共找到 20 条结果
[This corrects the article DOI: 10.1016/j.ohx.2025.e00724.].
Field installation of piezometric sensors often involves uncertainty regarding correct placement, sensor response, and agreement with manually measured static water levels. Commercial dataloggers provide high-resolution monitoring but do not offer installation-stage validation or open access to communication protocols. To address this gap, the ESPiezometer was developed as a low-cost, open-source device based on an ESP32-C3 microcontroller with RS485 Modbus communication, on-board water level calculation, temperature-based density correction, and Bluetooth Low Energy (BLE) integration for field data logging via an Android application. The hardware enables real-time verification of raw and corrected water level readings during deployment and allows immediate comparison with manual measurements. A custom PCB and 3D-printed enclosure were designed to facilitate reproducible assembly and portability. Field validation in a groundwater observation well (30-90 m depth range) demonstrated consistent communication integrity via CRC checks and measurement repeatability with a standard deviation below 0.03 m. After density correction, measurement error was reduced by 35-50% relative to manual reference levels. The obtained results demonstrate that the ESPiezometer can serve as a reliable companion instrument, reducing uncertainty during deployment and improving confidence in long-term groundwater monitoring campaigns.
Backlash in compact servo actuators is a common source of positioning error in low-cost robotic and mechatronic systems. Measuring this backlash reliably is difficult because most servos include only a single output-shaft encoder, and conventional tools such as dial indicators can introduce enough probing force to distort the measurement. We present an open-source test stand that applies small, repeatable loads to a servo lever and measures the resulting displacement under both loaded and unloaded conditions. The stand uses low-cost components, 3D-printed fixtures, interchangeable levers, and a soft elastic coupling to apply controlled forces in opposite directions. Accompanying software coordinates the test sequence, records telemetry, and analyzes backlash using a consistent, repeatable methodology. We demonstrate how the platform can characterize single-servo and coupled-servo configurations, enabling direct comparison of mechanical performance and aiding actuator selection in design work. All CAD files, control software, and analysis tools are openly provided to support replication and further development.
This work presents the design and implementation of a low-cost mobile robot prototype for trajectory tracking and robotic swarm tasks, aimed at research and educational applications. The robot is equipped with encoders for precise movement control and features wireless communication capabilities, enabling multiple robots to operate together using the ESP-NOW (Espressif's proprietary wireless protocol) protocol. The input for calculating the trajectory is provided by a camera positioned 1.5 meters away, which analyzes the environment and supplies the necessary data for tracking. The system's performance was validated through trajectory-following tests, where the robot navigated around several obstacles. The A* algorithm was implemented to calculate optimal paths and avoid collisions, ensuring smooth navigation. The results demonstrated the robot's ability to effectively handle multiple obstacles while maintaining precise trajectory tracking. This prototype offers an affordable solution for educational and research purposes, particularly in multi-robot systems and the study of pathfinding algorithms. Future research can explore the integration of additional sensors and the optimization of the behavior of the swarm.
In various microscale applications, accurate evaluation of the mechanical properties of materials under small-strain and low-force conditions is important. However, conventional universal testing machines (UTM) are expensive and difficult to operate reliably under low-force conditions, making them unsuitable for small-strain testing. To overcome these limitations, we developed a cost-effective device for single slow micro-compression testing (MCT) to measure the mechanical properties of materials in the small-strain region. The MCT consists of a force sensor (FlexiForce A301-1, Tekscan, USA), an Arduino-based signal acquisition module, and a high-precision z-stage. The displacement control accuracy of the z-stage was verified using a laser displacement meter (LK-G10, Keyence, Japan), and the experimental results confirmed displacement and force resolutions of 1 µm and 0.01 N, respectively. Under no-load conditions, the force-displacement error between the MCT and a commercial universal testing machine (MTS, AMETEK LRX-plus, LLOYD INSTRUMENTS, UK) was within ± 2.0 %. In addition, standard and one-third-size PDMS (polydimethylsiloxane) specimens were fabricated according to ASTM D575-91 and tested using both systems; the error between the two specimens was within ± 0.05 %. From the linear region in the small-strain range, the Young's modulus of the miniature specimen was estimated, showing a percentage error of + 2.2 % from reported values, confirming high precision and reliability. The developed device, with a total fabrication cost below USD 1,500, provides cost-effectiveness, precision, and repeatability, enabling applications in polymer MEMS and soft robotics.
We present the design, construction, and validation of a low-cost digital calorimeter intended for teaching thermochemistry in chemistry, engineering, and life sciences curricula. The device repurposes a commercial 380 mL thermal container with integrated magnetic stirring, transforming it into a closed and well-insulated constant-pressure system suitable for calorimetric experiments. Temperature monitoring is achieved with a waterproof Dallas DS18B20 digital sensor interfaced to an Arduino UNO board, allowing adjustable resolution and automated data acquisition. Open source software provides real time graphical visualization, CSV export, and optional Windows executables for straightforward deployment. Compared to traditional educational calorimeters based on manual thermometry, this device offers improved reproducibility, elimination of reading errors, and enhanced student engagement through live data analysis. In contrast to professional-grade commercial calorimeters (US $15,000-100,000) and basic educational kits (US $50-500 without digital monitoring), our Arduino-based system (∼US $30 in components) provides an accessible middle ground that democratizes laboratory experimentation. Validation experiments, including neutralization and dissolution reactions, confirm reliable thermometric response, stable equilibrium detection, and enthalpy values consistent with literature. This open-hardware calorimeter not only broadens access to thermochemistry education but also serves as a platform for interdisciplinary training in electronics, programming, and laboratory automation, fostering early exposure to modern research practices.
Despite decades of research, swarm robotics still lacks realistic applications. A primary obstacle is the absence of modern, reliable, and affordable robot platforms for experimentation. Existing commercial robots are often outdated or too limited in sensing, computation, and communication. We introduce Mercator, a modular mobile robot purpose-built for contemporary swarm studies in both laboratory and indoor environments. Mercator integrates on-board object and people recognition, short- and long-range obstacle detection, ceiling-based tracking, and local, decentralized communication. By combining these capabilities in a low-cost and extensible package, Mercator enables swarm robotics research to align with modern mobile robotics standards, supporting navigation, mapping, and advanced perception in laboratory settings. This design promotes closer alignment between laboratory swarm experiments and contemporary robotic systems used in real-world settings. The platform has already been used in peer-reviewed scientific work and several master's theses, and we plan to expand its use in future research and teaching.
Growing demand for complex and efficient high-throughput experimentation is accelerating laboratory automation, yet liquid-handling robots, which are central to these workflows, remain constrained by sequential operations that limit scalability. To address this bottleneck, an asynchronous scheduling hub system, named Foehn, was developed to enable concurrent and coordinated control of multiple experimental modules within a robotic workstation. The Foehn integrates open-source hardware based on the Arduino microcontroller with a Python-based graphical user interface, forming a flexible and cost-effective control architecture. Besides, it enables asynchronous, multi-threaded operation through standardized serial protocols, managing communication between the liquid-handling robot and peripheral modules such as pumps and magnetic stirrers. Validation tests confirmed stable voltage output from H-bridge drivers, achieving a high pulse-width modulation control efficiency of 87.6%. The integrated Foehn system successfully executed concurrent pumping and stirring tasks while the liquid-handling robot performed pipetting and labware-moving, demonstrating excellent synchronization and operational stability across hardware layers. Combining modular design, open-source accessibility, and precise digital control, the Foehn system provides a scalable foundation for high-throughput automation and holds strong potential to accelerate research in chemistry, biology, and materials science by bridging benchtop setups with next-generation robotic laboratories.
The Franz diffusion cell (FDC), widely used for measuring drug absorption across the skin, is usually operated manually. However, manual operation is not only labour-intensive and time-consuming, but inevitably introduces human errors and inter-operator variability. The requirement to perform regular sampling around the clock also presents a significant logistical challenge for researchers. Commercial FDC automation solutions are costly and require proprietary/bespoke FDC designs. To overcome these challenges, we have developed Otto as a customisable and affordable, aftermarket FDC automation solution, to be retrofitted to existing FDCs of generic specifications. Otto uses a modified cartesian 3D-printer as a gantry and adds liquid-handling capabilities using 3D-printed components and common, inexpensive laboratory consumables. Liquid samples are collected into standard autosampler vials. Capable of handling 100 samples per run, Otto supports a high throughput and integrates well with downstream analytical equipment, without modifying the FDC or the analytical equipment. Its programming is facilitated by OttoMate, a companion software application with a graphical user interface designed to generate human-readable code for Otto. Here, we describe the design, construction, operation and characterisation of Otto. To our knowledge, this is the first open-source, retrofittable FDC autosampler with such throughput.
Deformation response evaluation is essential for understanding material behavior, providing insight into their suitability across many fields, such as biomechanics, materials science, and other engineering disciplines. Specialized applications in biomedical and soft materials demand miniaturization for testing under a microscope or spectroscopic stages. The current commercial machines on the market are often large, expensive, or heavy, making them difficult to use for specific needs. This hardware addresses this need by developing a cost-effective, miniature, and programmable system that can be tailored to individual lab requirements to fit multiple microscopic stages. By utilizing a bipolar stepper motor attached to a lead screw and sliding linear stage, programmed and controlled by an Arduino microcontroller, the system can apply specialized stretch under uniaxial static or cyclic loading. The developed system can be assembled for less than $100, making cost-effectiveness a central focus of this development. The device performance was validated using a variety of samples and microscope tests, with sample deformation captured in real time. The device is compatible with live imaging on microscopic stages, accommodating specialized research needs across applications.
In contemporary times, as air pollution becomes increasingly severe, the challenge for healthcare in addressing respiratory-related diseases has become more urgent than ever. To assist in researching the domain of medical equipment and education training, this paper aims to create a blower-based breath simulator (BBS) for the physiological processes of spontaneous breathing by using low-cost materials and easy-to-build hardware. Specifically, the BBS focuses on providing a representation of breathing patterns, lung compliance, and airway resistance. Notably, the BBS is built on a portable 3D printable components-based structure designed for fast installation, offering direct control of breathing modes, and can be operated for a long time. Besides, the experimental test is built according to ISO 806601-2-79:2018, with testing on a dual adult training test lung from Michigan Instruments for peak inspiratory pressure, respiratory rate, positive end-expiratory pressure, tidal volume, proximal pressure, lung pressure, and demonstrating repeatability. As a result, the BBS meets initial design criteria, which comprise being lightweight, approximately 1.5 kg for the ventilator unit, and low cost, around $650 per unit, fast production time, approximately 100 continuous hours for 3D printing, and 105 h in total for the complete prototype process.
Textile production is one of the largest industries on the planet. Global annual fibre production was over 113 million tonnes (Mt) in 2021 and is predicted to increase to 149 Mt by 2030. Research into this area has potential to have huge economic and environmental impacts, however the equipment needed to perform this research is often prohibitively expensive and only available on large scale, with quoted 'lab-scale' equipment still taking up the footprint of a small laboratory and costing hundreds of thousands of pounds. This paper details the design and fabrication of a truly lab-scale, modular wet spinning system for rapid first principle research into wet spun fibres. The total fabrication costs for this system are in the region of £500-700 and the total footprint required is <1 m2. The system also packs down for easy transportation and storage and requires a singles mains plug socket to operate. This system has already been used to explore a variety of wet spun fibres including cellulosics, alginates and caseins and has been used to develop new, novel dyeing systems for wet spun fibres as published in ASC Sustainable Chemistry and Engineering: https://doi.org/10.1021/acssuschemeng.3c07437.
Rooted Soil Shear Apparatus (RSSA) is an open-source laboratory apparatus designed to quantify the effect of plant roots on soil shear strength. Traditional methods used to assess the effect of vegetation on soil strength often rely on expensive proprietary systems and can involve sample disturbance, which may alter the root-soil interactions. This novel apparatus offers both an Arduino-based and a Raspberry Pi solution for data acquisition and control. The device enables laboratory shear testing directly in the same polyvinyl chloride (PVC) pots where the plants grow, eliminating the need to disturb the root-soil structure. Validation experiments demonstrate its effectiveness in capturing shear strength variations in rooted and non-rooted soil samples. By providing an affordable and customizable alternative to conventional shear testing equipment, the RSSA device advances research in geotechnical engineering and soil stabilization.
Mathematical modeling and simulation of aerial robotic systems (ARS) constitute a highly relevant field in domains such as smart cities and Industry 4.0. In this context, validating algorithm performance under real-world conditions remains essential. However, real-world testing presents several challenges, including the isolation of scenario-specific effects on algorithm performance. In this paper, we introduce the Low-Cost, Open-Access Sensorized Aerial Robot Multirotor Testing Operational Platform (ARMTOP). The ARMTOP features a gyroscope mounted on a fixed frame, allowing precise testing of pitch, yaw, and roll angles. Additionally, it integrates a Wi-Fi-based communication module for both sending commands and receiving onboard IMU data. The platform also includes a Graphical User Interface (GUI) for real-time visualization of IMU data, with the capability to export received data for offline analysis (e.g., feature extraction). The components of ARMTOP are developed using open-access frameworks, enhancing the platform's replicability for further customization and development.
Capturing accurate texture maps from physical materials remains a challenge in digital prototyping and projection-based spatial augmented reality (P-SAR). This paper presents an open-source material scanning system based on photometric stereo, designed for affordability, simplicity, and efficient operation. The system combines a consumer-grade digital camera, multifaceted reflector (MR16) LED lighting, and Arduino-controlled automation to acquire material data up to A4 size within 15 s. Accurate colour reproduction is achieved through a hybrid calibration workflow that integrates camera profiling with a 3D lookup table. The resulting images are processed in a streamlined Substance 3D Designer pipeline to generate albedo and normal maps compatible with physically based rendering (PBR). To evaluate performance under realistic conditions, two fabric samples were scanned and qualitatively compared with professionally digitised references. Albedo maps were assessed based on dominant colour accuracy using CIEDE2000 (ΔE00), while normal maps were evaluated through visual rendering comparisons and directional distribution analysis. Scanning and processing times were also measured to verify workflow efficiency. Results demonstrate that the proposed system produces perceptually consistent textures suitable for real-time rendering applications while offering a low-cost and customisable solution for material digitisation.
Homogeneous isotropic turbulence (HIT) chambers provide a valuable platform for experimentally studying turbulence across a wide range of systems. Existing designs are often characterized by high cost, complex fabrication requirements, and reliance on outsourced components. To address these challenges, we present a low-cost, accessible, and open-source HIT chamber that can be fabricated entirely in-house. The chamber consists of a truncated cube-shaped steel frame with acrylic windows, with a volume of 5.5 liters. Turbulence is generated using eight propellers driven by DC motors, providing controlled agitation of the flow. To assess the performance of our design, particle image velocimetry (PIV) was used to quantify the statistical properties of the turbulence. The design leverages simple machining processes and readily available parts, making it practical for laboratories regardless of resources. This open-source design aims to broaden access to HIT experimentation and provide a cost-effective platform for turbulence research and education.
In analytical and bioanalytical chemistry, pyrolysis is often used for thermal decomposition of complex, non-volatile samples into smaller and more volatile constituents in an inert atmosphere as a preparatory step in various analytical techniques to reveal the composition of a sample by quantifying its constituents and building blocks, rendering it a powerful tool for analyzing samples ranging from synthetic polymers to natural biomaterials. This work presents an open-source pyrolysis unit with temperature regulation based on the Curie temperature of a ferromagnetic wire serving as the sample holder. The system's modular design makes it adaptable to many different analytical applications. Depending on the voltage of the power supply and the excitation frequency of the coil, fast temperature rise times of 2 s can be reached, and the temperature is selectable between 350 °C and 1100 °C, depending on the material used for the ferromagnetic wire. Coupling this pyrolyzer to a gas chromatograph-ion mobility spectrometer for analyzing probiotics demonstrates one exemplary application.
Paper-based diagnostics are promising for point-of-care testing, but their assembly is often manual and can introduce alignment variability. To address this, we developed a low-cost, open-source workstation that repurposes a three-axis computer numerical control (CNC) machine for automated pick-and-place assembly of paper-based assays. The system integrates an Arduino-based controller with GRBL firmware, a custom vacuum end effector, and component holders to handle delicate assay components. This design eliminates reliance on proprietary CNC controls, reducing the costs to under $900 while enabling machine-agnostic adaptability. Performance was validated across dipstick, lateral flow immunoassay, and custom duplex immunoassay formats. Linear placement accuracy averaged ∼0.5-0.6 mm (within functional tolerance for diagnostic readability), while angular deviations (1-3°) remained acceptable for sample flow. Control line intensity in CNC-assembled assays were statistically indistinguishable from hand-assembled assays, confirming preserved diagnostic performance. By lowering the barrier to automated fabrication, this workstation provides an accessible platform for academic labs, startups, and decentralized environments to prototype and scale paper-based diagnostics. The open-source hardware and design files expand opportunities for reproducible, affordable diagnostic assembly in early-stage research and development.
This work presents the development of a two-part platform designed to evaluate the energy performance of Internet of Things (IoT) devices. The first component is a real-time monitoring system capable of synchronously measuring voltage and current to estimate the energy consumption of IoT nodes during the execution of computationally intensive algorithms. The second component is a battery-powered IoT test node that includes a user interface for configuring the percentage of training data used in a linear regression algorithm (RedWine dataset). Experimental evaluation shows that the monitoring system provides stable and accurate electrical measurements, while the test node enables controlled variation of computational load. Results demonstrate a nearly linear relationship between energy consumption, processing time, and the proportion of training data, with evidence that reduced datasets can achieve comparable model accuracy at significantly lower energy cost. The proposed platform provides a practical tool for analyzing the trade-off between algorithmic performance and resource usage, supporting the design of more energy-efficient IoT systems.
This paper presents an open-source redesign of a three‑phase induction motor for poultry farm ventilation fan applications that targets thermal stability, vibration reduction, and higher efficiency. The motor maintains a rated mechanical output of approximately 2 kW, while increases the stator outer diameter (160 → 190  mm) and shortening the axial core length (190 → 110  mm) to conserve D2L and shorten the thermal path. The rotor/shaft were shortened accordingly to raise stiffness and the critical speed, lowering vibration. Aluminum die-cast endcaps and a finned AL6063-T5 aluminum housing (a high-conductivity alloy commonly used for motor cooling applications) raised the effective heat-transfer area and conductivity relative to cast iron. Rewinding with a larger wire gauge (0.70  mm × 2) halved phase resistance (18.63  Ω → 8.57  Ω), cutting copper loss. Under full load, input power decreased from 3,420 W to 2,632 W, a reduction of approximately 788 W (23%), and the hottest coil fell by up to 24 °C W (∼16.2%), with rear-section vibration reduced by up to 5.5  mm/s. Complete CAD files, bill of materials, and step‑by‑step build/validation instructions were released under the open-source CERN-OHL-S v2 license (a share-alike hardware license that permits reproduction, modification, and redistribution), enabling replication and adaptation. This work offers a practical template for cost‑effective, thermally robust small induction motors.