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At least 685 records · Page 38

Spinteract: a program to refine magnetic interactions to diffuse scattering data

Magnetic diffuse scattering—the broad magnetic scattering features observed in neutron-diffraction data above a material's magnetic ordering temperature—provides a rich source of information about the material's magnetic Hamiltonian. However, this information has often remained under-utilised due to a lack of available computer software that can fit values of magnetic interaction parameters to such data. Here, an open-source computer program, Spinteract, is presented, which enables straightforward refinement of magnetic interaction parameters to powder and single-crystal magnetic diffuse scattering data. Here, the theory and implementation of this approach are summarised. Examples are presented of refinements to published experimental diffuse-scattering data sets for the canonical antiferromagnet MnO and the highly-frustrated classical spin liquid Gd 3 Ga 5 O 12 . Guidelines for data collection and refinement are outlined, and possible developments of the approach are discussed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Maximized lateral inhibition in paired magnetic domain wall racetracks for neuromorphic computing

Lateral inhibition is an important functionality in neuromorphic computing, modeled after the biological neuron behavior that a firing neuron deactivates its neighbors belonging to the same layer and prevents them from firing. In most neuromorphic hardware platforms lateral inhibition is implemented by external circuitry, thereby decreasing the energy efficiency and increasing the area overhead of such systems. Recently, the domain wall—magnetic tunnel junction (DW-MTJ) artificial neuron is demonstrated in modeling to be intrinsically inhibitory. Without peripheral circuitry, lateral inhibition in DW-MTJ neurons results from magnetostatic interaction between neighboring neuron cells. However, the lateral inhibition mechanism in DW-MTJ neurons has not been studied thoroughly, leading to weak inhibition only in very closely-spaced devices. This work approaches these problems by modeling current- and field- driven DW motion in a pair of adjacent DW-MTJ neurons. We maximize the magnitude of lateral inhibition by tuning the magnetic interaction between the neurons. The results are explained by current-driven DW velocity characteristics in response to an external magnetic field and quantified by an analytical model. Dependence of lateral inhibition strength on device parameters is also studied. Finally, lateral inhibition behavior in an array of 1000 DW-MTJ neurons is demonstrated. Our results provide a guideline for the optimization of lateral inhibition implementation in DW-MTJ neurons. Finally, with strong lateral inhibition achieved, a path towards competitive learning algorithms such as the winner-take-all are made possible on such neuromorphic devices.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Ab Initio modeling of Near-Edge EELS spectra for chemisorbed molecules

Abstract Electron energy loss spectroscopy (EELS) has recently been applied to probe chemisorbed molecules on metal nanostructures, but a fundamental understanding of the correlation between these spectra and the electronic structures of the adsorbates has been limited. We report here on the insights afforded by time-dependent density functional theory to decipher the energy loss near edge structure (ELNES) of EELS spectra associated with chemisorption. These first-principles calculations simulate the ELNES-EELS spectra for chemisorbed CO on various facets of Au and Pt. Computational predictions of key signatures such as the ‘red shift’ and reductions in the peak intensity of the 2 π * and 6 σ * peaks, as compared to free CO in the gas phase, are validated in comparison to experimentally collected EELS spectra. These signatures are revealed to arise from changes in the electronic structure in terms of unoccupied density of states associated with the chemisorption process. They are consistent with a Blyholder model that incorporates donation and back-donation of electrons. They are also characteristic of the chemisorption process, such as the choice of metal, site of adsorption and the coverage and distribution of adsorbates. Our simulations thus provide guidelines for the use of ELNES-EELS to characterize the atomic structure and adsorption property of nanostructured surfaces and facilitate the development of advanced nanomaterials for catalytic applications.

Materials Science↗

Designing polymer coatings for lithium metal protection

Abstract Protection of lithium metal has been one of the great challenges to realize a long-life, high-energy-density battery. Polymer coatings on lithium metal surface have been proven to be an effective protection method in terms of improved morphology, higher coulombic efficiency, and a longer cycle life. However, there is a variety of design principles of polymer coatings proposed by the research community, and the influence of polymer swelling in liquid electrolytes remains poorly understood. Herein we use crosslinking density and solvent–polymer interaction to quantitatively explain the mechanical property and the ion-transport property of polymer coatings when swollen in liquid electrolytes. Low crosslinking density is beneficial for reducing the rigidity and enhancing the viscosity of the polymer. Ion conductivity increases with the swelling ratio, and activation energy of lithium-ion transport increases in a polar polymer with strong ion–polymer coupling. We propose that polymer coatings must be combined with the emerging electrolytes with unconventional solvent compositions to realize a practical high-performance lithium metal battery. This study can provide design guidelines for polymer coatings through the optimized interactions with upcoming high-performance electrolytes.

Materials Science↗

Recent advances of two-dimensional material additives in hybrid perovskite solar cells

Perovskite solar cells (PSCs) have become one of the state-of-the-art photovoltaic technologies due to their facile solution-based fabrication processes combined with extremely high photovoltaic performance originating from excellent optoelectronic properties such as strong light absorption, high charge mobility, long free charge carrier diffusion length, and tunable direct bandgap. However, the poor intrinsic stability of hybrid perovskites under environmental stresses including light, heat, and moisture, which is often associated with high defect density in the perovskite, has limited the large-scale commercialization and deployment of PSCs. The use of process additives, which can be included in various subcomponent layers in the PSC, has been identified as one of the effective approaches that can address these issues and improve the photovoltaic performance. Among various additives that have been explored, two-dimensional (2D) materials have emerged recently due to their unique structures and properties that can enhance the photovoltaic performance and device stability by improving perovskite crystallization, defect passivation, and charge transport. In this work, we provide a review of the recent progresses in 2D material additives for improving the PSC performance based on key representative 2D material systems, including graphene and its derivatives, transitional metal dichalcogenides, and black phosphorous, providing a useful guideline for further exploiting unique nanomaterial additives for more efficient and stable PSCs in the near future.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Analysis and mitigation of parasitic resistance effects for analog in-memory neural network acceleration

To support the increasing demands for efficient deep neural network processing, accelerators based on analog in-memory computation of matrix multiplication have recently gained significant attention for reducing the energy of neural network inference. However, analog processing within memory arrays must contend with the issue of parasitic voltage drops across the metal interconnects, which distort the results of the computation and limit the array size. This work analyzes how parasitic resistance affects the end-to-end inference accuracy of state-of-the-art convolutional neural networks, and comprehensively studies how various design decisions at the device, circuit, architecture, and algorithm levels affect the system's sensitivity to parasitic resistance effects. Here, a set of guidelines are provided for how to design analog accelerator hardware that is intrinsically robust to parasitic resistance, without any explicit compensation or re-training of the network parameters.

97 MATHEMATICS AND COMPUTING↗

Physics and technology considerations for the deuterium–tritium fuel cycle and conditions for tritium fuel self sufficiency

The tritium aspects of the DT fuel cycle embody some of the most challenging feasibility and attractiveness issues in the development of fusion systems. The review and analyses in this paper provide important information to understand and quantify these challenges and to define the phase space of plasma physics and fusion technology parameters and features that must guide a serious R&D in the world fusion program. We focus in particular on components, issues and R&D necessary to satisfy three 'principal requirements': (1) achieving tritium self-sufficiency within the fusion system, (2) providing a tritium inventory for the initial start-up of a fusion facility, and (3) managing the safety and biological hazards of tritium. A primary conclusion is that the physics and technology state-of-the-art will not enable DEMO and future power plants to satisfy these principal requirements. We quantify goals and define specific areas and ideas for physics and technology R&D to meet these requirements. A powerful fuel cycle dynamics model was developed to calculate time-dependent tritium inventories and flow rates in all parts and components of the fuel cycle for different ranges of parameters and physics and technology conditions. Dynamics modeling analyses show that the key parameters affecting tritium inventories, tritium start-up inventory, and tritium self-sufficiency are the tritium burn fraction in the plasma (f b ), fueling efficiency (η f ), processing time of plasma exhaust in the inner fuel cycle (t p ), reactor availability factor (AF), reserve time (tr) which determines the reserve tritium inventory needed in the storage system in order to keep the plant operational for time t r in case of any malfunction of any part of the tritium processing system, and the doubling time (t d ). Results show that η f f b > 2% and processing time of 1–4 h are required to achieve tritium self-sufficiency with reasonable confidence. For η f f b = 2% and processing time of 4 h, the tritium start-up inventory required for a 3 GW fusion reactor is ~11 kg, while it is <5 kg if η f f b = 5% and the processing time is 1 h. To achieve these stringent requirements, a serious R&D program in physics and technology is necessary. The EU-DEMO direct internal recycling concept that carries fuel directly from the plasma exhaust gas to the fueling systems without going through the isotope separation system reduces the overall processing time and tritium inventories and has positive effects on the required tritium breeding ratio (TBR R ). A significant finding is the strong dependence of tritium self-sufficiency on the reactor availability factor. Simulations show that tritium self-sufficiency is: impossible if AF < 10% for any η f f b , possible if AF > 30% and 1% ≤ η f f b ≤ 2%, and achievable with reasonable confidence if AF > 50% and η f f b > 2%. These results are of particular concern in light of the low availability factor predicted for the near-term plasma-based experimental facilities (e.g. FNSF, VNS, CTF), and can have repercussions on tritium economy in DEMO reactors as well, unless significant advancements in RAMI are made. There is a linear dependency between the tritium start-up inventory and the fusion power. The required tritium start-up inventory for a fusion facility of 100 MW fusion power is as small as 1 kg. Since fusion power plants will have large powers for better economics, it is important to maintain a 'reserve' tritium inventory in the tritium storage system to continue to fuel the plasma and avoid plant shutdown in case of malfunctions of some parts of the tritium processing lines. But our results show that a reserve time as short as 24 h leads to unacceptable reserve and start-up inventory requirements. Therefore, high reliability and fast maintainability of all components in the fuel cycle are necessary in order to avoid the need for storing reserve tritium inventory sufficient for continued fusion facility operation for more than a few hours. The physics aspects of plasma fueling, tritium burn fraction, and particle and power exhaust are highly interrelated and complex, and predictions for DEMO and power reactors are highly uncertain because of lack of experiments with burning plasma. Fueling by pellet injection on the high field side of tokamak has evolved to be the preferred method to fuel a burning plasma. Extrapolation from the DIII-D penetration scaling shows fueling efficiency expected in DEMO to be <25%, but such extrapolations are highly uncertain. The fueling efficiency of gas in a reactor relevant regime is expected to be extremely poor and not very useful for getting tritium into the core plasma efficiently. Gas fueling will nonetheless be useful for feedback control of the divertor operating parameters. Extensive modeling has been carried out to predict burn fraction, fueling requirements, and fueling efficiency for ITER, DEMO, and beyond. The fueling rate required to operate Q = 10 ITER plasmas in order to provide the required core fueling, helium exhaust and radiative divertor plasma conditions for acceptable divertor power loads was calculated. If this fueling is performed with a 50–50 DT mix, the tritium burn fraction in ITER would be ~0.36%, which is too low to satisfy the self-sufficiency conditions derived from the dynamics modeling for fusion reactors. Extrapolation to DEMO using this approach would also yield similarly low burn fraction. Extensive analysis presented shows that specific features of edge neutral dynamics in ITER and fusion reactors, which are different from present experiments, open possibilities for optimization of tritium fueling and thus to improve the burn fraction. Using only tritium in pellet fueling of the plasma core, and only deuterium for edge density, divertor power load and ELM control results in significant increase of the burn fraction to 1.8–3.6%. These estimates are performed with physics models whose results cannot be fully validated for ITER and DEMO plasma conditions since these cannot be achieved in present tokamak experiments. Thus, several uncertainties remain regarding particle transport and scenario requirements in ITER and DEMO. The safety standard requirements for protection of the public and release guidelines for tritium have been reviewed. General safety approaches including minimizing tritium inventories, reducing tritium permeation through materials, and decontaminating material for waste disposal have been suggested.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Enhancing predictive capabilities in fusion burning plasmas through surrogate-based optimization in core transport solvers

Abstract This work presents the PORTALS framework (Rodriguez-Fernandez et al 2022 Nucl. Fusion 62 076036), which leverages surrogate modeling and optimization techniques to enable the prediction of core plasma profiles and performance with nonlinear gyrokinetic simulations at significantly reduced cost, with no loss of accuracy. The efficiency of PORTALS is benchmarked against standard methods, and its full potential is demonstrated on a unique, simultaneous 5-channel (electron temperature, ion temperature, electron density, impurity density and angular rotation) prediction of steady-state profiles in a DIII-D ITER Similar Shape plasma with GPU-accelerated, nonlinear CGYRO (Candy et al 2016 J. Comput. Phys. 324 73–93). This paper also provides general guidelines for accurate performance predictions in burning plasmas and the impact of transport modeling in fusion pilot plants studies.

Physics↗

Challenges in Rotor Aerodynamic Modeling for Non-Uniform Inflow Conditions

Within an international collaboration framework, the accuracy of rotor aerodynamic models used for design load calculations of wind turbines is being assessed. Where the use of high-fidelity computation fluid dynamics (CFD) and mid-fidelity free-vortex wake (FVW) models has become commonplace within the wind energy community, these still fail to meet the requirements in terms of execution time and computational cost needed for design load calculations. The fast but engineering fidelity blade-element/momentum (BEM) method can therefore still be considered the industry workhorse for design load simulations. At the same time, upscaling of wind turbine rotors makes inflow non-uniformities (e.g. shear, veer, turbulence) more important. The objective of this work is to assess model accuracy in non-uniform inflow conditions, which violate several BEM assumptions. Thereto a comparison in turbulent inflow has been executed including a wide variety of codes, focusing on the DanAero field measurements, where a 2.3-MW turbine was equipped with, among other sensors, a pressure measurement apparatus. The results indicate that, although average load patterns are in good agreement, this does not hold for the unsteady loads that drive fatigue damage and aero-elastic stability. A simplified comparison round in vertical shear was initiated to investigate the observed differences in a more controlled manner. A consistent offset in load amplitude was observed between CFD and free-vortex codes on the one hand and BEM-type codes on the other hand. To shed more light on the observations, dedicated efforts are ongoing to pinpoint the cause for these differences, in the end leading to guidelines for an improved BEM implementation.

17 WIND ENERGY↗

Maximizing ion dynamics and electrochemical performance of ionic liquid-acetonitrile electrolyte in Ti 3 C 2 T x MXene

Modification of the structure and morphology of MXene electrodes and the formulation of the electrolytes used in their supercapacitor configurations are significant factors affecting the performance of electrochemical devices. In this study, we investigated the electrochemical performance and ion dynamics of 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide, [EmimTFSI], ionic liquid in the presence of acetonitrile (ACN) at different concentrations in Ti 3 C 2 T x MXene supercapacitor. We found an optimum concentration of ACN, at which more cations from the ionic liquid attach to the MXene electrode surface, providing higher electrochemical performance. This higher capacitance is also associated with increased microscopic dynamics of the cation away from the pore wall. These findings give a guideline to optimize the performance of MXene-based supercapacitors using organic solvents-ionic liquid-based electrolyte systems.

36 MATERIALS SCIENCE↗

Impact of hydrogenation on the stability and mechanical properties of amorphous boron nitride

Abstract Interconnect materials with ultralow dielectric constant, and good thermal and mechanical properties are crucial for the further miniaturization of electronic devices. Recently, it has been demonstrated that ultrathin amorphous boron nitride (aBN) films have a very low dielectric constant, high density (above 2.1 g cm −3 ), high thermal stability, and mechanical properties. The excellent properties of aBN derive from the nature and degree of disorder, which can be controlled at fabrication, allowing tuning of the physical properties for desired applications. Here, we report an improvement in the stability and mechanical properties of aBN upon hydrogen doping. With the introduction of a Gaussian approximation potential for atomistic simulations, we investigate the changing morphology of aBN with varying H doping concentrations. We found that for 8 at% of H doping, the concentration ofsp 3 -hybridized atoms reaches to a maximum which leads to an improvement of thermal stability and mechanical properties by 20%. These results will be a guideline for experimentalists and process engineers to tune the growth conditions of aBN films for numerous applications.

Materials Science↗

Roadmap on perovskite light-emitting diodes

Abstract In recent years, the field of metal-halide perovskite emitters has rapidly emerged as a new community in solid-state lighting. Their exceptional optoelectronic properties have contributed to the rapid rise in external quantum efficiencies (EQEs) in perovskite light-emitting diodes (PeLEDs) from <1% (in 2014) to over 30% (in 2023) across a wide range of wavelengths. However, several challenges still hinder their commercialization, including the relatively low EQEs of blue/white devices, limited EQEs in large-area devices, poor device stability, as well as the toxicity of the easily accessible lead components and the solvents used in the synthesis and processing of PeLEDs. This roadmap addresses the current and future challenges in PeLEDs across fundamental and applied research areas, by sharing the community’s perspectives. This work will provide the field with practical guidelines to advance PeLED development and facilitate more rapid commercialization.

14 SOLAR ENERGY↗

Emerging inorganic solar cell efficiency tables (version 2)

Abstract This paper presents the second version of the efficiency tables of materials considered as emerging inorganic absorbers for photovoltaic solar cell technologies. The materials collected in these tables are selected based on their progress in recent years, and their demonstrated potential as future photovoltaic absorbers. The first part of the paper consists of the guidelines for the inclusion of the different technologies in this paper, the verification means used by the authors, and recommendation for measurement best practices. The second part details the highest world-class certified solar cell efficiencies, and the highest non-certified cases (some independently confirmed). The third part highlights the new entries including the record efficiencies, as well as new materials included in this version of the tables. The final part is dedicated to review a specific aspect of materials research that the authors consider of high relevance for the scientific community. In this version of the efficiency tables, we are including an overview of the latest progress in quasi one-dimensional absorbers, such as antimony chalcogenides, for photovoltaic applications.

14 SOLAR ENERGY↗

2022 roadmap on 3D printing for energy

The energy transition is one of the main challenges of our society and therefore a major driver for the scientific community. To ensure a smart transition to a sustainable future energy scenario different technologies such as energy harvesting using solar cells or windmills and chemical storage in batteries, super-capacitors or hydrogen have to be developed and ultimately deployed. New fabrication approaches based on additive manufacturing and the digitalization of the industrial processes increase the potential to achieve highly efficient and smart technologies required to increase the competitiveness of clean energy technologies against fossil fuels. In this frame, the present roadmap highlights the tremendous potential of 3D printing as a new route to fully automate the manufacturing of energy devices designed as digital files. Additionally, this article gives numerous guidelines to maximize the performance and efficiency of the next generation of 3D printed devices for the energy transition while reducing the waste of critical raw materials. In particular, the paper is focused on the current status, present challenges and the expected and required advances of 3D printing for the fabrication of the most relevant energy technologies such as fuel cells and electrolysers, batteries, solar cells, super-capacitors, thermoelectric generators, chemical reactors and turbomachinery.

36 MATERIALS SCIENCE↗

Impacts of benchmarking choices on inferred model skill of the Arctic–Boreal terrestrial carbon cycle

Abstract Land surface models require continuous validation against observations to improve and reduce simulation uncertainty. However, inferred model performance can be heavily influenced by subjective choices made in the selection and application of observational data products. A key area often misrepresented by models is the Arctic–Boreal region, which is a potential tipping point region in Earth’s climate system due to large permafrost carbon stocks that are vulnerable to release with climate warming. We use the International Land Model Benchmarking (ILAMB) framework to evaluate how the model skill of TRENDY-v9 models varies based on the choice of observational-based benchmark and how benchmarks are applied in model evaluation. This analysis uses global datasets integrated into ILAMB and new, regionally-specific observational products from the Arctic–Boreal Vulnerability Experiment. Our results cover the overall time period of 1979–2019 and show that model scores can vary substantially depending on the data product applied, with higher model scores indicating better model performance against observations. The lowest model scores occur when benchmarked against regional, compared to global, datasets. We also evaluate observed and modeled functional relationships between ecosystem respiration and air temperature and between gross primary production and precipitation. Here, we find that the magnitude and shape of the responses are strongly impacted by the choice of observational dataset and the approach used to construct the functional relationship benchmark. These results suggest that model evaluation studies could conclude a false sense of model skill if only using a single benchmark data product or if not applying regional data products when performing a regional model analysis. Collectively, our findings highlight the influence of benchmarking choices on model evaluation and point to the need for benchmarking guidelines when assessing model skill.

Poe, Jeralyn (ORCID:0000000318495278)↗

Biogeochemical Characteristics of Earth's Volcanic Permafrost: An Analog of Extraterrestrial Environments

This article describes a study of frozen volcanic deposits collected from volcanoes Tolbachik and Bezymianny on the Kamchatka Peninsula, Russia, and Deception Island volcano, Antarctica. In addition, we studied suprasnow ash layers deposited after the 2007 eruptions of volcanoes Shiveluch and Bezymianny on Kamchatka. The main objectives were to characterize the presence and survivability of thermophilic microorganisms in perennially frozen volcanic deposits. As opposed to permafrost from the polar regions, viable thermophiles were detected in volcanic permafrost by cultivation, microscopy, and sequencing. In the permafrost of Tolbachik volcano, we observed methane formation by both psychrophilic and thermophilic methanogenic archaea, while at 37°C, methane production was noticeably lower. Thermophilic bacteria isolated from volcanic permafrost from the Deception Island were 99.93% related to Geobacillus stearothermophilus. Furthermore, our data showed biological sulfur reduction to sulfide at 85°C and even at 130°C, where hyperthermophilic archaea of the genus Thermoproteus were registered. Sequences of hyperthermophilic bacteria of the genus Caldicellulosiruptor were discovered in clone libraries from fresh volcanic ash deposited on snow. Microorganisms found in volcanic terrestrial permafrost may serve as a model for the alien inhabitants of Mars, a cryogenic planet with numerous volcanoes. Thermophiles and hyperthermophiles and their metabolic processes represent a guideline for the future exploration missions on Mars.

54 ENVIRONMENTAL SCIENCES↗

Effectiveness of supervised exercise, home-based exercise, or walk advice strategies on walking performance and muscle endurance in patients with intermittent claudication (SUNFIT trial): a randomized clinical trial

Abstract Aims Supervised exercise is a guideline-recommended treatment in intermittent claudication (IC). Hospital-based supervised exercise programmes (SEPs) are underutilized, while home-based structured exercise programmes (HSEPs) have attracted interest. The results from HSEP in IC are inconsistent and may confer no benefit over walk advice (WA) and be less effective than SEP. The aim of the study was to compare the effectiveness of best medical treatment, including Nordic pole WA alone, or WA + SEP or WA + HSEP for patients with IC. Methods and results This three-armed, multicentre randomized clinical trial enrolled patients with IC; all patients received best medical treatment including walking poles and the advice of regular Nordic pole walking (WA). For HSEP and SEP, additional exercise programmes were provided. The primarily investigated hypothesis was a non-inferiority analysis of SEP vs. HSEP regarding the 6-min walk test (6MWT) maximum distance, with a pre-defined non-inferiority margin of 50 m. Supporting outcomes included muscle endurance tests and the walking impairment questionnaire. Outcomes were assessed at baseline, 3, 6, and 12 months by a blinded evaluator. Altogether 166 patients (mean age 72 years; 59% males) were randomized. In HSEP and SEP, 24 and 26% patients, respectively, were fully exercise adherent. All three groups improved pain-free walking distance over time, but there were no significant intergroup differences. The intergroup 6MWT difference between SEP and HSEP from 0 to 12 months was –11.6 m, 95% confidence interval: –36.4 to 13.0 m (i.e. within the pre-specified non-inferiority margin). Conclusion The HSEP was non-inferior to SEP in patients with IC. There were no significant differences observed between the three groups at 1 year. Registration ClinicialTrials.gov: NCT02341716.

Sandberg, Anna (ORCID:0000000258432784)↗

Open Hardware in Science: The Benefits of Open Electronics

Abstract Openly shared low-cost electronic hardware applications, known as open electronics, have sparked a new open-source movement, with much untapped potential to advance scientific research. Initially designed to appeal to electronic hobbyists, open electronics have formed a global “maker” community and are increasingly used in science and industry. In this perspective article, we review the current costs and benefits of open electronics for use in scientific research ranging from the experimental to the theoretical sciences. We discuss how user-made electronic applications can help (I) individual researchers, by increasing the customization, efficiency, and scalability of experiments, while improving data quantity and quality; (II) scientific institutions, by improving access to customizable high-end technologies, sustainability, visibility, and interdisciplinary collaboration potential; and (III) the scientific community, by improving transparency and reproducibility, helping decouple research capacity from funding, increasing innovation, and improving collaboration potential among researchers and the public. We further discuss how current barriers like poor awareness, knowledge access, and time investments can be resolved by increased documentation and collaboration, and provide guidelines for academics to enter this emerging field. We highlight that open electronics are a promising and powerful tool to help scientific research to become more innovative and reproducible and offer a key practical solution to improve democratic access to science.

Oellermann, Michael (ORCID:0000000153926737)↗