Initial Performance Evaluation Research Articles

Prospective life cycle assessment of an electric vehicle equipped with a model magnesium battery

BackgroundConcerns about the sustainability of commercially available batteries have driven the development of post-lithium systems. While previous studies on Magnesium batteries have explored both the potential environmental footprint of battery production and their possible use in stationary applications, their environmental impact in electromobility remains unexplored. This study provides an initial prospective evaluation of the environmental performance of a theoretical Mg–S battery for potential use in electric vehicles (EVs). Utilizing life cycle assessment (LCA) methodology, various scenarios are analyzed and compared to conventional systems. The analysis focuses on potential environmental impacts, including climate change, resource criticality, acidification of the biosphere, and particulate matter emissions.ResultsIn the battery pack level, the Magnesium anode and its respective supply chain have been identified as main drivers of environmental burdens. Additional concerns arise from the uneven geographical distribution of Mg production, which leads to dependency on few producers. In terms of resource criticality, the Mg–S battery could carry significant advantages over benchmark systems. A look into the use-phase via theoretical implementation in an electric vehicle (EV) also suggests that the Magnesium based EV could perform on a comparable level to an LIB EV, also outperforming conventional ICEVs in several impact categories.ConclusionsThis study is based on optimistic assumptions, acknowledging several remaining technical challenges for the Mg battery. Consequently, the results are indicative and carry a significant degree of uncertainty. Nonetheless, they suggest that the Mg–S system shows promising environmental sustainability performance, comparable to other reference systems.

Potential of Hydrogen Internal Combustion Engine for the Decarbonised Passenger Vehicle

CO2 regulations are becoming very stringent due to the goal of reducing greenhouse gases and achieving carbon neutrality. It has already become a common situation that electric vehicles are emerging as eco-friendly power systems rather than vehicles equipped with conventional internal combustion engines and their share in the market is increasing. However, even with an internal combustion engine, CO2 can be drastically reduced if a carbon-free fuel such as hydrogen is used. Raw nitrogen oxides (NOx) emissions can be overcome to a certain level through ultra-lean burn operation, but in order to balance the amount of hydrogen and air in the limited space of the combustion chamber, a drop in the engine’s maximum output should be accepted. Hyundai Motor Company (HMC) also previously developed an engine using hydrogen fuel (), but was unable to progress to mass production. Since then, hybrid technology has become popular, and with the development of hydrogen injection devices, an era has arrived where mass production becomes a possibility. For this reason, studies on internal combustion engines using hydrogen fuel based on existing spark ignition or compression ignition engines are rapidly increasing. In this study, a hydrogen fuel engine was designed and manufactured based on the mass produced gasoline spark ignition engine. CO2 level was confirmed from initial performance evaluation, and it was found that raw NOx levels and maximum power were in a trade-off relationship with each other under the same air-charging system application. In addition, the method to improve maximum engine torque was verified while maintaining the raw NOx level, and the maximum engine power improvement level was confirmed when raw NOx emissions were allowed to increase. Thereby the potential of the carbon-neutral internal combustion engine has been demonstrated.

Construction and initial performance evaluation of a newly developed plant PET system

In plant research, positron emission tomography (PET) is occasionally employed for physiological studies, offering valuable insights. However, the generally high cost of PET systems and their suboptimal design for plant research pose challenges to their application in this field. To address these issues, we have developed a new PET system optimized specifically for plant research. The PET detector ring was positioned vertically to enable measurements of plants in their normal upright position. The developed plant PET system features a transaxial field of view (FOV) of approximately 12 cm and an axial FOV slightly larger than 9 cm, allowing for the imaging of relatively small-sized plants. To facilitate imaging of taller plants, the PET system can expand the axial FOV by changing the subject height using a lab jack, enabling the imaging of taller plant species. The measured spatial resolution at the central FOV was 3.3 mm FWHM, and the sensitivity was 3.7%. The timing resolution was 6.78 ns FWHM with a lower energy threshold set to 350 keV. Phantom images simulating plants were successfully measured using the developed plant PET system. We conclude that the developed plant PET system holds promise for effective plant imaging.

A Flexible System-on-Chip Field-Programmable Gate Array Architecture for Prototyping Experimental Global Navigation Satellite System Receivers

Global navigation satellite system (GNSS) technology is evolving at a rapid pace. The rapid advancement demands rapid prototyping tools to conduct research on new and innovative signals and systems. However, researchers need to deal with the increasing complexity and integration level of GNSS integrated circuits (IC), resulting in limited access to modify or inspect any internal aspect of the receiver. To address these limitations, the authors designed a low-cost System-on-Chip Field-Programmable Gate Array (SoC-FPGA) architecture for prototyping experimental GNSS receivers. The proposed architecture combines the flexibility of software-defined radio (SDR) techniques and the energy efficiency of FPGAs, enabling the development of compact, portable, multi-channel, multi-constellation GNSS receivers for testing novel and non-standard GNSS features with live signals. This paper presents the proposed architecture and design methodology, reviewing the practical application of a spaceborne GNSS receiver and a GNSS rebroadcaster, and introducing the design and initial performance evaluation of a general purpose GNSS receiver serving as a testbed for future research. The receiver is tested, demonstrating the ability of the receiver to acquire and track GNSS signals using static and low Earth orbit (LEO)-scenarios, assessing the observables’ quality and the accuracy of the navigation solutions.

A portable reflected-sunlight spectrometer for CO2 and CH4

Abstract. Mapping the greenhouse gases (GHGs) carbon dioxide (CO2) and methane (CH4) above source regions such as urban areas can deliver insights into the distribution and dynamics of local emission patterns. Here, we present the prototype development and an initial performance evaluation of a portable spectrometer that allows for measuring CO2 and CH4 concentrations integrated along a long (>10 km) horizontal path component through the atmospheric boundary layer above a target region. To this end, the spectrometer is positioned at an elevated site from which it points downward at reflection targets in the region, collecting the reflected sunlight at shallow viewing angles. The path-integrated CO2 and CH4 concentrations are inferred from the absorption fingerprint in the shortwave–infrared (SWIR) spectral range. While mimicking the concept of the stationary California Laboratory for Atmospheric Remote Sensing – Fourier Transform Spectrometer (CLARS-FTS) in Los Angeles, our portable setup requires minimal infrastructure and is straightforward to duplicate and to operate in various locations. For performance evaluation, we deployed the instrument, termed EM27/SCA, side by side with the CLARS-FTS at the Mt. Wilson Observatory (1670 m a.s.l.) above Los Angeles for a 1-month period in April/May 2022. We determined the relative precision of the retrieved slant column densities (SCDs) for urban reflection targets to be 0.36 %–0.55 % for O2, CO2 and CH4, where O2 is relevant for light path estimation. For the partial vertical column (VCD) below instrument level, which is the quantity carrying emission information, the propagated precision errors amount to 0.75 %–2 % for the three gases depending on the distance to the reflection target and solar zenith angle. The comparison to simultaneous CLARS-FTS measurements shows good consistency, but the observed diurnal patterns highlight the need to take light scattering into account to enable detection of emission patterns.

Perceptual learning based on a temporal stimulus enhances visual function in adult amblyopic subjects

Studies have shown that Perceptual Learning (PL) can lead to enhancement of spatial visual functions in amblyopic subjects. Here we aimed to determine whether a simple flickering stimulus can be utilized in PL to enhance temporal function performance and whether enhancement will transfer to spatial functions in amblyopic subjects. Six adult amblyopic and six normally sighted subjects underwent an evaluation of their performance of baseline psychophysics spatial functions (Visual acuity (VA), contrast sensitivity (CS), temporal functions (critical fusion frequency (CFF) test), as well as a static and flickering stereopsis test, and an electrophysiological evaluation (VEP). The subjects then underwent 5 training sessions (on average, a total of 150 min over 2.5 weeks), which included a task similar to the CFF test using the method of constant stimuli. After completing the training sessions, subjects repeated the initial performance evaluation tasks. All amblyopic subjects showed improved temporal visual performance (CFF) in the amblyopic eye (on average, 17%, p << 0.01) following temporal PL. Generalization to spatial, spatio-temporal, and binocular tasks was also found: VA increased by 0.12 logMAR (p = 0.004), CS in backward masking significantly increased (by up to 19%, p = 0.003), and flickering stereopsis increased by 85 arcsec (p = 0.048). These results were further electrophysiologically manifested by an increase in VEP amplitude (by 43%, p = 0.03), increased Signal-to-Noise ratio (SNR) (by 39%, p = 0.024) to levels not different from normally sighted subjects, along with an improvement in inter-ocular delay (by 5.8 ms, p = 0.003). In contrast, no significant effect of training was found in the normally sighted group. These results highlight the potential of PL based on a temporal stimulus to improve the temporal and spatial visual performance in amblyopes. Future work is needed to optimize this method for clinical applications.

Development of a quantitative fluorescence lateral flow immunoassay (LFIA) prototype for point-of-need detection of anti-Müllerian hormone

ObjectiveAnti-Müllerian Hormone (AMH) is a quantitative marker for ovarian reserve and is used to predict response during ovarian stimulation. Streamlining testing to the clinic or even to the physician's office would reduce inconvenience, turnaround time, patient stress and potentially also the total cost of testing, allowing for more frequent monitoring. In this paper, AMH is used as a model biomarker to describe the rational development and optimization of sensitive, quantitative, clinic-based rapid diagnostic tests. Design and MethodsWe developed a one-step lateral-flow europium (III) chelate-based fluorescent immunoassay (LFIA) for the detection of AMH on a portable fluorescent reader, optimizing the capture/detection antibodies, running buffer, and reporter conjugates. ResultsA panel of commercial calibrators was used to develop a standard curve to determine the analytical sensitivity (LOD = 0.41 ng/ml) and the analytical range (0.41–15.6 ng/ml) of the LFIA. Commercial controls were then tested to perform an initial evaluation of the prototype performance and showed a high degree of precision (Control I CV 2.18%; Control II CV 3.61%) and accuracy (Control I recovery 126%; Control II recovery 103%). Conclusions: This initial evaluation suggests that, in future clinical testing, the AMH LFIA will likely have the capability of distinguishing women with low ovarian reserve (<1 ng/ml AMH) from women with normal (1–4 ng/ml AMH) ovarian reserve. Furthermore, the LFIA demonstrated a wide linear range, indicating the assay's applicability to the detection of other health conditions such as PCOS, which requires AMH measurement at higher concentrations (>6 ng/ml).

A novel telementoring platform: initial evaluation of technical skills performance and participant satisfaction

A novel telementoring platform: initial evaluation of technical skills performance and participant satisfaction

The Initial Performance Evaluation of Mixed Multi-Frequency Undifferenced and Uncombined BDS-2/3 Precise Point Positioning under Urban Environmental Conditions

With the full operation of the global BeiDou navigation satellite system (BDS-3), positioning performance can be further enhanced by BDS-3 combined with the regional BeiDou navigation satellite system (BDS-2). However, due to satellite signals being out of lock and the limited visibility of satellites, the traditional multi-frequency BDS-2/3 precise point positioning (PPP) model is unable to maintain great positioning performance under urban environmental conditions. In this study, a mixed multi-frequency undifferenced and uncombined (UDUC) BDS-2/3 PPP model is presented to improve the positioning performance under urban environmental conditions by making full use of B1I, B1C, B2I, B2a, and B3I signals from all visible BDS satellites. In this model, BDS satellites with single-, dual-, triple- and quad-frequency observations all can participate in PPP. The static and kinematic experiments were carried out using the mixed multi-frequency UDUC BDS-2/3 PPP model to fully assess the positioning performance under urban environmental conditions with comparisons to the multi-frequency model. The static experiments indicated that the mixed multi-frequency UDUC BDS-2/3 PPP could continuously achieve decimeter-level positioning accuracy at a cut-off elevation angle of 40°, but part of the BDS-3 PPP would lose resolution due to limited visible satellites. Furthermore, the initial kinematic vehicle experiment showed that mixed multi-frequency UDUC BDS-2/3 PPP had better satellite geometry and more observation redundancy than the traditional multi-frequency model. Compared with the traditional multi-frequency BDS-2/3 model, the positioning accuracy of the mixed multi-frequency model was improved by 51.6, 35.5, and 39.1%, respectively, in east, north, and up directions. The convergence time was shortened by 40%.

Design and evaluation of UKRI-MPW0: An HV-CMOS prototype for high radiation tolerance

High-Voltage CMOS (HV-CMOS) sensors are emerging as a prime candidate for future tracking applications that have extreme requirements on material budget, pixel granularity, time resolution and radiation tolerance. This article presents a new HV-CMOS prototype chip, UKRI-MPW0, aimed at pushing some of the boundaries of these sensors. This HV-CMOS chip implements a novel sensor cross-section which is optimised for backside biasing to unprecedented high voltages. Preliminary measurements have shown the chip is able to withstand high bias voltages (>600V) much beyond the state of the art, thus promising a large improvement in radiation tolerance. The design details and initial performance evaluation are presented in this paper.

The Diversification and Enhancement of an IDS Scheme for the Cybersecurity Needs of Modern Supply Chains

Despite the tremendous socioeconomic importance of supply chains (SCs), security officers and operators are faced with no easy and integrated way for protecting their critical, and interconnected, infrastructures from cyber-attacks. As a result, solutions and methodologies that support the detection of malicious activity on SCs are constantly researched into and proposed. Hence, this work presents the implementation of a low-cost reconfigurable intrusion detection system (IDS), on the edge, that can be easily integrated into SC networks, thereby elevating the featured levels of security. Specifically, the proposed system offers real-time cybersecurity intrusion detection over high-speed networks and services by offloading elements of the security check workloads on dedicated reconfigurable hardware. Our solution uses a novel framework that implements the Aho–Corasick algorithm on the reconfigurable fabric of a multi-processor system-on-chip (MPSoC), which supports parallel matching for multiple network packet patterns. The initial performance evaluation of this proof-of-concept shows that it holds the potential to outperform existing software-based solutions while unburdening SC nodes from demanding cybersecurity check workloads. The proposed system performance and its efficiency were evaluated using a real-life environment in the context of European Union’s Horizon 2020 research and innovation program, i.e., CYRENE.

Endoscopic Coregistered Ultrasound Imaging and Precision Histotripsy: Initial In Vivo Evaluation.

Objective. Initial performance evaluation of a system for simultaneous high-resolution ultrasound imaging and focused mechanical submillimeter histotripsy ablation in rat brains. Impact Statement. This study used a novel combination of high-resolution imaging and histotripsy in an endoscopic form. This would provide neurosurgeons with unprecedented accuracy in targeting and executing nonthermal ablations in minimally invasive surgeries. Introduction. Histotripsy is a safe and effective nonthermal focused ablation technique. However, neurosurgical applications, such as brain tumor ablation, are difficult due to the presence of the skull. Current devices are too large to use in the minimally invasive approaches surgeons prefer. We have developed a combined imaging and histotripsy endoscope to provide neurosurgeons with a new tool for this application. Methods. The histotripsy component had a 10 mm diameter, operating at 6.3 MHz. Affixed within a cutout hole in its center was a 30 MHz ultrasound imaging array. This coregistered pair was used to ablate brain tissue of anesthetized rats while imaging. Histological sections were examined, and qualitative descriptions of ablations and basic shape descriptive statistics were generated. Results. Complete ablations with submillimeter area were produced in seconds, including with a moving device. Ablation progress could be monitored in real time using power Doppler imaging, and B-mode was effective for monitoring post-ablation bleeding. Collateral damage was minimal, with a 100 μm maximum distance of cellular damage from the ablation margin. Conclusion. The results demonstrate a promising hardware suite to enable precision ablations in endoscopic procedures or fundamental preclinical research in histotripsy, neuroscience, and cancer.

An interval evidential reasoning-based dynamic performance evaluation method for complex systems

The performance of complex systems is closely related to its safety and reliability. Grasping the performance of complex systems accurately and timely can help avoid or reduce losses if performance drops. In engineering practice, the monitoring information in interval form can express uncertainty. The upper and lower bounds of monitoring information are easier to obtain than the probability distribution, which can reduce the requirements for information distribution. In this paper, the interval evidential reasoning approach is used to evaluate performance of complex systems. A Monte Carlo simulation-based method for calculating the reliability and weight of evidence is proposed. The initial performance evaluation results are obtained by constructing a nonlinear optimization model. Then the historical performance evaluation information is fully considered to obtain the optimal evaluation results dynamically using a linear weighted update method. An uncertainty quantification method is proposed to quantify the uncertainty of input information and evaluation results. Finally, a case study is carried out for a kind of diesel generator to validate the applicability of the proposed method, and shows that the proposed method can improve the evaluation accuracy.

A new insight to deformability correlation of circulating tumor cells with metastatic behavior by application of a new deformability-based microfluidic chip

Isolation and characterization of circulating tumor cells (CTCs) found in blood samples of cancer patients have been considered as a reliable source for cancer prognosis and diagnosis. A new continuous microfluidic platform has been designed in this investigation for simultaneous capture and characterization of CTCs based on their deformability. The deformability-based chip (D-Chip) consists of two sections of separation and characterization where slanted weirs with a gap of 7 μm were considered. Although sometimes CTCs and leukocytes have the same size, the deformability differs in such a way that can be exploited for enrichment purposes. MCF7 and MDA-MB-231 cell lines were used for the initial evaluation of the D-Chip performance. In the separation section, cancer cells were isolated based on deformability differences with an efficiency of higher than 93% (∼average capturing capacity of 2085 out of 2200 cancer cells ml−1) and with significantly high purity (15–40 WBCs ml−1; ∼5 log depletion of WBCs). Cancer cells were categorized based on the deformability difference in the characterization section. Subsequently, 15 clinical blood samples from breast cancer patients were analyzed by the D-Chip. Suggest 'The chip detected CTCs in all patient samples, processed the blood sample at a high throughput of 5.3 ml/h, and properly categorized CTCs based on deformability differences. Further characterization showed that the highly deformable breast cancer CTCs in our patient samples also showed higher potential of metastasis in support of a broader correlation between deformability of CTCs and metastatic behavior.

Fractional Order PID Design based on Novel Improved Slime Mould Algorithm

This study attempts to maintain the terminal voltage level of an automatic voltage regulator (AVR) and control the speed of a direct current (DC) motor using a fractional order proportional integral derivative (FOPID) controller. The best parameters of the controller have been adjusted using a novel meta-heuristic algorithm called opposition-based hybrid slime mold with simulated annealing algorithm. The proposed algorithm aims to improve the original slime mold algorithm in terms of exploitation and exploration using simulated annealing and opposition-based learning, respectively. A time domain objective function was adopted as performance index to design the FOPID-based AVR and DC motor systems. The initial performance evaluation was carried out using unimodal and multimodal benchmark functions. The results confirmed the superior exploration and exploitation capabilities of the developed algorithm compared to the other state-of-the-art optimization algorithms. The performance of the proposed algorithm has also been assessed through statistical tests, time domain and frequency domain simulations along with robustness and disturbance rejection analyses for both DC motor and AVR systems. The proposed algorithm has shown superior capabilities for the respective systems compared to the other state-of-the-art optimization algorithms used for the same purpose.

Machine Learning Applied to Clinical Laboratory Data in Spain for COVID-19 Outcome Prediction: Model Development and Validation.

BackgroundThe COVID-19 pandemic is probably the greatest health catastrophe of the modern era. Spain’s health care system has been exposed to uncontrollable numbers of patients over a short period, causing the system to collapse. Given that diagnosis is not immediate, and there is no effective treatment for COVID-19, other tools have had to be developed to identify patients at the risk of severe disease complications and thus optimize material and human resources in health care. There are no tools to identify patients who have a worse prognosis than others.ObjectiveThis study aimed to process a sample of electronic health records of patients with COVID-19 in order to develop a machine learning model to predict the severity of infection and mortality from among clinical laboratory parameters. Early patient classification can help optimize material and human resources, and analysis of the most important features of the model could provide more detailed insights into the disease.MethodsAfter an initial performance evaluation based on a comparison with several other well-known methods, the extreme gradient boosting algorithm was selected as the predictive method for this study. In addition, Shapley Additive Explanations was used to analyze the importance of the features of the resulting model.ResultsAfter data preprocessing, 1823 confirmed patients with COVID-19 and 32 predictor features were selected. On bootstrap validation, the extreme gradient boosting classifier yielded a value of 0.97 (95% CI 0.96-0.98) for the area under the receiver operator characteristic curve, 0.86 (95% CI 0.80-0.91) for the area under the precision-recall curve, 0.94 (95% CI 0.92-0.95) for accuracy, 0.77 (95% CI 0.72-0.83) for the F-score, 0.93 (95% CI 0.89-0.98) for sensitivity, and 0.91 (95% CI 0.86-0.96) for specificity. The 4 most relevant features for model prediction were lactate dehydrogenase activity, C-reactive protein levels, neutrophil counts, and urea levels.ConclusionsOur predictive model yielded excellent results in the differentiating among patients who died of COVID-19, primarily from among laboratory parameter values. Analysis of the resulting model identified a set of features with the most significant impact on the prediction, thus relating them to a higher risk of mortality.

Reexamining the Outcome Effect: Are Auditors Penalized for Exercising Professional Skepticism?

Prior research has documented an outcome effect such that appropriately skeptical auditors receive higher performance evaluations when they identify a misstatement than when they do not. In Experiment 1, we find differences in performance evaluations (as identified in prior research and that we empirically confirm) are driven by a positive reaction to auditors who identify a misstatement rather than a negative reaction to auditors who do not. In Experiment 2, we use the evaluation fact pattern from Experiment 1 and find outcome effects do not differentially impact auditors’ subsequent professional skepticism, so long as the auditor is aware of their initial task performance evaluation. Taken together, results from our experiments contradict the consensus inference in prior research that the audit evaluation system inadvertently disincentivizes profession skepticism. Rather, our results suggest the evaluation system not only does not deter professional skepticism, but also is critical in facilitating auditors’ professional skepticism.

Hydrogen negative ion density measurement by laser photodetachment and the effect of H recombination on the walls

A laser photodetachment (LPD) was applied to measure the absolute hydrogen negative ion (H−) density in an RF negative ion source. The ion source has been developed to study a Cs-free ion source utilizing a magnetic filter by permanent magnets to enhance the volume production of H− in the extraction region. Prior to a beam extraction experiment, the laser photodetachment was applied as an initial performance evaluation. The absolute H− densities were obtained by LPD with the variation of the RF power. The H− density reached 1.8×109 cm−3 at an RF power of 5 kW. The comparison with the calculation of a particle balance model showed the discrepancy between the model and the LPD results. The LPD result showed the rapid increase in H− density with respect to the RF power compared to the model. By assuming the wall temperature increase and adjusting the recombination coefficient (γrec) of hydrogen (H) atoms on the walls, the discrepancy could be resolved. The recombination coefficient (γrec) plays an important role in determining the H− density in view of the fact that it can affect both the generation and the destruction processes of H−.

Decoding PPP Corrections From BDS B2b Signals Using a Software-Defined Receiver: An Initial Performance Evaluation

With the rapid development of China's BeiDou Navigation Satellite System (BDS), the application of real-time precise point positioning (RTPPP) based on BDS has become an active research area in the field of Global Navigation Satellite Systems (GNSS). BDS has provided the service of broadcasting RTPPP information. It indicates that BDS has become the second satellite system that provides RTPPP services, following Galileo among the GNSS, but work based on this direction has yet to be explored. Therefore, this paper evaluates the performance of precise point positioning (PPP) service using a software-defined receiver (SDR). An experiment was carried out to verify the feasibility of the SDR. The PPP-B2b signal was processed to obtain PPP service information, including orbit corrections, clock corrections, and differential code bias corrections. The time-varying attributes of these corrections of BDS and GPS are evaluated, and the integrity and stability of the PPP service were analyzed. The results show the PPP-B2b signal can stably provide PPP services for satellites in the Asia-Pacific region, including centimeter to decimeter-level orbit corrections and meter-level clock corrections for BDS satellites. At the same time, PPP services provide decimeter to meter-level orbit correction and meter-level clock correction for GPS satellites. Finally, detection tip for bitstream availability in SDR is proposed. Some content which is not defined in the official document, such as the PPP-B2b frame arrangement, various correction update cycles and the progress of PPP service are discussed.

Microreaction system combining chaotic micromixing with fast mixing and particle growth in liquid-segmented flow for the synthesis of hazardous ionic materials

A microreaction system, which combines chaotic mixing with liquid-segmented flow for the synthesis of hazardous ionic materials, was established. Previous single micro-segmented flow achieved good mixing by increasing the length of the tube via the slow diffusion of the reactants; however, it consumed a long residence time and achieved a low efficiency. Consequently, optimized chaotic micromixing was applied to achieve rapid and excellent initial mixing of the reactants. Thereafter, the optimized chaotic micromixing was combined with the liquid-segmented flow to ensure the homogeneity of particle nucleation/growth while overcoming encrustation challenges. Two tubing coils were employed for the crystal nucleation and growth; they extensively reduced the size of the microreaction system. Additionally, a separation column was designed to achieve on-line recovery of the carrier fluid, followed by on-line separation of the products and waste. Furthermore, the initial performance and design evaluation of the microreaction system were performed. Furthermore, we utilized typical ionic primary explosives, barium-2,4,6-trinitroresorcinate (BaTNR) and lead-2,4,6-trinitroresorcinate styphnate (LTNR), to verify the applicability of the microreaction system. Further, BaTNR and LTNR particles with better crystal morphologies, narrower size distributions, and higher heat release than those of the single micro-segmented flow were prepared to illustrate the advantages of the system. The particle size of BaTNR synthesized by the microreaction system ranged from 5 to 13 ​μm, while the heat release was 168.7 ​J·g−1 greater than that of BaTNR prepared by the micro-segmented flow platform. The particle size of LTNR ranged from 30 to 90 ​μm, while the heat release was 230.1 ​J·g−1 greater than that of LTNR prepared by the micro-segmented flow platform. Conclusively, this study demonstrated the feasibility of an efficient and safe microreaction system for synthesizing hazardous ionic materials.