Sidekick: A Low-Cost Open-Source 3D-printed liquid dispensing robot

A low-cost, open-source cylindrical Couette rheometer

Rheology describes the flow of fluids from food and plastics, to coatings, adhesives, and 3D printing inks, and is commonly denoted by viscosity alone as a simplification. While viscometers adequately probe Newtonian (constant) viscosity, most fluids have complex viscosity, requiring tests over multiple shear rates, and transient measurements. As a result, rheometers are typically large, expensive, and require additional infrastructure (e.g., gas lines), rendering them inaccessible for regular use by many individuals, small organizations, and educators. Here, we introduce a low-cost (under USD$200 bill of materials) Open Source Rheometer (OSR), constructed entirely from thermoplastic 3D printed components and off-the-shelf electromechanical components. A sample fluid rests in a cup while a micro stepping motor rotates a tool inside the cup, applying strain-controlled shear flow. A loadcell measures reaction torque exerted on the cup, and viscosity is calculated. To establish the measurement range, the viscosity of four Newtonian samples of 0.1-10 Pa.s were measured with the OSR and compared to benchmark values from a laboratory rheometer, showing under 23% error. Building on this, flow curves of three complex fluids - a microgel (hand sanitizer), foam (Gillette), and biopolymer solution (1% Xanthan Gum) - were measured with a similar error range. Stress relaxation, a transient test, was demonstrated on the biopolymer solution to extract the nonlinear damping function. We finally include detailed exposition of measurement windows, sources of error, and future design suggestions. The OSR cost is ∼1/25th that of commercially available devices with comparable minimum torque (200 µN.m), and provides a fully open-source platform for further innovation in customized rheometry.

ASMI: An automated, low-cost indenter for soft matter

The automated soft matter indenter (ASMI) is a platform for rapidly performing mechanical characterization of samples with elastic moduli in the range 7 kPa to 67 MPa with a sample acquisition time between 1 and 10 min. It is a low-cost system based upon open-source software, a modified mill, and an educational force sensor with a total bill of materials <$500. This system tests batches of up to 96 samples based on a standard well-plate sample holder without requiring any human intervention. Using the ASMI, users can obtain mechanical data in a programmable manner that enables high-throughput workflows, precisely testing time-dependent phenomena, and integration with other processing steps for closed-loop optimization.

The Dawn of a New Pharmaceutical Epoch: Can AI and Robotics Reshape Drug Formulation?

Over the last four decades, pharmaceutical companies' expenditures on research and development have increased 51-fold. During this same time, clinical success rates for new drugs have remained unchanged at about 10 percent, predominantly due to lack of efficacy and/or safety concerns. This persistent problem underscores the need to innovate across the entire drug development process, particularly in drug formulation, which is often deprioritized and under-resourced.

Spin coating on a budget: A 3D-Printed all-mechanical alternative for cost-effective thin-film deposition

Spin coating stands out as the most employed thin-film deposition technique across a variety of scientific fields. Particularly in the past two decades, spin coaters have become increasingly popular due to the emergence of solution-processed semiconductors such as quantum dots and perovskites. However, acquiring commercial spin coaters from reputable suppliers remains a significant financial burden for many laboratories, particularly for smaller research or educational facilities. Prompted by the simple mechanical principles of the device, in this work, we present a 3D-printed analogue that can be printed and assembled in under 10 h and costs less than 5 euros per device. The operating principle is fully mechanical since the rotating motion is induced by gas flow. It does not require any additional components such as DC motors, motor drivers, circuitry or software and thus it can be fully operational off the grid. Additionally, the gas flow generates a purging effect that was found to be rather advantageous for film formation. To prove the effectiveness of this device, we have employed it to fabricate planar thin-film antimony sulfide (Sb2 S3 ) solar cells. The optoelectronic characteristics of solar cells revealed noteworthy improvements, particularly in terms of repeatability, when compared to those fabricated with a commercial spin coater.

Self-Driving Laboratories for Chemistry and Materials Science

Self-driving laboratories (SDLs) promise an accelerated application of the scientific method. Through the automation of experimental workflows, along with autonomous experimental planning, SDLs hold the potential to greatly accelerate research in chemistry and materials discovery. This review provides an in-depth analysis of the state-of-the-art in SDL technology, its applications across various scientific disciplines, and the potential implications for research and industry. This review additionally provides an overview of the enabling technologies for SDLs, including their hardware, software, and integration with laboratory infrastructure. Most importantly, this review explores the diverse range of scientific domains where SDLs have made significant contributions, from drug discovery and materials science to genomics and chemistry. We provide a comprehensive review of existing real-world examples of SDLs, their different levels of automation, and the challenges and limitations associated with each domain.

Automated Purification of DNA Origami with SPRI Beads

DNA origami synthesis is a well-established technique with wide-ranging applications. In most cases, the synthesized origami must be purified to remove excess materials such as DNA oligos and other functional molecules. While several purification techniques are routinely used, all have limitations, and cannot be integrated with robotic systems. Here the use of solid-phase reversible immobilization (SPRI) beads as a scalable, high-throughput, and automatable method to purify DNA origami is demonstrated. Not only can this method remove unreacted oligos and biomolecules with yields comparable to existing methods while maintaining the high structural integrity of the origami, but it can also be integrated into an automated workflow to purify simultaneously large numbers and quantities of samples. It is envisioned that the SPRI beads purification method will improve the scalability of DNA nanostructures synthesis both for research and commercial applications.

Accelerated chemical science with AI

In light of the pressing need for practical materials and molecular solutions to renewable energy and health problems, to name just two examples, one wonders how to accelerate research and development in the chemical sciences, so as to address the time it takes to bring materials from initial discovery to commercialization. Artificial intelligence (AI)-based techniques, in particular, are having a transformative and accelerating impact on many if not most, technological domains. To shed light on these questions, the authors and participants gathered in person for the ASLLA Symposium on the theme of 'Accelerated Chemical Science with AI' at Gangneung, Republic of Korea. We present the findings, ideas, comments, and often contentious opinions expressed during four panel discussions related to the respective general topics: 'Data', 'New applications', 'Machine learning algorithms', and 'Education'. All discussions were recorded, transcribed into text using Open AI's Whisper, and summarized using LG AI Research's EXAONE LLM, followed by revision by all authors. For the broader benefit of current researchers, educators in higher education, and academic bodies such as associations, publishers, librarians, and companies, we provide chemistry-specific recommendations and summarize the resulting conclusions.

Physical Laboratory Automation in Synthetic Biology

Synthetic Biology has overcome many of the early challenges facing the field and is entering a systems era characterized by adoption of Design-Build-Test-Learn (DBTL) approaches. The need for automation and standardization to enable reproducible, scalable, and translatable research has become increasingly accepted in recent years, and many of the hardware and software tools needed to address these challenges are now in place or under development. However, the lack of connectivity between DBTL modules and barriers to access and adoption remain significant challenges to realizing the full potential of lab automation. In this review, we characterize and classify the state of automation in synthetic biology with a focus on the physical automation of experimental workflows. Though fully autonomous scientific discovery is likely a long way off, impressive progress has been made toward automating critical elements of experimentation by combining intelligent hardware and software tools. It is worth questioning whether total automation that removes humans entirely from the loop should be the ultimate goal, and considerations for appropriate automation versus total automation are discussed in this light while emphasizing areas where further development is needed in both contexts.

An open-source smart fraction collector for isocratic preparative liquid chromatography

Preparative liquid chromatography is a technique for separating complex samples or isolating pure compounds from complex extracts. It involves eluting samples through a packed column and selectively collecting or isolating the separated bands in a sequence of fractions. Depending on the column length and the sample complexity, a large number of fractions may be obtained, making fraction collection a laborious and time-consuming process. Manual fraction collection is also tedious, error-prone, less reproducible, and susceptible to contamination. Several commercial and lab-made solutions are available for automated fraction collection, but most systems do not synchronize with the instrument detector and collect fractions at fixed volumes or time intervals. We have assembled a low-cost Arduino-based smart fraction collector that can record the signal from the UV-vis detector of the chromatography instrument and enable the automated selective collection of the targeted bands. The system consists of a robot equipped with position sensors and a 3-way solenoid valve that switches the column effluent between the waste or collection positions. By proper programming, an Arduino board records the detector response and actuates the solenoid valve, the position sensors, and the stepper motors to collect the target chromatographic bands.

Open-source 3-D printable autoinjector: Design, testing, and regulatory limitations

Autoinjectors have become popular modern injectable medical devices used as drug delivery systems. Due to their ease, capability and reliability compared to other conventional injectable medical devices, the market and manufacturing demand for autoinjector devices are increasing rapidly and expected to reach a market of $37.5 billion globally by 2025. Although autoinjectors can offset healthcare treatment costs through self-administered medication, they can be expensive for consumers, which limit their accessibility. This study describes the design and manufacture of a spring-driven and 3-D printed autoinjector to overcome this economic accessibility challenge. The digitally replicable device is released as open-source hardware to enable low-cost distributed manufacturing. The bill of materials and assembly instructions are detailed, and the effectiveness of the autoinjector is tested against the current standard (ISO 11608-1:2022) for needle-based injection systems. The safety and dosing accuracy was tested by measuring the weight of 100% ethyl alcohol expelled from six BD Insulin syringes with varying capacities or needle lengths. A one-way analysis assessed the variability between the dose delivery efficiency of 1mL, 0.5mL, and 0.3mL syringes. Testing indicated that the entire dose was delivered over 97.5% of the time for 1mL and 0.5mL syringes, but the autoinjector's loaded spring force and size exceeded structural limitations of 0.3mL or smaller syringes. Components can be manufactured in about twelve hours using an open-source desktop RepRap-class fused filament 3-D printer. The construction requires two compression springs and 3-D printed parts. The total material cost of CAD$6.83 is less than a tenth of comparable commercial autoinjectors, which makes this approach promising. The autoinjector, however, is a class two medical device and must be approved by regulators. Future work is needed to make distributed manufacturing of such medical devices feasible and reliable to support individuals burdened by healthcare costs.

Platform for Hands-On Remote Labs Based on the ESP32 and NOD-red

Not only in Morocco, throughout the walks of the world covid 19 pandemics has seriously questioned policymakers from different sectors. Think-tank in the educational sector notably higher education addressed by such a wide range of challenges brought about by covid 19. The characteristic concern that educationalists in Moroccan universities have to reconsider in this pandemic period should not be beyond rethinking new pedagogical alternatives including approaches, methods, techniques and didactic materials which can successfully assist practioners of the teaching and learning process to keep up with the current alterations. Practical work (PW) is an indispensable type of teaching in scientific and technical training and meets a real complementary need through real, remote or virtual laboratories. Students can consolidate what they have learnt and develop analytical skills by comparing experimental results with those obtained during the manipulation. In this context, the Laboratory of Engineering Sciences and Energy Management (LASIME) at the Superior School of Technology of Agadir has developed a low-cost platform called LABERSIME installed in the cloud (LMS, IDE) and equipped with an embedded system to drive real laboratory equipment and perform experiments qualitatively more efficient than those in face-to-face mode. The ultimate goal is to stimulate self-learning motivation in students through a creative approach.