Optimal Parameters Research Articles

Microstructures and mechanical properties of pure copper manufactured by high-strength laser powder bed fusion

Pure copper is widely used in motor windings, heat exchangers and aerospace engines because of its high electrical and thermal conductivity. High-strength laser powder bed fusion (HS-LPBF) not only allows rapid production of components with complex geometry and high spatial resolution, but also offers various advantages such as small focal spot diameter, fine powder, and small layer thickness, providing advantages for forming complex structural parts in fields such as engines and heat exchangers. A single factor single layer experiment was performed by varying the hatch spacing (H), and the range of hatch spacing was determined according to the overlap rate. The degree of influence of process parameters on the relative density of pure copper specimens was analyzed using an orthogonal experiment, and a comparative study of the phase composition, microstructure and mechanical properties of pure copper specimens was carried out by varying the laser power. The characteristics of pure copper formed by HS-LPBF were analyzed. In addition, the effect of heat treatment on the microstructure and mechanical properties of pure copper specimens was investigated, and the fracture morphology of the specimens was observed comparatively. The results show that the HS-LPBF technique can effectively increase the energy density and improve the specific surface area of the powder and the laser absorptivity due to its small focal spot diameter, fine powder and layer thickness, thus reducing the minimum energy required to melt pure copper powder. The optimum process parameters were obtained by orthogonal experiment with a relative density of 98.1 % of the specimen. The highest hardness, ultimate tensile strength and elongation were obtained at a laser power of 260 W with 84 HV, 320 MPa and 17.8 %, respectively. This ultimate tensile strength is 18 % higher than the highest ultimate tensile strength that has been reported so far. In addition, the average grain size of the optimal specimens was 3.6 µm. Mechanical properties such as hardness, tensile strength and elongation of pure copper parts can be significantly improved by precisely controlling the process parameters, in particular laser power and hatch spacing.

Optimization of Printing Parameters of PLA and ABS Produced by FFF

In this study, the changes in tensile strength of PLA and ABS specimens, the most commonly used materials in additive manufacturing with FFF, were investigated as a function of fill rate and print speed. Tensile specimens were fabricated for different fill rates and speeds and tensile tests were performed. Increasing the fill rate increases the tensile strength. Increasing or decreasing the print speed too much has a negative effect on tensile strength. Filament usage and printing times were also calculated. With the data obtained, an optimization model was created using response surface methodology. The aim of this study is to optimize the strength/cost of ABS and PLA, the two preferred FFF materials. The novelty of the study is to investigate the strength/cost optimization for different material types in terms of UTS, filament consumption and printing speed. For each material type, high tensile strength, low printing time and low filament used conditions were determined for the optimization model. The optimum parameters for PLA are obtained at 66.77% fill level and 78.43% speed rate. For ABS, optimum values are obtained at 79.5% fill rate and 135% speed rate. Then, samples were produced for optimum conditions and experiments and calculations were repeated. The numerical results obtained with the model were compared with the experimental results. It is found that the model estimates the output parameters with high accuracy. This proves the accuracy of the proposed optimization model.

Preparation and performance study of P(BMA-SMA-st)/MIL-101(Fe) composite resin

In this study, composite resin (P(BMA-SMA-St)/MIL-101(Fe)) was successfully fabricated through suspension polymerization to enhance the absorption efficiency of oil-absorbing resin. Butyl methacrylate (BMA), octadecyl methacrylate (SMA), and styrene (St) were used as oil-absorbing monomers, with benzoyl peroxide (BPO) as the initiator and ethyl acetate (EAC) as the pore-causing agent. By using methods such as infrared spectroscopy (FTIR), electron microscopy (SEM), and scanning thermogravimetric analysis (TGA), the oil-absorbing resin structure was characterized. Simultaneously, the composite resin’s oil retention, oil absorption rate, recycling capabilities, and oil–water separation properties were also investigated, and the optimum synthesis parameters were determined. The experimental results indicate that the composite resin exhibits optimal oil absorption performance when metal-organic framework (MIL-101(Fe)) is at 0.069 wt%, divinylbenzene (DVB) is at 1.4 wt%, BPO is at 1.6 wt%, and EAC is at 50 wt%. P(BMA-SMA-St)/MIL-101(Fe) composite resin can absorb carbon tetrachloride up to 39.01 times its weight, 33.97 times for toluene, 35.69 times for chloroform, 14.82 times for kerosene, 13.57 times for gasoline and 17.81 times for diesel oil. Moreover, the exceptional oil absorption of P(BMA-SMA-St)/MIL-101(Fe) enables the oil retention rate to keep above 90%, speedy removal of oil slicks from the water surface as well, and maintains excellent oil–water separation even after repeated use.

Multi-Objective Optimization of MEMS-based Box Pattern Microheaters Using Response Surface Method

We present a response surface method to evaluate multi-objective optimization for MEMS-based microheater design. Box pattern, the standard microheater shape, was selected in this study since it has a uniform temperature distribution compared to other patterns. The optimum parameters are used to obtain the maximum total current density and Joule heat. Based on a hybrid of the Response Surface Method and Central Composited Design, the model simulation emerged with 25 sets of Design Experiments. As expected, the voltage is proportional to the increased output temperature and Joule heat of the microheater. Material thermal conductivity, anchor length and thickness of the heating element are included as design variables for the optimization. The microheater thicknesses of 4.23 - 4.55 µm, length of 40 µm and thermal conductivity of materials of approximately between 52 to 66 Wm-1K-1 became the optimized results at 1 V input voltage to obtain a maximum Joule heat of 4.9x105 W/mm3 and total current density of 5.6x107 mA/mm2.

Deep Q-Network-Enhanced Self-Tuning Control of Particle Swarm Optimization

Particle Swarm Optimization (PSO) is a widespread evolutionary technique that has successfully solved diverse optimization problems across various application fields. However, when dealing with more complex optimization problems, PSO can suffer from premature convergence and may become stuck in local optima. The primary goal is accelerating convergence and preventing solutions from falling into these local optima. This paper introduces a new approach to address these shortcomings and improve overall performance: utilizing a reinforcement deep learning method to carry out online adjustments of parameters in a homogeneous Particle Swarm Optimization, where all particles exhibit identical search behaviors inspired by models of social influence among uniform individuals. The present method utilizes an online parameter control to analyze and adjust each primary PSO parameter, particularly the acceleration factors and the inertia weight. Initially, a partially observed Markov decision process model at the PSO level is used to model the online parameter adaptation. Subsequently, a Hidden Markov Model classification, combined with a Deep Q-Network, is implemented to create a novel Particle Swarm Optimization named DPQ-PSO, and its parameters are adjusted according to deep reinforcement learning. Experiments on different benchmark unimodal and multimodal functions demonstrate superior results over most state-of-the-art methods regarding solution accuracy and convergence speed.

Optimum technological parameters of new filter materials for the preparation of drinking water

Optimum technological parameters of new filter materials for the preparation of drinking water

Preventing malware propagation in wireless sensor networks: Hybrid optimization algorithm for controlling

Malware transmission is a significant security issue in WSN, however, the influence of the attack and defensive processes on malware propagation is rarely taken into account in traditional malware propagation prevention methods. Advanced methods are in need to stop the propagation of malware of sensor nodes. With the formulation of representing dynamics among states, a new decision-making problem as the optimal control problem via hybrid optimization algorithm. The proposing model is termed as Butterfly Updated Bald Eagle Optimization based Prevention of Malware Propagation in Wireless Sensor Network (BUBEO-PMPWSN). In the proposed controlling system, optimal system parameters are analyzed via the BUBEO for preventing malware propagation in WSN. Particularly, the sensor node states considered are Susceptible, Infectious, Infectious and sleeping, recovered, Recovered and sleeping, and finally Dead. The system parameter tuning will be under the evaluation of fitness calculation under probability of infectious sensor node becoming recovered and the probability of infectious sensor node entering sleeping state. This optimal tuning strategy ensures the preventing of malware propagation. Finally, the performance of proposed BUBEO-PMPWSN model is evaluated and validated successfully by comparing other state-of-the-art models. The BUBEO-PMPWSN achieved 250 recovered nodes for time 500, while the HGS, BOA, HBA, COOT, and HHO scored 123, 115, 236, 172, and 180, respectively, for recovered nodes.

Mechanical properties of laser powder bed fusion processed Inconel alloy IN718 in different heat treatment conditions through small scale specimen testing

In this study, IN-718 samples were printed using laser powder bed fusion (LPBF) process to investigate the effect of printing parameters (in terms of Volume Energy Density, (VED)), printing orientation, heat treatment and test temperature on the microstructure and mechanical properties. Tensile properties were evaluated using small-scale tensile specimens extracted from samples printed with 15 different processing parameters (by varying scan speed and scan power) in two print orientations (XY and XZ plane), in three microstructural conditions (as-printed (AP), printed + solution treated and aged (STA), printed + hot isostatically pressed (HIP) + STA), at two different temperatures (room temperature and 650 °C). The mechanical properties obtained from testing of small-scale tensile specimens were compared with results obtained from testing of specimens following ASTM E8 standard, to understand effect of specimen size on mechanical properties. Based on microstructural analysis, it was observed that below a VED value of 50 J/mm3, the conduction region prevailed, with the presence of irregular lack of fusion porosities. In VED range of 50–100 J/mm3, the transition prevailed with highly dense samples (over 99 % of theoretical density) with minimal porosity. Above a VED of 100 J/mm3, the keyhole regime prevailed with the presence of spherical keyhole porosities. STA heat treatment improved YS and UTS to ∼1200 and ∼1400 MPa, respectively, while reducing ductility to ∼15 %. HIP + STA had similar effect on tensile properties as STA heat treatment. Based on tensile strength data, it was observed that HIP is not essential for parts printed with optimum parameters. Sample size in the present study was found to have an insignificant effect on tensile properties. In conclusion, the study provides an insight into the role played by printing parameters, printing orientation, and post-processing on defects, microstructures and thereby on the mechanical properties.

Classification-Based Parameter Optimization Approach of the Turning Process

The turning process is a widely used machining process, and its productivity has a significant impact on the cost and profit in industrial enterprises. Currently, it is difficult to effectively determine the optimum process parameters under complex conditions. To address this issue, a classification-based parameter optimization approach of the turning process is proposed in this paper, which aims to provide feasible optimization suggestions of process parameters and consists of a classification model and several optimization strategies. Specifically, the classification model is used to separate the whole complex process into different substages to reduce difficulties of the further optimization, and it achieves high accuracy and strong anti-interference in the identification of substages by integrating the advantages of an encoder-decoder framework, attention mechanism, and major voting. Additionally, during the optimization process of each substage, Dynamic Time Warping (DTW) and K-Nearest Neighbor (KNN) are utilized to eliminate the negative impact of cutting tool wear status on optimization results at first. Then, the envelope curve strategy and boxplot method succeed in the adaptive calculation of a parameter threshold and the detection of optimizable items. According to these optimization strategies, the proposed approach performs well in the provision of effective optimization suggestions. Ultimately, the proposed approach is verified by a bearing production line. Experimental results demonstrate that the proposed approach achieves a significant productivity improvement of 23.43% in the studied production line.

Dual-mode, signal-amplified DNA biosensor for label-free, reliable assay of gestational diabetes mellitus-related miRNA (miR-135a)

miR-135a is highly expressed in patients with gestational diabetes mellitus, and its target genes are also involved in insulin signaling pathway, so it is one biomarker for gestational diabetes mellitus. Herein we designed a dual-mode DNA biosensor for reliable assay of miR-135a based on the fluorescence and colorimetric signals. Several experiments were carried out to demonstrate the assay feasibility and mechanism for this dual-mode DNA biosensor. With optimum parameters, this proposed dual-mode biosensor has been realized sensitive and quantitative assay of miR-135a. For the fluorescence and colorimetric signals, the working ranges are 0.56–61 and 8.3–74 nM, while limits of detection are 0.18 and 3.7 nM respectively. This dual-mode strategy allows two independent signals for miR-135a assay, so it can verify each other to show more accurate results with good fidelity. Furthermore, there is a good selectivity in the biosensor for target miR-135a over other nucleotide variants, as well as good anti-interference ability in complex samples. This dual-mode DNA biosensor provides a new approach for miR-135a assay and miRNA expression profiling in gestational diabetes mellitus.

Photovoltaic Integrated Shading Devices in the Retrofitting of Existing Buildings on Chinese Campuses Within a Regional Context

Retrofitting existing buildings to be more energy-efficient is a tremendous contribution to the sustainability of society. The application of photovoltaic integrated shading devices (PVSDs) accords with this ambition by blocking out unwanted radiant heat gain and generating clean electricity. The deployment of PVSDs needs sensible design strategies to optimize the production of renewable energy while retaining the aesthetic quality of the built-up environment, especially in historic campuses. The concept was tested in a case study of buildings in South China University of Technology (SCUT) using Ladybug 1.4.0 and PVsyst 7.2, utilizing the existing “Xia’s shading” design method in historical environments and optimizing the design from the perspective of photovoltaic performance. Firstly, the photovoltaic (PV) panels were integrated as architectural components, and the parameters were incorporated into a mathematical equation based on “Xia’s shading” design method. This was followed by the assessment of the solar energy harvesting potential based on simulated annual solar irradiation values. Lastly, the PV panels’ solar irradiation potential under these different parameters was shown in figures to identify the optimum parameters combination for PVSD applications. The proposed methodology could evolve as a design tool and thus further assist in promoting the large-scale adoption of PVSDs in retrofit projects.

Efficient and sustainable approach of heavy metal adsorption from wastewater using algal biomass of Hypnea valentiae (Turner) Montagne, 1841

The biosorption of heavy metals especially, Cd2+, Pb2+, and Zn2+ from wastewater were evaluated using the biomass of macroalgae, Hypnea valentiae found in coastal waters of Rameshwaram, Tamil Nadu, India. The probable functional groups involved in the biosorption process was analyzed by Fourier transform infrared spectroscopy. The specific surface area, pore volume and pore diameter of prepared biosorbent was determined by Brunauer–Emmett–Teller (BET) analysis and it was found to be 59.993 m2 g−1, 0.292 cc g−1 and 1.429 nm, respectively. The scanning electron microscopy images after the biosorption revealed that the heavy metals have been adsorbed on to the surface of biosorbent. The optimization study was performed using Box–Behnken design and the optimum parameters used were initial concentration of metal ions (10–500 mg L−1), biomass dose (5–25 g L−1), contact time (10–120 min), temperature (25–45 °C), agitation speed (60–120 rpm) and pH (2–14). The heavy metal uptake (biosorption) was assessed by isotherm models including Dubinin–Radushkevich (D–R), Freundlich and Langmuir models. The maximum sorption of metal ions was observed in Langmuir isotherm model (R L 0.1773 and K F 2.2030 L mg−1) with an R 2 value close to 0.99 clearly indicating the chemical mode of metal ion adsorption. Also, the sorption of Cd2+, Pb2+, and Zn2+ on to the surface of algal biomass followed pseudo-second-order kinetics with a rate constant, k2 being 9.627 × 10−3 g (mg min) −1 and qe being 93.98496 mg g−1, strongly supporting the chemisorption mechanism. The computed thermodynamic parameters (ΔG°, ΔH, and ΔS) demonstrated an endothermic, spontaneous biosorption that was feasible. The maximum removal efficiency was achieved for Pb (92.86%) followed by Cd (91.48%) and Zn (87.32%). The biosorbent can be reused and regenerated up to four cycles efficiently. There was a significant reduction in the biological oxygen demand, chemical oxygen demand, total dissolved solids, and pH of wastewater after treatment with the biosorbent. From this study, it is assessed that the biomass from red algae can be utilized for the biosorption of heavy metals from polluted water which is cost-effective and eco-friendly.

Enhancing Viability of Lactobacillus plantarumBG24 Through Optimized Spray Drying: Insights Into Process Parameters, Carrier Agents, Comparative Analysis With Freeze Drying, and Storage Condition Influences.

This study investigated the survival dynamics of Lactobacillus plantarum BG24, a probiotic strain, within reconstituted skim milk (RSM) and yeast extract (YE) matrices during the spray-drying (SD) process, encompassing of inlet/outlet air temperatures. Notably, optimum SD parameters were found to be an inlet air temperature of 150°C and outlet air temperature of 83°C, that achieving high viability (92.23%), and reducing both moisture content (MC) (3.57%) and water activity (a w) (0.266). The use of soy protein isolate (SPI), gum Arabic (GA), RSM, maltodextrin (MD), sucrose (SUC), and lactose in binary mixtures or alone was investigated in terms of the best survival rate of probiotic bacteria, and RSM alone and RSM + GA and SPI alone were found to be the best drying carriers giving higher viability during SD. SD at optimum process temperatures and freeze drying (FD) were compared in the survival rate of probiotic bacteria in the carrier of RSM with YE, and FD samples showed a higher survival rate (97.69%) than SD samples. It was determined that the storage temperature (4°C and 20°C) had an impact on the glass transition temperature, MC, a w, and cell viability. Increased storage temperature led to a greater decrease in cell viability, especially for SD probiotic powders. These findings furnish critical insights into the intricate interplay among process parameters, carrier agents, drying techniques, and storage conditions, thereby elucidating avenues for refining probiotic preservation strategies within the ambit of SD, and by extension, in the domains of food and pharmaceutical sciences.

Bio-sorption of methylene blue using Datura stramonium leaves as adsorbent

Present study was accomplished to prospect the viability of using the Datura stramonium leaves powder (DS) as an adsorbent to remove the methylene blue from aqueous solution. The physico-chemical characteristics of the studied adsorbent were examined. The optimum parameters such as contact time, particle size, absorbent dose, initial methylene blue concentration, and pH were investigated by performing batch experiments models. The kinetics and the isotherms adsorption were evaluated by varying the initial concentration and using the optimum parameters. The optimum of contact time is 30min, with a removal capacity of 89.60 %. The optimal adsorbent concentration to reach the maximum removal of methylene blue (89.54 %) is 18 g/L. An initial methylene blue concentration of 50 ppm is ideal to reach the maximum capacity of removal (92.72 %). The optimum particle size is 80 mm. The kinetics of the adsorption process are in accordance with the pseudo-second order model. Experimental values of the adsorption capacity are close proximity to the optimum values predicted by the pseudo-second order model. Langmuir, Freundlich, Temkin, Dubinin-Radushkevich, Harkin-Jura and Hasley isotherms were applied to represent the data obtained from the adsorption studies. The highest R2 values were related to Freundlich, Dubinin-Radushkevich and Hasley isotherm models.

Application of Taguchi Method in Design of Surface Eddy Current Probes for Diagnostics of Power Equipment

The article’s aim is to create a method of reducing the influence on the surface eddy current probes output signal of a number of interfering parameters without their elimination, to ensure its sta-bility, which is achieved as a result of computer search of design and operating values of probes Taguchi-parameters at the stage of their design. To achieve the goal the following tasks were carried out: software for calculating the output signal of surface probes, which is based on the electrodynamic model of the measurement process for the test object in the form of a conductive plate of infinite over-all dimensions and finite thickness; using the Taguchi method, a special design of experiments with the use of orthogonal arrays is constructed, the fulfillment of which makes it possible to determine the influence of each parameter and their complex nonlinear interaction on the output signal of the probe; by integrating the Taguchi method with computer numerical simulation, the optimal controllable pa-rameters of the probe were determined, minimizing the signal changes caused by noise factors. The most important research result is the method creation of providing the signals probes stability and re-ducing the influence of noise parameters on them simultaneously without their elimination. The meth-od effectiveness is demonstrated on the example of designing a thickness gauge, which allowed com-puter search for a set of its optimal parameters to maximize the signal-to-noise ratio, thereby reducing the signal variability. The significance of the obtained results lies in the creation of theoretical and practical approaches to the design of surface eddy current probes with new properties of interfering factors suppression, which provide the best conditions for reliable diagnostics of power equipment objects.

Investigation of cutting forces of glass sphere reinforced polymer composites

AbstractIn this study, the effects of reinforcement ratio, drill bit material, and drilling process parameters on the cutting forces generated during the drilling of glass sphere‐reinforced polypropylene composites were investigated experimentally. Test specimens were produced by conventional injection‐moulding of glass sphere reinforced polypropylene composite materials at 5 %, 10 % and 20 % wt. ratios. High speed steel, titanium‐coated high‐speed steel, and carbide drill bits with 4 mm diameter were preferred for drilling. In addition, the drilling process was carried out on a 3‐axis computer numeric control milling machine. Three different feed rates of 0.05 mm/rev, 0.10 mm/rev, and 0.15 mm/rev and cutting speeds of 12 m⋅min−1, 16 m⋅min−1, and 20 m⋅min−1 were determined for the drilling process. In addition, Taguchi experimental optimization method, analysis of variance and scanning electron microscopy were used to investigate the morphology of the drilled surface and the wear mechanisms occurring on the drill bit due to the drilling process. The test findings showed that the maximum torque value was 54.64 N⋅mm and the maximum thrust force was 100.43 N. The optimum test parameter for cutting forces was observed as C1D3FR1CS3. Drill parameter had an effect of 40.96 % on thrust force and 36.11 % on torque.

An extensive analysis of GTAW process and its influence on the microstructure and mechanical properties of SDSS 2507

The Gas Tungsten Arc Welding (GTAW) process is well-known for its accuracy, simplicity, and economical, making it the optimum method for joining Super Duplex Stainless Steel (SDSS) materials. This review paper investigates the influence of the GTAW process on the microstructure, tensile strength, micro-hardness and corrosion resistance of SDSS welded joints. The optimum constant current GTAW process parameters are discovered by various researchers who found that the welding current range should be 65A–160A for joining up to 6 mm thick SDSS material. The pulsed current GTAW process optimum Peak current range (120–165A) and back current (60–80A) range for joining 4–14 mm thick SDSS material. Microstructural analysis revealed that coarse grain is in the welded joint's weld zone (WZ) and heat-affected zone (HAZ) because of the weld thermal cycle. The Widmanstatten austenite with ferrite grain boundary is found between HAZ and WZ due to thermal cooling. Welded joint tensile strength (740 MPa–896 MPa) is sometimes greater or the same as the base metal. It shows the GTAW best parameters selection. The microhardness of HAZ (380 HV) and WZ (370 HV) of the welded joint is increased with respect to base metal (310HV) GTAW process. Multiple studies have shown that using the best GTAW parameters can improve the microstructural properties of SDSS, resulting in increased tensile strength. The charge transfer resistance analysis of GTAW welded joint revealed that higher charge transfer leads to a lower corrosion rate having ER2594 filler material with icorrs value of 0.0139 μA/cm2.

Study on heat transfer and flow of molten pool during the deposition process of laser wire additive manufacturing

In the laser wire additive manufacturing process, the molten pool acts as the critical link between the wire and the deposited part. The heat transfer and flow behavior within the molten pool predominantly determine the quality of the final deposition. Under laser power ranging from 2400 to 3000 W, traverse speeds between 0.01 and 0.04 m/s, and wire feeding speeds from 0.03 to 0.08 m/s, three distinct flow states—single-swirl, double-swirl, and no-swirl—were observed with increasing heat input. Under the optimum process parameters, the molten pool with stable temperature distribution and orderly flow was obtained. In multilayer deposition, the implementation of a laser decay strategy mitigates steep temperature gradients, diminishes the Marangoni effect within the molten pool, and effectively reduces both heat accumulation and lateral flow. Consequently, the flow mode transitions from no-swirl to swirl, and the maximum flow velocity decreases by 40%.

Quick-Delivery Mold Fabricated via Stereolithography to Enhance Manufacturing Efficiency.

The ever-growing demand for reducing costs and decreasing the time to market in today's plastics industry makes rapid tooling and rapid prototyping highly researched areas. Stereolithography (SLA)-manufactured injection mold inserts make it possible to produce prototype parts rapidly and cost-effectively. To utilize SLA in the injection molding industry, two steps have to be considered. The first is to identify suitable SLA process and post-thermal curing process parameters to enhance the mechanical and thermal characteristics. The second is to verify the applicability of SLA-manufactured molds for use in the injection molding industry. IA comprehensive study was performed to find the optimum process parameters for an SLA mold with excellent mechanical and thermal properties and to verify the applicability of the mold. First of all, the mechanical and thermal properties of samples manufactured based on various laser powers and heat treatment at different temperatures were analyzed with a tensile test, DSC, and TMA according to the degree of cure. On the basis of the results from those tests, an SLA mold was designed and fabricated with the optimum mechanical and thermal properties. In addition, the SLA mold was assembled into an injection machine, and an injection molding test was conducted. The SLA mold endured during the injection cycle, and 500 shots were successfully injected without damaging the mold, which resulted in reaching the quick-delivery mold standard. Finally, we demonstrate that SLA is an effective technology to produce molds for use in the injection molding industry.

Fizzy extraction secondary electrospray ionization mass spectrometry for analysis of volatile solutes in high-matrix samples

Fizzy extraction (FE) is a rapid way to prepare liquid samples containing volatile organic compounds (VOCs) for analysis. The sample is first infused with a carrier gas, and subsequent rapid decompression of the sample chamber causes it to effervesce spontaneously. Secondary electrospray ionization (SESI) enables analysis of VOCs using mass spectrometry (MS). Here, we report direct hyphenation of FE with SESI-MS. In order to adjust the flow rate of the gaseous extract to match the optimum input flow rate of the ion source, flow was split with a tee junction. The following parameters have been optimized: pressure inside the sample chamber (during saturation), high voltage applied to the nano-ESI solution, temperature of desolvation line, temperature of heated block, temperature of the SESI chamber, gas pressure applied to the headspace of nano-ESI solution, and length of tubing connected to the tee junction. The optimum parameters were 150 kPa, +4.0 kV, 225 °C, 200 °C, 90 °C, 18 kPa, and 6 cm, respectively. The developed method was characterized using MS and high-speed imaging. The limits of detection for ethyl butyrate, ethyl pentanoate, ethyl hexanoate, ethyl octanoate, and ethyl decanoate are 1.11 × 10−7 M, 4.33 × 10−7 M, 8.13 × 10−8 M, 1.09 × 10−7 M, and 2.19 × 10−7 M, respectively. The analysis time was only 2.5 min per sample (not counting the cleaning step). The method was further applied for profiling VOCs in selected dairy products. Interestingly, the FE-SESI-MS method is much more tolerant to the sample matrix (milk) than headspace vapor analysis using the same ion source.