Amount Of Injection Research Articles

Injection rate measurements and Machine-Learning based predictions of ECN Spray A-3 piezoelectric injector

This study investigates the impact of parametric conditions on the rate of injection (ROI) and injection quantities of a new piezo-type Engine Combustion Network (ECN) Spray A-3 injector using a combination of experimental and model-based approaches. The experiments were conducted using a Zeuch-based HDA Moehwald injection rate measurement system to obtain ROI data. An artificial neural network (ANN) algorithm was employed to develop a predictive model for ROI data, accurately capturing injection behaviors and ROI patterns under a wide range of conditions. The temporal ROI data were trained using a Bayesian regularization backpropagation model with four input conditions: chamber temperature, chamber pressure, injection pressure, and injection duration. This study examined the influence of these conditions on the transient profiles of the ROI, quasi-steady ROI, injection duration, and total injection mass for both the experimental and predicted results. The model demonstrated good predictions that aligned well with the experimental measurements, indicating a significant increase in the ROI and injection quantities with an increase in injection pressure, while the effects of chamber temperature and pressure were less pronounced. The ANN model used in this study allows for the prediction of various ROI profiles without the need for additional experiments or computational fluid dynamics techniques, and complex physical modeling, thereby substantially reducing the cost and time involved in developing injection control systems for advanced internal combustion engines.

Effect of proppant injection condition on fracture network structure and conductivity

AbstractThe hydraulic fracturing of shale reservoirs is an important topic, and adjusting the fracturing process can enhance fracturing efficiency. To analyze the effect of injection conditions on the fracture network structure and conductivity, numerical simulations and theoretical calculations are carried out based on the construction data, and the variation patterns of the fracture network parameters are determined. During the theory study, a fracture network conductivity model was obtained by combining the fracture network expansion model and the fracture diversion model. Then a numerical model was set up according to the analysis results of monitoring data. The numerical simulation results showed the fracture network structure and proppant distribution under different conditions. Throughout the simulation process, the structural parameters and conductivity of the fracture network can be determined by controlling the injection amount and adjusting the injection method, speed, and sand ratio. Results indicated that the proppant pulse frequency during the injection process was a major factor affecting the structure and conductivity of the fracture network. At the same time, a comparison of the distribution structure of the proppant revealed that although the intermittent injection of the proppant improved the flow channel, the efficiency of fracture utilization can still be improved.

Study on fuel injection stability improvement in marine low-speed dual-fuel engines

Pressure waves within the fuel injection system exert a significant influence on the fuel injection process. This study investigated the impact of pressure waves on injection quantity stability. To quantify the influence of pressure waves on injection quantity stability, the relative standard deviation (RSD) was introduced as a metric. Through computational analysis under various operating conditions, the following results were obtained: when the target rail pressure is constant, the RSD tends to diminish as the injection quantity increases. The elevated RSDs observed during small injection quantities are predominantly attributed to the short power-on period of the solenoid valve. Subsequently, parameter optimization and structural improvements were carried out on the injector to address this problem. The results indicate that optimizing structural parameters alone has a limited effect on reducing RSD. However, by adding a block in the control chamber above the needle to improve the structural layout of the injector, the maximum RSD has been reduced from 21.08% to 4.58% under the action of pressure waves caused by fuel injection, and from 29.24% to 6.67% under the action of given random high-frequency pressure waves. The proposed improvement idea for existing injectors enhances injection stability across the entire operating condition range, thereby improving fuel utilization efficiency.

Controlled engineering of high-purity pseudo-boehmite with large pore volume by aluminum alkoxide hydrolysis: Mechanistic understanding and reforming catalysis

The mechanistic understanding of the pore formation during aluminum alkoxide hydrolysis is of crucial importance for the controlled engineering of large pore volume pseudo-boehmite. The time-dependent structure evolution during n-hexanol-aluminum hydrolysis and the DFT calculations were performed to monitor the changes in the aluminum coordination. The results show that the hydrolysis, oxolation and alcoxolation reactions dominate the pore construction in turn with the continuous addition of water. The aluminum coordination undergoes aggregation from Al tetra-coordinates to Al hexa-coordinates and further stable Al3hexa-coordinates as repeating units for linear growth. The rate and amount of water injection is critical for the retention of at least one OR (R = -C6H13) group, which acts as a directed pore-forming group to promote the large cyclization growth of the Al3hexa-coordinates. Consequently, 1.44 cm3/g pore volume of high-purity pseudo-boehmite was obtained, and the prepared PtSn-Al2O3 catalyst exhibits a > 80 % of toluene selectivity for n-heptane reforming.

Quantifying the Impact of Internal Variability on the CESM2 Control Algorithm for Stratospheric Aerosol Injection

AbstractEarth system models are powerful tools to simulate the climate response to hypothetical climate intervention strategies, such as stratospheric aerosol injection (SAI). Recent simulations of SAI implement a tool from control theory, called a controller, to determine the quantity of aerosol to inject into the stratosphere to reach or maintain specified global temperature targets, such as limiting global warming to 1.5°C above pre‐industrial temperatures. This work explores how internal (unforced) climate variability can impact controller‐determined injection amounts using the Assessing Responses and Impacts of Solar climate intervention on the Earth system with Stratospheric Aerosol Injection (ARISE‐SAI) simulations. Since the ARISE‐SAI controller determines injection amounts by comparing global annual‐mean surface temperature to predetermined temperature targets, internal variability that impacts temperature can impact the total injection amount as well. Using an offline version of the ARISE‐SAI controller and data from Earth system model simulations, we quantify how internal climate variability and volcanic eruptions impact injection amounts. While idealized, this approach allows for the investigation of a large variety of climate states without additional simulations and can be used to attribute controller sensitivities to specific modes of internal variability.

Optimization of surfactant-enhanced injection parameters in Lamadian oilfield

Abstract Optimizing injection fluid parameters is critical for the development of unconventional reservoirs since it is the principal strategy for increasing surfactant recovery in low-permeability reservoirs. This study used numerical simulation methods to objectively investigate the influencing variables under various injected surfactant values, based on the reservoir features of the target block. Additionally, it established the yield relationship corresponding to changes in reservoir pressure. Consequently, a correlation was established between the amount of injection, concentration of surfactant, distance between wells, extreme difference in permeability, and increase in pressure. This led to the determination of appropriate injection parameters for enhancing surfactant permeability. The study’s findings have practical implications for determining the appropriate injection scale of a reservoir surfactant system.

Percutaneous pedicle screw anchored vertebral augmentation for the treatment of Kümmell disease without neurological symptoms

To explore the clinical effect of percutaneous pedicle screw anchored vertebral augmentation(PPSAVA) in the treatment of asymptomatic Kümmell disease without neurological symptoms. The clinical data of 20 patients with Kümmell disease without neurological symptoms treated with PPSAVA in our hospital from January 2019 to December 2021 were analyzed retrospectively, including 5 males and 15 females, aged 56 to 88 (74.95±9.93) years old. and the course of disease was 7 to 60 days with an average of (21.35±14.46) days. All patients were treated with PPSAVA. The time of operation, the amount of bone cement injected and the leakage of bone cement were recorded. The visual analogue scale(VAS), Oswestry disability index(ODI), vertebral body angle(VBA), anterior edge height and midline height of vertebral body were compared among the before operation, 3 days after operation and during the final follow-up. The loosening and displacement of bone cement were observed during the final follow-up. All the 20 patients completed the operation successfully. The operation time was 30 to 56 min with an average of (41.15±7.65) min, and the amount of bone cement injection was 6.0 to 12.0 ml with an average of (9.30±1.49) ml. Bone cement leakage occurred in 6 cases and there were no obvious clinical symptoms. The follow-up time was 6 to 12 months with an average of (8.43±2.82) months. The VBA, anterior edge height and midline height of of injured vertebral body were significantly improved 3 days after operation and the final follow-up(P<0.05), and the VBA, anterior edge height and midline height of of injured vertebral body were lost in different degrees at the final follow-up (P<0.05). The VAS and ODI at 3 days after operation and at the final follow-up were significantly lower than those at preoperatively(P<0.05), but the VAS score and ODI at the final follow-up were not significantly different from those at 3 d after operation(P>0.05). At the last follow-up, no patients showed loosening or displacement of bone cement. PPSAVA is highly effective in treating Kümmell disease without neurological symptoms, improving patients' pain and functional impairment, and reducing the risk of cement loosening and displacement postoperatively.

Study on the Influencing Factors of Injection Blockage during CO2 Sequestration in One-Dimensional Long Reactor

Carbon sequestration through CO2 injection into a formation is an effective strategy for reducing greenhouse gas emissions. In this study, a one-dimensional long reactor was constructed to simulate the CO2 injection process under various sediment temperatures, pressures, and flow rates. The formation of CO2 hydrate and the resulting blockages were investigated in detail through a series of indoor experiments. Due to the increasing driving force for CO2 hydrate formation, reducing sediment temperature and increasing sediment pressure can cause hydrate blockage to form near the injection end, leading to an increase in CO2 injection pressure and a reduction in the storage range. Furthermore, CO2 injection rate has a substantial impact on the pattern of hydrate blockage. A lower injection rate facilitates full contact between CO2 gas and pore water, which helps to increase the formation and blockage degree of CO2 hydrates, thereby decreasing the amount of CO2 injection. The experimental investigation presented in this paper examines the laws of CO2 injection and clogging under various sediment conditions and injection processes on a one-dimensional scale, which can provide valuable insights for the design of CO2 sequestration processes.

Optimizing Fuel Injection Timing for Multiple Injection Using Reinforcement Learning and Functional Mock-up Unit for a Small-bore Diesel Engine

&lt;div&gt;Reinforcement learning (RL) is a computational approach to understanding and automating goal-directed learning and decision-making. The difference from other computational approaches is the emphasis on learning by an agent from direct interaction with its environment to achieve long-term goals [&lt;span&gt;1&lt;/span&gt;]. In this work, the RL algorithm was implemented using Python. This then enables the RL algorithm to make decisions to optimize the output from the system and provide real-time adaptation to changes and their retention for future usage. A diesel engine is a complex system where a RL algorithm can address the NO&lt;sub&gt;x&lt;/sub&gt;–soot emissions trade-off by controlling fuel injection quantity and timing. This study used RL to optimize the fuel injection timing to get a better NO–soot trade-off for a common rail diesel engine. The diesel engine utilizes a pilot–main and a pilot–main–post-fuel injection strategy. Change of fuel injection quantity was not attempted in this study as the main objective was to demonstrate the use of RL algorithms while maintaining a constant indicated mean effective pressure. A change in fuel quantity has a larger influence on the indicated mean effective pressure than a change in fuel injection timing. The focus of this work was to present a novel methodology of using the 3D combustion data from analysis software in the form of a functional mock-up unit (FMU) and showcasing the implementation of a RL algorithm in Python language to interact with the FMU to reduce the NO and soot emissions by suggesting changes to the main injection timing in a pilot–main and pilot–main–post-injection strategy. RL algorithms identified the operating injection strategy, i.e., main injection timing for a pilot–main and pilot–main–post-injection strategy, reducing NO emissions from 38% to 56% and soot emissions from 10% to 90% for a range of fuel injection strategies.&lt;/div&gt;

Numerical simulation of enhanced gas recovery from methane hydrate using the heat of CO2 hydrate formation under specific geological conditions

Methane hydrate (MH) is found under the seabed in Japan's exclusive economic zone and is attracting attention as a domestic natural gas resource. One of the methods for extracting methane gas (MG) from sub-seabed MH reservoir is depressurisation. However, the production decelerates after a certain time partly due to the cooling of the reservoir caused by the heat absorption during MH dissociation. Therefore, several enhanced gas recovery (EGR) methods have been proposed, such as injecting CO2 into a sub-seabed sand layer to form CO2 hydrate (CDH) and, using the heat of CDH formation. This method is two functions: EGR and the reduction of greenhouse gas emission. In this study, a numerical method was developed to investigate the performance of the EGR from MH, using the heat of CDH formation. In our previous study, CDH formation model had been installed into a programme code for two-phase flow of CO2 and water in porous media. Based on this code, we newly implemented the state equation, enthalpy model, viscosity model, and heat conduction model of MG and the dissociation model of MH. Then, simulations were performed to form CDH in specific sand-mud alternate layers and to dissociate MH. As a result, it was suggested that increasing the CO2 injection amount potentially increases MH dissociation and the vertical distance between the mud layer capping the injected liquid CO2 and the bottom-simulating reflector of CDH is important to ensure a large CDH region to generate a large amount of heat. It was also shown that even after stopping CO2 injection, MH dissociation can continue for a certain period.

Experimental investigation on in-cylinder working process and thermal efficiency of ammonia/diesel low-carbon engine with pre-injection strategy

Ammonia, as a zero carbon and sustainable fuel, combined with traditional diesel fuel can provide a promising solution for reducing the engine environmental impact. However, ammonia/diesel dual-fuel (ADDF) engine has the significant drawback of low combustion efficiency and poor combustion stability at low loads, which seriously hinders its development. Therefore, this study explored the potential of pre-injection strategy in improving the performance of ADDF engine, comprehensively evaluating the effects of four pre-injection parameters (main injection timing (MIT), pre-injection timing (PIT), pre-injection quantity (PIQ), and diesel injection pressure (DIT)) on in-cylinder combustion process, incomplete combustion emissions, and energy efficiency. The results indicate that MIT has the most significant impact on combustion process. Advancing MIT can significantly increase in-cylinder combustion pressure and reduce CO, HC and unburned NH3 emissions. At MIT = -12 °CA ATDC, the highest brake thermal efficiency (BTE) of 32.3 % is obtained, while simultaneously generating high combustion noise. The advance of PIT has adverse effects on combustion stability. When PIT is advanced from −24 °CA ATDC to −36 °CA ATDC, COVIMEP increases from 2.61 % to 4.44 %, unburned NH3 emission increases by 23.5 %, and the BTE of ADDF engine decreases. Adjusting the PIQ and DIP can improve the reactivity distribution of fuel and reduce incomplete combustion emissions. However, the decrease in main injection quantity would increase the cycle fluctuation. At low loads, shortening the pre-main injection interval and increasing PIQ and DIP can enable the engine to achieve higher BTE while reducing pollutant emissions. This study elucidates in detail the influence of four pre-injection parameters on the operation characteristics of ADDF engine. It can offer insights and practical references for expanding the operating range of ammonia fuel engine.

High-pressure liquid refrigerant injection for reciprocating compressors

Isentropic (adiabatic) compression of superheated vapor in vapor compression refrigeration cycles usually results in some discharge superheat, i.e. the discharge temperature exceeding the condensing temperature. Large discharge superheat reduces both operating range and compression efficiency. Sub-isentropic compression with heat rejection to the heat sink is therefore superior to adiabatic compression, as it results in lower discharge superheat and improved efficiency. However, significant temperature reduction by heat transfer through the working chamber walls is difficult to facilitate in common refrigeration compressors, particularly reciprocating compressors. Refrigerant and oil injection is a well-established method for reducing temperatures and increasing efficiency in screw and scroll compressors, as well as multi-stage systems. In comparison, effective methods for temperature reduction in single-stage reciprocating compressors are fairly limited. Therefore, a concept for high-pressure liquid injection is proposed. By means of a pump and injection valve, high-pressure liquid refrigerant is injected into the working chamber and atomized. The compressed gas is cooled through the evaporation of the injected liquid. The injection valve allows for control over the injection timing and quantity, enabling adjustment of the temperature profile, which is a major distinction from existing refrigerant injection methods. The coupled compression-injection process is evaluated for various refrigerants using an energetic chamber model. The injection is found to be particularly suitable for refrigerants with a large evaporation heat and a shallow dew line slope. For the example of ammonia, a theoretical reduction in compression work of 8.9% at an evaporation temperature of −10 °C and a condensing temperature of 45 °C is found.

Time-dependent model for two-phase flow in ultra-high water-cut reservoirs: Time-varying permeability and relative permeability

For the ultra-high water-cut reservoirs, after long-term water injection exploitation, the physical properties of the reservoir change and the heterogeneity of the reservoir becomes increasingly severe, which further aggravates the spatial difference of the flow field. In this study, the displacement experiments were employed to investigate the variations in core permeability, porosity, and relative permeability after a large amount of water injection. A relative permeability endpoint model was proposed by utilizing the alternating conditional expectation (ACE) transformation to describe the variation in relative permeability based on the experimental data. Based on the time dependent models for permeability and relative permeability, the traditional oil-water two-phase model was improved and discretized using the mimetic finite difference method (MFD). The two cases were launched to confirm the validation of the proposed model. The impact of time-varying physical features on reservoir production performance was studied in a real water flooding reservoir. The experimental results indicate that the overall relative permeability curve shifts to the right as water injection increases. This shift corresponds to a transition towards a more hydrophilic wettability and a decrease in residual oil saturation. The endpoint model demonstrates excellent accuracy and can be applied to time-varying simulations of reservoir physics. The impact of variations in permeability and relative permeability on the reservoir production performance yields two distinct outcomes. The time-varying permeability of the reservoir results in intensified water channeling and poor development effects. On the other hand, the time-varying relative permeability enhances the oil phase seepage capacity, facilitating oil displacement. The comprehensive time-varying behavior is the result of the combined influence of these two parameters, which closely resemble the actual conditions observed in oil field exploitation. The time-varying simulation technique of reservoir physical properties proposed in this paper can continuously and stably characterize the dynamic changes of reservoir physical properties during water drive development. This approach ensures the reliability of the simulation results regarding residual oil distribution.

Radiopharmaceutical transport in solid tumors via a 3-dimensional image-based spatiotemporal model

Lutetium-177 prostate-specific membrane antigen (177Lu-PSMA)-targeted radiopharmaceutical therapy is a clinically approved treatment for patients with metastatic castration-resistant prostate cancer (mCRPC). Even though common practice reluctantly follows “one size fits all” approach, medical community believes there is significant room for deeper understanding and personalization of radiopharmaceutical therapies. To pursue this aim, we present a 3-dimensional spatiotemporal radiopharmaceutical delivery model based on clinical imaging data to simulate pharmacokinetic of 177Lu-PSMA within the prostate tumors. The model includes interstitial flow, radiopharmaceutical transport in tissues, receptor cycles, association/dissociation with ligands, synthesis of PSMA receptors, receptor recycling, internalization of radiopharmaceuticals, and degradation of receptors and drugs. The model was studied for a range of values for injection amount (100–1000 nmol), receptor density (10–500 nmol•l–1), and recycling rate of receptors (10–4 to 10–1 min–1). Furthermore, injection type, different convection-diffusion-reaction mechanisms, characteristic time scales, and length scales are discussed. The study found that increasing receptor density, ligand amount, and labeled ligands improved radiopharmaceutical uptake in the tumor. A high receptor recycling rate (0.1 min–1) increased radiopharmaceutical concentration by promoting repeated binding to tumor cell receptors. Continuous infusion results in higher radiopharmaceutical concentrations within tumors compared to bolus administration. These insights are crucial for advancing targeted therapy for prostate cancer by understanding the mechanism of radiopharmaceutical distribution in tumors. Furthermore, measures of characteristic length and advection time scale were computed. The presented spatiotemporal tumor transport model can analyze different physiological parameters affecting 177Lu-PSMA delivery.

Multi-injection downdraft moving bed reactor for hydrolysis in thermochemical hydrogen production

This paper investigates a downdraft multi-injection moving bed reactor (MBR) for the hydrolysis reaction in the copper-chlorine (Cu–Cl) thermochemical cycle for hydrogen production. The numerical modelling is conducted for a variety of system configurations of the MBR, with a focus on reducing the energy requirement of the reactor while achieving high conversion rates. Several design variables are investigated, including reactor volume, injection point location, and quantity of steam injection. The numerical predictions show an approximate 23% increase in CuCl2 conversion for the multi-injection MBR compared to a single injection design. A maximum conversion of 66.5% is predicted through design parameter variations. Asymptotic behavior for the quantity of injection locations with respect to conversion extent is presented for several different steam to copper ratios. The results and new insights in this paper suggest opportunities for conversion improvement and steam to copper ratio reduction in the hydrolysis reactor through the MBR design.

Numerical characterization of acid fracture wall etching morphology and experimental investigation on sensitivity factors in carbonate reservoirs

Carbonate reservoirs are marked by their low porosity and permeability, naturally occurring fractures that develop in a stochastic fashion and exhibit significant heterogeneity. Deep acidification techniques are essential for the efficient development of such oil and gas reservoirs. The effective distance of acid etching (acid etch fracture length) and the fracture conductivity stand as the two most critical parameters for assessing the efficacy of acidizing. The primary objective of using this technique is to extend the effective distance of the acid etch and enhance the fracture conductivity. The "relay-style" full-length acid etched fracture testing method is employed, achieving an accurate match between the testing temperature, pressure, fracture length, and the actual acid fracturing conditions. It employs a large-scale rock plate acid etching experimental device, in conjunction with 3D laser scanning technology, and utilizes orthogonal experimental design methods to conduct detailed numerical characterization of the rock plate fracture surfaces before and after etching with various acid fluid types, acid injection amounts, and acid injection rates. It quantifies the change in the concentration of the residual acid fluid after the acid-rock reaction, calculating the etching volume of the acid fluid and the length of the acidizing fracture. The experimental results demonstrate that both the gelled acid and the clean diverting acid exhibit long acidification distances and strong inhomogeneous etching capabilities. The etch morphology of the clean diverting acid is dominated by pitting-type and stripe-like dissociation, exhibiting a wavy pattern. In contrast, the etch morphology of the gelled acid appears band-like and groove-like. As the acid injection amount increases, the etch length increases. Under on-site working conditions, etch lengths of 46.42 m and 41.63 m were recorded for 20% gelled acid and clean diverting acid, respectively, after 60 min acid injection time. The factors affecting the etch length sensitivity are in the following order: acid injection rate > acid type > etching time. The optimal acid fracturing parameters to achieve the maximum etch length are: The etch is performed at a pump rate of 600 mL/min for 90 min using gelled acid. Quantitative characterization of acid etch fracture morphology can optimize designing parameters of acid fracturing techniques, enhance the efficiency of their modification, and further enhance the development benefits of oil and gas carbonate rock reservoirs.

Development and Validation of a New High-Performance Liquid Chromatography-Ultraviolet Assay for Quantification of Mitoxantrone in Plasma of BALB/c-nu Mice.

The concentration of mitoxantrone in the blood of mice was determined by a high-performance liquid chromatography-ultraviolet method with aloe-emodin as the internal standard. The separation was performed on a Hypersil BDS2 column (4.6 × 250mm, 5μm) as the analytical column, the mobile Phase A was acetonitrile, and B was 20-mM potassium dihydrogen phosphate (adding 1% triethylamine and adjusting the pH to 2.8 with phosphoric acid) and 4.6-mM sodium octyl sulfonate. The flow rate was 1.0mL·min-1, the detection wavelength was 243nm, the column temperature is 25 ± 5°C and the injection amount was 20μL. Finally, the linear range of mitoxantrone was 5-200μg·mL-1, and the correlation coefficient was r = 0.9999. The recovery rate of the method was 91.93-105.5%, and the extraction recovery rate was 91.45-105.5%. The intraday precision and interday precision were <3.29% (limit of detection = 0.3μg·mL-1). The HPLC method established in this paper was simple, rapid, sensitive and accurate, and can be used to determine the content of mitoxantrone in mouse plasma after tail vein injection.

Reversible charge injection in artificially created charged domain wall region

The impact of electric field application in the charged domain wall (DW) region on the performance of DW devices remains elusive. Here, we present our observations of substantial charge injection occurring in an artificially created charged DW region. Rapid charge injection coincides with polarization switching, contributing to the transient current collected for the integration of polarization-voltage hysteresis loops. Subsequently, a gradual injection of charges persists under externally applied voltages, diffusing into the thin film from the DW region to screen the space defect dipoles and effectively suppressing the imprint field. The process of charge injection proves reversible and is notably more pronounced in aged ferroelectric thin films, as evidenced in planar BiFeO3 nanodevices where the charge injection amount is five orders of magnitude higher than charges generated from polarization switching. This work constitutes a significant contribution to understanding the intricate process of charge injection and its influence on charged DW.

One-dimensional General Relativistic Particle-in-cell Simulations of Stellar-mass Black Hole Magnetospheres: A Semianalytic Model of Gamma-Rays from Gaps

In the absence of a sufficient amount of plasma injection into the black hole (BH) magnetosphere, the force-free state of the magnetosphere cannot be maintained, leading to the emergence of strong, time-dependent, longitudinal electric fields (i.e., spark gaps). Recent studies of supermassive BH magnetospheres using analytical methods and particle-in-cell (PIC) simulations propose the possibility of efficient particle acceleration and consequent gamma-ray emission in the spark gap. In this work, we perform 1D general relativistic PIC simulations to examine the gamma-ray emission from stellar-mass BH magnetospheres. We find that intermittent spark gaps emerge and particles are efficiently accelerated in a similar manner to the supermassive BH case. We build a semianalytic model of the plasma dynamics and radiative processes, which reproduces the maximum electron energies and peak gamma-ray luminosities of the simulation results. Based on this model, we show that the gamma-ray signals from stellar-mass BHs wandering through the interstellar medium could be detected by gamma-ray telescopes such as the Fermi Large Area Telescope or the Cherenkov Telescope Array.

Development of an Untargeted LC-MS Metabolomics Method with Postcolumn Infusion for Matrix Effect Monitoring in Plasma and Feces.

Untargeted metabolomics based on reverse phase LC-MS (RPLC-MS) plays a crucial role in biomarker discovery across physiological and disease states. Standardizing the development process of untargeted methods requires paying attention to critical factors that are under discussed or easily overlooked, such as injection parameters, performance assessment, and matrix effect evaluation. In this study, we developed an untargeted metabolomics method for plasma and fecal samples with the optimization and evaluation of these factors. Our results showed that optimizing the reconstitution solvent and sample injection amount was critical for achieving the balance between metabolites coverage and signal linearity. Method validation with representative stable isotopically labeled standards (SILs) provided insights into the analytical performance evaluation of our method. To tackle the issue of the matrix effect, we implemented a postcolumn infusion (PCI) approach to monitor the overall absolute matrix effect (AME) and relative matrix effect (RME). The monitoring revealed distinct AME and RME profiles in plasma and feces. Comparing RME data obtained for SILs through postextraction spiking with those monitored using PCI compounds demonstrated the comparability of these two methods for RME assessment. Therefore, we applied the PCI approach to predict the RME of 305 target compounds covered in our in-house library and found that targets detected in the negative polarity were more vulnerable to the RME, regardless of the sample matrix. Given the value of this PCI approach in identifying the strengths and weaknesses of our method in terms of the matrix effect, we recommend implementing a PCI approach during method development and applying it routinely in untargeted metabolomics.