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In response to the problems of strong specificity, poor universality, and high maintenance difficulty of existing flywheel control software, this paper develops a generalized flywheel control and testing software. By analyzing the problems in the universality, automation, parallelism, and reusability of existing equipment, and adopting the modular design concept, the design is carried out in the mode of hardware generalization to meet the control and testing requirements of various types of flywheel products, improve the universality and testing efficiency of the control software, and verify the accuracy and stability of the control software through experiments.

Suppressing noise in physical systems is of fundamental importance. As quantum computers mature, quantum error correcting codes (QECs) will be adopted in order to suppress errors to any desired level. However in the noisy, intermediate-scale quantum (NISQ) era, the complexity and scale required to adopt even the smallest QEC is prohibitive: a single logical qubit needs to be encoded into many thousands of physical qubits. Here we show that, for the crucial case of estimating expectation values of observables (key to almost all NISQ algorithms) one can indeed achieve an effective exponential suppression. We takenindependently prepared circuit outputs to create a state whose symmetries prevent errors from contributing bias to the expected value. The approach is very well suited for current and near-term quantum devices as it is modular in the main computation and requires only a shallow circuit that bridges thencopies immediately prior to measurement. Using no more than four circuit copies, we confirm error suppression below10−6for circuits consisting of several hundred noisy gates (2-qubit gate error 0.5%) in numerical simulations validating our approach.

Technologies such as batteries, biomaterials and heterogeneous catalysts have functions that are defined by mixtures of molecular and mesoscale components. As yet, this multi-length-scale complexity cannot be fully captured by atomistic simulations, and the design of such materials from first principles is still rare 1 – 5 . Likewise, experimental complexity scales exponentially with the number of variables, restricting most searches to narrow areas of materials space. Robots can assist in experimental searches 6 – 14 but their widespread adoption in materials research is challenging because of the diversity of sample types, operations, instruments and measurements required. Here we use a mobile robot to search for improved photocatalysts for hydrogen production from water 15 . The robot operated autonomously over eight days, performing 688 experiments within a ten-variable experimental space, driven by a batched Bayesian search algorithm 16 – 18 . This autonomous search identified photocatalyst mixtures that were six times more active than the initial formulations, selecting beneficial components and deselecting negative ones. Our strategy uses a dexterous 19 , 20 free-roaming robot 21 – 24 , automating the researcher rather than the instruments. This modular approach could be deployed in conventional laboratories for a range of research problems beyond photocatalysis. A mobile robot autonomously operates analytical instruments in a wet chemistry laboratory, performing a photocatalyst optimization task much faster than a human would be able to.

Multiorgan-on-a-chip (multi-OoC) platforms have great potential to redefine the way in which human health research is conducted. After briefly reviewing the need for comprehensive multiorgan models with a systemic dimension, we highlight scenarios in which multiorgan models are advantageous. We next overview existing multi-OoC platforms, including integrated body-on-a-chip devices and modular approaches involving interconnected organ-specific modules. We highlight how multi-OoC models can provide unique information that is not accessible using single-OoC models. Finally, we discuss remaining challenges for the realization of multi-OoC platforms and their worldwide adoption. We anticipate that multi-OoC technology will metamorphose research in biology and medicine by providing holistic and personalized models for understanding and treating multisystem diseases. Multiorgan-on-a-chip (multi-OoC) devices, by supporting cross-organ communication, allow the study of multiorgan processes and modeling of systemic diseases.Multi-OoC approaches provide new insights that would be lost using single-OoC models.Various coupling configurations have been proposed for building multi-OoC platforms, and these present different levels of user-friendliness.Multi-OoC platforms have the potential to transform medical research by opening new avenues for understanding multiorgan diseases and for developing personalized treatments.To further emulate the complexity of the human system in vivo, key elements of the immune, nervous, and vascular systems are being integrated into multi-OoC models.The next generation of multi-OoCs will incorporate multimodal and real-time readouts in the form of on-chip chemical, physical, and molecular sensors, as well as online multiomic analysis.

Remote sensing research was carried out for a standard-gauge railbus used for passenger transport in the Wielkopolska voivodeship (Poland). Pollution concentrations were measured using a modular device for ecological assessment of moving vehicles - an emission gate. The basic tests were carried out using equipment from the PEMS group. The results from the remote sensing device were compared to them. Taking into account the results, it was concluded that the newly developed device allows for the assessment of pollutant concentrations in a non-invasive way, both for gaseous compounds and solid particles. The presented analyzes indicate that most of the concentrations reached values close to the minimum indications from the PEMS equipment.

Naturally occurring protein switches have been repurposed for the development of biosensors and reporters for cellular and clinical applications 1 . However, the number of such switches is limited, and reengineering them is challenging. Here we show that a general class of protein-based biosensors can be created by inverting the flow of information through de novo designed protein switches in which the binding of a peptide key triggers biological outputs of interest 2 . The designed sensors are modular molecular devices with a closed dark state and an open luminescent state; analyte binding drives the switch from the closed to the open state. Because the sensor is based on the thermodynamic coupling of analyte binding to sensor activation, only one target binding domain is required, which simplifies sensor design and allows direct readout in solution. We create biosensors that can sensitively detect the anti-apoptosis protein BCL-2, the IgG1 Fc domain, the HER2 receptor, and Botulinum neurotoxin B, as well as biosensors for cardiac troponin I and an anti-hepatitis B virus antibody with the high sensitivity required to detect these molecules clinically. Given the need for diagnostic tools to track the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) 3 , we used the approach to design sensors for the SARS-CoV-2 spike protein and antibodies against the membrane and nucleocapsid proteins. The former, which incorporates a de novo designed spike receptor binding domain (RBD) binder 4 , has a limit of detection of 15 pM and a luminescence signal 50-fold higher than the background level. The modularity and sensitivity of the platform should enable the rapid construction of sensors for a wide range of analytes, and highlights the power of de novo protein design to create multi-state protein systems with new and useful functions. A modular de novo designed biosensor platform consisting of a cage and key molecule is developed, and used to create sensors for seven distinct proteins including the spike protein from SARS-CoV-2 and anti-SARS antibodies.

Autonomous laboratories can accelerate discoveries in chemical synthesis, but this requires automated measurements coupled with reliable decision-making 1 , 2 . Most autonomous laboratories involve bespoke automated equipment 3 – 6 , and reaction outcomes are often assessed using a single, hard-wired characterization technique 7 . Any decision-making algorithms 8 must then operate using this narrow range of characterization data 9 , 10 . By contrast, manual experiments tend to draw on a wider range of instruments to characterize reaction products, and decisions are rarely taken based on one measurement alone. Here we show that a synthesis laboratory can be integrated into an autonomous laboratory by using mobile robots 11 – 13 that operate equipment and make decisions in a human-like way. Our modular workflow combines mobile robots, an automated synthesis platform, a liquid chromatography–mass spectrometer and a benchtop nuclear magnetic resonance spectrometer. This allows robots to share existing laboratory equipment with human researchers without monopolizing it or requiring extensive redesign. A heuristic decision-maker processes the orthogonal measurement data, selecting successful reactions to take forward and automatically checking the reproducibility of any screening hits. We exemplify this approach in the three areas of structural diversification chemistry, supramolecular host–guest chemistry and photochemical synthesis. This strategy is particularly suited to exploratory chemistry that can yield multiple potential products, as for supramolecular assemblies, where we also extend the method to an autonomous function assay by evaluating host–guest binding properties. A modular autonomous platform for general exploratory synthetic chemistry uses mobile robots to integrate an automated synthesis platform and two analysis platforms.

In-situ wastewater treatment has gained popularity due to cost and energy savings tailored to water sources and user needs. However, this treatment, particularly through advanced oxidation processes (AOPs), poses ecological risks due to the need for strong oxidizing agents. Here, we present a decoupled oxidation process (DOP) using single-atom copper-modified graphite felt electrodes. This process creates a positive potential difference (ΔE ~ 0.5 V) between spatially isolated oxidants and organics and drives electron transfer-based redox reactions. The approach avoids the drawbacks of conventional AOPs, while being capable of treating various recalcitrant electron-rich organics. A floating water treatment device designed based on the DOP approach can degrade organic molecules in large bodies of water with oxidants stored separately in the device. We demonstrate that over 200 L of contaminated water can be treated with a floating device containing only 40 mL of oxidant (10 mM peroxysulphate). The modular device can be used in tandem structures on demand, maximizing water remediation per unit area. Our result provides a promising, eco-friendly method for in-situ water treatment that is unattainable with existing techniques. In-situ wastewater treatment using advanced oxidation processes poses ecological risks. Here, authors introduce a decoupled oxidation process with single-atom copper-based electrodes. This strategy overcomes drawbacks of AOPs, offering a sustainable and efficient in-situ treatment solution.

The present paper offers a complete standardization plan of assemblies for the helicopter assembly process equipment based on the principle of modular design. The study covers the dire need for standard, common, and efficient assembly systems within the helicopter manufacturing units. By methodical dissection of existing assembly procedures and adoption of a modular approach to design, this paper will actually suggest a standardization platform, which not only decreases the complexity in manufacturing but also maximizes the usage of equipment and optimizes production. The offered scheme includes the use of geometric compatibility matrices, functional decomposition algorithms, and standardized interface protocols specifically tailored to the rotorcraft assembly applications. Validated by experiment in one of the representative helicopter manufacturing plants, an experiment proved to reduce assembly time by 34.2 percent, equipment utilization by 28.6 percent, and the complexity of setup by 42.1 percent over conventional methods. The modular standardization plan is a scalable framework of the current helicopter manufacturing industry so that the modern industries can be reconfigured very quickly according to different types of aircraft with the required precision and quality standards. The findings have proved the saving of considerable cost in terms of reduced capital investment, easy maintenance procedures, and flexibility in the operation of various helicopter platforms.

System scalability is fundamental for large-scale quantum computers (QCs) and is being pursued over a variety of hardware platforms. For QCs based on trapped ions, architectures such as the quantum charge-coupled device (QCCD) are used to scale the number of qubits on a single device. However, the number of ions that can be hosted on a single quantum computing module is limited by the size of the chip being used. Therefore, a modular approach is of critical importance and requires quantum connections between individual modules. Here, we present the demonstration of a quantum matter-link in which ion qubits are transferred between adjacent QC modules. Ion transport between adjacent modules is realised at a rate of 2424 s −1 and with an infidelity associated with ion loss during transport below 7 × 10 −8 . Furthermore, we show that the link does not measurably impact the phase coherence of the qubit. The quantum matter-link constitutes a practical mechanism for the interconnection of QCCD devices. Our work will facilitate the implementation of modular QCs capable of fault-tolerant utility-scale quantum computation. A possible route to scalability of trapped-ion-based quantum computing platforms is to connect multiple modules where ions can be shuttled across different registers. Here, the authors demonstrate fast and low-loss transfer of trapped ions between two microchip modules.