The power of open-source hardware in crisis

Could open-source solutions provide a crucial layer of defense for the future of pandemic-ready and disaster-resilient supply chains?

Configurable IoT Open-Source Hardware and Software I-V Curve Tracer for Photovoltaic Generators

Photovoltaic (PV) energy is a renewable energy resource which is being widely integrated in intelligent power grids, smart grids, and microgrids. To characterize and monitor the behavior of PV modules, current-voltage (I-V) curves are essential. In this regard, Internet of Things (IoT) technologies provide versatile and powerful tools, constituting a modern trend in the design of sensing and data acquisition systems for I-V curve tracing. This paper presents a novel I-V curve tracer based on IoT open-source hardware and software. Namely, a Raspberry Pi microcomputer composes the hardware level, whilst the applied software comprises mariaDB, Python, and Grafana. All the tasks required for curve tracing are automated: load sweep, data acquisition, data storage, communications, and real-time visualization. Modern and legacy communication protocols are handled for seamless data exchange with a programmable logic controller and a programmable load. The development of the system is expounded, and experimental results are reported to prove the suitability and validity of the proposal. In particular, I-V curve tracing of a monocrystalline PV generator under real operating conditions is successfully conducted.

Accessible, Open-source Hardware and Process Designs for 3D Bioprinting and Culturing Channels Lined with iPSC-derived Vascular Endothelial Cells

Indirect bioprinting for cell culture requires the use of several technologies and techniques which currently prevent many researchers not specialized in electrical engineering or materials science from accessing these new tools. In this paper, a printer and all necessary associated hardware was developed and tested for the purpose of seeding human induced Pluripotent Stem Cell (iPSC)-derived endothelial cells (iECs) onto all surfaces of a fibrin-gelatin channel. Immature iECs were seeded onto all channel surfaces and completed differentiation along channel walls. All required tools and methods, including engineering drawing, printable files, code, and hand-tool templates, have been provided with sufficient clarity to enable full, open-source replication of all technique employed.

An Open-Source Framework for Automated High-Throughput Cell Biology Experiments

Modern data analysis methods, such as optimization algorithms or deep learning have been successfully applied to a number of biotechnological and medical questions. For these methods to be efficient, a large number of high-quality and reproducible experiments needs to be conducted, requiring a high degree of automation. Here, we present an open-source hardware and low-cost framework that allows for automatic high-throughput generation of large amounts of cell biology data. Our design consists of an epifluorescent microscope with automated XY stage for moving a multiwell plate containing cells and a perfusion manifold allowing programmed application of up to eight different solutions. Our system is very flexible and can be adapted easily for individual experimental needs. To demonstrate the utility of the system, we have used it to perform high-throughput Ca2+ imaging and large-scale fluorescent labeling experiments.