation alongside brief face-to-face interviews with physicians. It was aimed at providing a depth of understanding using evidence to demonstrate causality. This study was conducted at 3 hospitals in the emergency department, the intensive care unit, and the operating rooms. Where possible and with additional consent, sessions were recorded in video or still photography, or at times both. This study included 19 observations and 24 interviews. In this study, the approach to CVC insertion was consistent across hospitals and care environments, with moderate variability spanning a few sections, such as suture and dressing use or lack thereof in specific care environments. The described and observed difficulties leave room for improvement in device design. The results of this study indicated that there are 34 discrete steps to placing a CVC line, with most time spent during sterile preparation. As a result of the device or kit design, challenges were observed. These included missing essential materials from kits, difficulty distinguishing between nonsterile and sterile items, challenges with lidocaine ampules, patient claustrophobia from draping, and a lack of user preference for kit contents. Additional challenges included obscured ultrasound views, kinked guidewires, overall procedural untidiness, and considerable waste management issues. An intuitive kit that aligns with predictable human behavior and eliminates unnecessary multistep detours can reduce novice failure rates, cognitive load, and practice inconsistency, and it could also curb nonrecyclable waste from "backup" kits opened for a single missing item. By reframing CVC systems as sociotechnical solutions rather than static assortments of parts, the same design moves that minimize improvisation and coordination errors for physicians may also reduce dwell time and manipulation events for patients, thereby advancing the core triad of safety, procedural efficacy, and everyday usability. By examining how clinicians place central lines, this study reveals modifiable design flaws that perpetuate risk despite decades of procedural standardization. Contextual inquiry provides the evidentiary bridge between clinical imperatives to reduce complications and the practical realities of device use. Embedding such investigations at the outset of design and iteratively throughout product life cycles offers a path toward safer, more efficient, and more humane central venous access for both patients and providers.