Chamber Temperature Research Articles

Rancang Bangun Insinerator Pengolahan Sampah dengan Penerapan Teknologi Termal yang Ramah Lingkungan

Concerns about environmental problems such as increasing the volume of waste which if not treated properly will affect environmental pollution which can damage soil fertility and also have an impact on human health. This study aims to make a waste processing incinerator with the application of thermal technology. Oil and water stoves are used as media for burning waste, the stove will burn the waste that has been put into the combustion chamber made of drums coated with clay. This clay coating aims to increase the temperature of the combustion chamber so that maximum combustion is obtained with minimal smoke. From the waste burning test, the temperature measurement results in the combustion chamber reached 751ºC. Carbon gas measured at the maximum temperature around the incinerator is 27 ppm. From the data obtained, it can be concluded that waste burning with an incinerator has been made to minimize air pollution so that it can be used for solutions in environmentally friendly waste processing.

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.

In situ mass spectrometric investigation to probe GeSn growth dynamics and mechanisms in the chemical vapor deposition processes

GeSn has attracted increasing attention due to its tunable bandgap from indirect to direct resulting in unique electronic and optoelectronic capabilities. Chemical vapor deposition (CVD) is well acknowledged as an advanced growth method for GeSn, demonstrating its capability with grown materials for infrared lasers and detector development. As an in situ diagnostics of the CVD process, a residual gas analyzer (RGA) could enable the detection of all gaseous species during growth, thus probing the growth dynamics and mechanism. Therefore, it is highly desirable but is lacking in the (Si)GeSn research community. This work utilized an RGA equipped with a specialized differential vacuum pumping system to analyze the mass spectra of the GeSn CVD precursors of SnCl4, GeH4, and their combination. The spectra of SnCl4 collected from gas samples at a standard base pressure of 0.3 Torr display consistent fragments with central mass-to-charge ratios (m/z) of 78, 120, 155, 225, and 260, corresponding to Sn+, SnCl2+, SnCl+, SnCl2+, SnCl3+, and SnCl4+, respectively. These profiles closely resemble those observed in the National Institute of Standards and Technology and Wiley and Matsumoto et al. The simultaneous introduction of SnCl4 and GeH4 at a combined pressure of several tens of Torr yields spectra, indicating a chemical reaction that produces GeCl4 at room temperature in the vacuum chamber and tubing. Utilizing Gaussian16 and ORCA codes, the ab initio and density functional thermochemistry computations were employed to predict potential essential reactions and validate the experimental findings.

Renewable energy integration for sustainable cold storage: Designing a solar PV operated thermoelectric cool chamber

Thermoelectric coolers utilizing peltier effect offer a promising solution for cooling applications. This study elaborates the design and optimization of a TEC-operated cool chamber and evaluation of developed thermoelectric cool chamber. A number of elements need to be carefully considered during the design process, including heat load assessment, TEC module selection and effective heat dissipation techniques. Appropriate TEC modules are chosen based on estimated cooling load, temperature difference achieved, power consumption, maximum cooling capacity of each TEC and heatsink. The solar photovoltaic operated thermoelectric cool chamber comprises essential components such as SPV Panel, solar charger controller, battery, PWM controller, TEC module with heat sink, and insulated box (TCC unit). The design considerations involve estimating total power consumption and determining the number and ratings of solar panels, batteries, and power conditioning devices to ensure reliable electricity supply. The system operates on SPV-generated power, utilizing MPPT charge controllers to maximize power output. Pulsed width modulation (PWM) systems efficiently regulate power distribution to thermoelectric modules, optimizing performance. The thermoelectric cool chamber was developed of 40 L water capacity. It was observed that, the chamber and water temperature in developed thermoelectric cool chamber was reduced from initial temperature by 11.85°C and 11.56°C, respectively after 24 hours. The chamber and water temperature after 24 hours were 13.31°C and 13.49°C, respectively. The performance evaluation showed that the chamber’s cooling efficiency was influenced by factors such as cooling load and water volume. This comprehensive approach enables the development of an effective and sustainable thermoelectric cooling system suitable for various applications.

Ultra‐Inclined Nanocolumnar ZnO Films Sputtered Using a Novel Masking Configuration Providing Controlled and Restricted Oblique Angle Deposition for Enhanced Sensing Platforms

AbstractOblique angle deposition (OAD) of inclined thin films is mainly performed using electron beam evaporation due to its accurate point source control over the incoming evaporated flux angle α, leading to thin films with a nanocolumnar inclination angle β. However, the utilization of magnetron sputtering (MS) with an extended source for OAD is not extensively studied and reported. This work presents a thorough analysis of ZnO inclined thin films deposited by a novel restricted DC‐reactive MS‐OAD technique. OAD‐inclined films are deposited at α ranged 60°‐88°, where incoming flux is restricted using a patented masking configuration enabling tunable control of deposited nanocolumn angular range. The described technique provides accurate control over the resulting β (99.5% reproducibility), allowing demonstrated βmax of 47.3°, close to theoretical limits predicted for ZnO. The approach discussed here probes enhanced control of β comparable to that observed in evaporation, however using an extended source, resulting in high‐quality reproducible nanocolumnar‐inclined films. The mentioned improvements result from the exploration of operational parameters such as magnetron power, working pressure, and chamber temperature, as well as the design of the restricting configuration and substrate holders and their influence on the resulting inclined thin film crystallinity, and morphology.

Surface Finish Optimization of Vapor Smoothened PLA Fabricated Parts with Microstructural Analysis

Additive Manufacturing (AM) is a product creation method done layer-by-layer. This process tends to create an unwanted feature known as staircase effect. Vapor smoothing is considered a viable solution for polymer-based AM products to minimized surface roughness. Research literature concerning vapor smoothing of polylactic acid (PLA) parts generally limited unlike its ABS counterpart. This research aims to identify optimum level for both chamber temperature and exposure time of the AM product. Two methods were used to compare their outputs with one another. The two methods are surface roughness tester and optical microscopy. The results provided an impressive 50.88 and 62.72% improvement based on the two test methods. Lastly, a contour-plot was generated to provide future users a guideline if they want to conduct research similar study.

Analysis of vacuum operation on hydrogen separation from H2/H2O mixture via Pd membrane using Taguchi method, response surface methodology, and multivariate adaptive regression splines

The influence of vacuum pressure applied on H2 separation from a palladium membrane is explored in this study. Three factors with three levels are considered, including the membrane chamber temperature with levels 320 °C, 350 °C, and 380 °C; the retentate-side total pressure with levels 1, 2, and 3 atm; and the permeation-side vacuum pressure with levels 0, 25, and 50 kPa. The Taguchi, response surface methodology (RSM), and multivariate adaptive regression splines (MARS) methods are employed to analyze the effects of the three parameters on hydrogen separation and predict their optimal combination. The retentate-side total pressure exhibits the highest impact on H2 permeation, following the permeation-side vacuum pressure and then the membrane chamber temperature. The maximum H2 flux is 0.226 mol∙s−1∙m−2, with H2 recovery of 91 % obtained at the optimal conditions with a temperature of 380 °C, a total pressure of 3 atm, and a vacuum pressure of 50 kPa. The improvement in H2 flux reaches 21.6 % compared with the case without the imposed vacuum pressure at the same temperature and total pressure. This result shows the imposed vacuum pressure is an efficient way to enhance H2 permeation. The maximum relative errors between the experimental data and the predictions from the Taguchi, RSM, and MARS methods are 6.74 %, 3.37 %, and 8.08 %, respectively. The RSM method presents higher accuracy than Taguchi and MARS, perhaps due to a more precise analysis of the interaction terms. The smaller amount of input data and ignoring the temperature effect in MARS could be the reason for the lower accuracy. Nevertheless, the MARS method still demonstrates acceptable results. The cost of the Taguchi method is lower than that of the RSM method since it requires fewer experimental cases. In a word, the choice of the prediction method depends on the desired accuracy and the experimental cost.

Insights into nanostructured silica particle formation from sodium silicate using spray drying: An experimental and theoretical study

Spray drying is a widely used operational procedure utilized in diverse sectors. The current knowledge of droplet mobility processesinside the drying chamber is not fully comprehensive due to the complex nature of droplet evaporation issues. The present study used a comprehensive methodology that integrated numerical models and actual testing to investigate the drying process of droplets in the context of spray drying. The precursor material utilized in this investigation was colloidal silica. The influence of external hydrodynamic variables, such as drying temperature (473, 673, and 873 K) and carrier gas flow rate (2, 4, 6 L/min), was thoroughly investigated in connection to the dynamics of droplets and the subsequent creation of silica particles. Distinct alterations in the size and shape of the silica particles were observed due to variations in drying temperature and carrier gas flow rate. The validity of this investigation was established by the generation of two discrete particle morphologies, namely spherical particles and doughnut-shaped particles. Spherical particles were produced under reduced carrier gas flow rates of 2 L/min and lower drying chamber temperatures of 473 K. In the quantitative evaluation, the computational fluid dynamics (CFD) computations properly established the evaporation rate constant (K) and the temperature difference (ΔT) inside the droplets. Furthermore, qualitative calculations provide insight into the complex dynamics of droplet motion inside the spray chamber. The results of this study have the potential to open up new possibilities for regulating nanoparticle creation via the use of the spray drying process.

Analytical modeling of nucleation and growth of graphene layers on CNT array and its application in field emission of electrons

Carbon Nanotube (CNT) arrays and graphene have undergone several investigations to achieve efficient field emission (FE) owing to CNT’s remarkable large aspect ratio and graphene’s exceptional FE stability. However, when dense CNT arrays and planar graphene layers were used as field emitters, their field enhancement factor reduced dramatically. Therefore, in this paper, we numerically analyze the growth of a dense CNT array with planar graphene layers (PGLs) on top, resulting in a CNT-PGL hybrid and the associated field enhancement factor. The growth of the CNT array is investigated using Plasma Enhanced Chemical Vapor Deposition (PECVD) chamber in C2H2/NH3 environment with variable C2H2 flow, Ni catalyst film thickness, and substrate temperature followed by PGL precipitation on its top at an optimized cooling rate and Ni film thickness. The analytical model developed accounts for the number density of ions and neutrals, various surface elementary processes on catalyst film, CNT array growth, and PGLs precipitation. According to our investigation, the average growth rate of CNTs increases and then decreases with increasing C2H2 flow rate and catalyst film thickness. CNTs grow at a faster rate when the substrate temperature increases. Furthermore, as the chamber temperature is lowered from 750 °C to 250 °C in N2 environment and Ni film thickness grows, the number of the graphene layers increases. The field enhancement factors for the CNT array and hybrid are then calculated based on the optimal parameter values. The average height of the nanotubes, their spacing from one another, and the penetration of the electric field due to graphene coverage are considered while computing the field enhancement factor. It has been found that adding planar graphene layers to densely packed CNTs can raise its field enhancement factor. The results obtained match the current experimental observations quite well.

Influence factors of frictional heat between bristles and rotor for a multi-stage brush seal

Frictional heat generates at frictional surface caused by contact between bristles of brush seal and rotor, which leads to early failure of the seal, especially downstream stage of multi-stage brush seal (MBS). In this paper, a three-dimensional tube bundle model of the MBS was established to study change of heat flux on the frictional surface among stages, internal temperature distribution of bristles and leakage flow characteristics of the seal. Moreover, three control strategies (i.e., increasing height of backing plate to rotor hbp, decreasing interference between bristles and rotor Δr and decreasing axial width of bristle pack wab) were analyzed to further investigate influence mechanism of the frictional heat. Results showed that the frictional heat at bristle tips mainly depend on formation of frictional heat caused by friction between bristle tip and rotor, transfer of heat from upstream stage to downstream one and dissipation of heat with flow of the airflow passing through the seal. For a traditional MBS with same structural single-stage seal units, a remarkable increasing bristle temperature at bristle tip of downstream stage and an increasing vortex area of airflow with higher temperature in chambers implied accumulation of the frictional heat at the downstream stages. Increase of hbp enhanced dissipation of the heat due to increasing passage area of airflow. Both decrease of Δr and decrease of wab obviously reduced bristle temperatures at downstream stages due to decreasing formation of the frictional heat. Furthermore, the decrease of wab had a lower bristle temperature compared to the increase of hbp, indicating a higher impact of the frictional heat formation on bristle temperature at downstage stages.

P‐239: Late‐News Poster: Modeling Particle Deposition in Evaporating Colloidal Droplets

Inkjet printing is a cost‐effective method of particle deposition applicable, for example, in the manufacture of Quantum Dot (QD) color filters. However, it is a challenge to achieve uniform deposition of particles because evaporating colloidal dispersions are prone to the coffee‐ring effect.When the particle size is small, it is difficult to gauge directly by experiment how particles migrate during the evaporation process. Consequently, it is a challenge to optimize the process conditions to improve uniformity by experiment alone. To aid in this task, we have developed a simulator for colloidal droplet evaporation. Rather than use an effective particle concentration field as in previous works, motion of each individual particle is calculated by Stokesian Dynamics, with particle interactions governed by the DLVO theory. In order to facilitate the simulation of large collections of particles, GPU computing is applied to reduce the simulation time.A phase‐field approach is taken to capture the interface physics at the solvent‐air interface. Within a colloidal droplet we find that, by controlling the temperature, it is possible to promote Marangoni flow and, in turn, improve deposition uniformity. In future, we aim to use simulation to further optimize the process conditions, such as the chamber pressure and temperature, in order maximize uniformity.

Analysis of the influence of damp-heat aging on the shear failure of the adhesive joint of composite materials

Abstract In this study, a comprehensive temperature and humidity environment chamber was used to accelerate the artificial aging of carbon fiber bonded joint specimens in wet and hot environments, and shear tests were conducted on non-aging and wet and hot aging specimens, respectively. At the same time, acoustic emission technology was used to monitor the damage to the specimen, and the influence of wet and heat aging on the shear properties and damage forms of the bonded joint was explored. It is found that under shearing load, the unaged bonded joint specimens first show delamination degumming damage with an energy distribution of about 1000 (mV*mS) and then fiber fracture damage with an energy distribution of more than 4000 (mV*mS). According to the load strain curve, it can be seen that the shear strength of the moisture-heat aging specimen decreases by 30% compared with that of the non-aging specimen, from 33.6 kN to 22.3 kN. According to the load energy curve, it can be seen that the rubber layer of the specimen is damaged at the inflection point of the load curve, the rubber layer of the non-aging specimen is damaged at 15 kN, and the rubber layer of the moisture-heat aging specimen is damaged at 8 kN. The test results show that the wet heat aging reduces the interlayer properties of the specimens. The structural adhesive delamination is serious, which leads to the damage of the aged specimens in advance compared with the non-aged specimens. The overall deformation of the specimens increases.

An analytical formula evolved from thermal-structural coupling model for life prediction and structural design of reusable thrust chambers

The thermal-structural analytic model is essential for the life prediction of reusable rocket thrust chambers. The common numerical model based on the finite element method is computationally intensive. In order to simplify the life prediction method and improve the calculation efficiency, a thermal-structural analytical formula is proposed. The one-dimensional analytical heat transfer algorithm for accurately calculating the temperature of the thrust chamber is established, and Porowski’s beam model for calculating the structural deformation is adopted. Finally, the analytic formula for life prediction is directly established by reasonable simplification. This is an algebraic solution describing the relationship between life and the cooling channel parameters, and the computational efficiency is improved by about 12,000 times. The calculated temperature and deformation of the inner wall are verified by the finite element method with an error of less than 10 %, indicating the proposed analytical formula is accurate. Further, the analytical formula is applied to design the cooling channel parameters according to the given target life. The structural design method is validated by numerical simulation and experimental data. The analytical formula and the structural design method provide new ideas for the analysis and design of reusable rocket engines, which have broad application prospects.

Design and optimization of a domestic solar dryer: an analytical approach

PurposeFood loss and wastage is an issue of global concern and the household sector is one of the biggest contributors to this. Solar drying has been explored by many eminent researchers as a solution to this problem but there have been concerns about the lack in designs, higher cost, lower performance, and consumer acceptability. The present research aims to design a small-scale domestic solar dryer by using computer software.Design/methodology/approachResponse surface methodology (RSM) and computational fluid dynamics (CFD) are used to design the domestic solar dryer. Initially, design variables (inlet and outlet vent height) are identified and a design of experiments has been created using RSM for set of experimental runs. The experimental runs suggested by RSM were carried out using CFD simulation in COMSOL Multiphysics software and the results were used for optimization of response variables (outlet velocity and drying chamber temperature) in RSM.FindingsOutlet vent height was found to be most significantly affecting parameter to both the responses. The optimum values of inlet and outlet vent heights were 0.5 and 2.5 cm, respectively with the overall desirability of 0.728. The model accuracy was tested by conducting a confirmation test as post processing in design expert software.Originality/valueDesigning a solar dryer is a complex, costly and time consuming process, this study presents an easy, economic and fast method to design a new solar dryer. It would help researchers to design and develop new domestic as well as large size industrial solar dryer.

Temperature- and rate-dependent tensile behaviour of unidirectional carbon/polyamide-6 composite under off-axis loading with oblique tabs

Unidirectional carbon/polyamide-6 (CPA6) is a thermoplastic composite with attractive properties for many industrial applications. However, shortage of experimental data may hinder the development of reliable material models. This paper is the first to provide a complete dataset for the tensile behaviour of unidirectional CPA6, including the longitudinal, transverse, in-plane shear, and off-axis response, at different temperatures and (quasi-static) strain rates. The oblique end tab design, already proven in the literature for off-axis testing of composites at room temperature, was successfully extended to the elevated temperature of 120 °C. The use of cardboard tabs and fast-curing adhesive greatly simplified the tab manufacturing and application for all the combinations of fibre angles, temperatures and strain rates. Digital image correlation (DIC) was performed through the window of the temperature chamber to verify the homogeneous strain field produced by the oblique tabs. The in-plane shear behaviour was extracted from the off-axis tests, allowing to estimate the shear modulus and shear strength. Finally, the robustness of the experimental results generated in this study was demonstrated with well-established analytical models that could excellently predict the elastic modulus, Poisson's ratio, and failure stress at different fibre angles.

Temperature Changes in the Pulp Chamber During Orthodontic Bonding Using a High-Power Light-Emitting Diode Device With Two Different Exposure Times and Intensities: An In-Vitro Study.

This study used a high-power light-emitting diode (LED) device to evaluate the effects of two exposure times and intensities on pulp chamber temperature and cooling time during bracket bonding. Sixty upper premolars were used in the sample in this study. These premolars were split into two main groups based on the exposure time and intensity: the first group employed a traditional curing mode (TCG) for 20 seconds with an intensity of 1200 mw/cm2, whereas the second group had a quick curing mode (QCG) for 3 seconds with an intensity of 2500 mw/cm2. The pulp chamber's temperature variations and cooling times were recorded using a thermal imaging camera. The Mann-Whitney U test was used to find differences between the two-group comparison of the pulp chamber's temperature and cooling time. The two groups had statistically significant differences regarding the temperature increase in the pulp chamber and cooling time (p > 0.001). The mean temperature increase in the traditional curing group was 3.52°C, which is greater than that in the quick curing group (i.e., a mean value of 1.28°C). The mean cooling time in the traditional curing group was 38.83 seconds, which is greater than that in the quick curing group (9.97 seconds). Reducing the exposure time to 3 secondsand increasing the intensity to 2500 mw/cm2is considered safer for the pulp chamber during and after the curing process.

Drying of Nettle Using Concentrated Air Collector and Concentrated Photovoltaic Thermal Supported Drying System and Modeling with Machine Learning

This study examines the performance of a solar assisted drying system in the nettle drying process. The drying process works by using thermal energy obtained from solar air collectors and PV modules. The experimental were carried out in October 2022, and the room temperature, total efficiency and moisture content parameters were investigated. The data obtained from the drying system were modelled using machine learning algorithms such as artificial neural networks (ANN), support vector machines (SVM), and gradient boosting decision trees (GBDT). The average thermal energy transferred to the drying cabin was calculated as 154 W, with 77% of this energy was obtained from the air collector and the remaining 23% from the PV module. The stinging nettle was dried from an initial moisture content of 11.18 g water/g dry matter to a final moisture content of 1.18 g water/g dry matter. The average total efficiency of the drying system was found to be 16.8%. Additionally, the results show that the SVM algorithm exhibits the best performance in estimating important parameters such as chamber temperature, moisture content, and total efficiency. Especially in total efficiency prediction. The SVM algorithm has a significant advantage over other algorithms. As a result, it was concluded that the SVM algorithm can be used effectively utilized in solar energy-supported drying systems and can be a precious choice for the optimization of the drying process.

Adaptive SARIMA modelling for continuous chamber temperature tracking in ultra-low temperature freezers

Ultra-low temperature (ULT) freezers are vital for storing perishable biological materials, requiring continuous monitoring of chamber thermal conditions to ensure sample integrity. A reliable dynamic data-driven model is key for smart proactive surveillance of the ULT freezers through real-time status tracking. However, the dynamic nature of ULT freezers, influenced by external disturbances, demands adaptive models to sustain performance. Complex models thus face challenges due to time-consuming parameter updates. To ensure model prediction performance while minimising model updating time, this study proposes a Seasonal Autoregressive Integrated Moving Average (SARIMA) model-based approach for short-term ULT freezer chamber temperature prediction. This method solely relies on historical chamber temperature data, eliminating the need for additional measurements. Moreover, two adaptive duty cycle length (DCL) selection strategies and a one-step ahead DCL estimation method are developed to address auto-correlation issues caused by recurring duty cycles. Comparative analyses with reference models demonstrate that the SARIMA model, incorporating future DCL effects, excels in one-step prediction and multi-step forecast under stable and variant DCL periods. Moreover, it outperforms the reference models in auto-correlation representation, affirming its reliability in predicting future states. The proposed modelling approach promises an effective method for freezing chamber temperature prediction, enabling continuous status tracking and early fault detection. Moreover, it holds great potential for modelling other critical temperatures in refrigeration systems and facilitating flexible energy operations.

Application of ensemble machine learning techniques to the diagnosis of the combustion in a gas turbine

This paper describes a method based on the combination of several machine learning techniques, working together in an ensemble, with the aim of continuously monitoring the combustion of a gas turbine in a combined cycle by observing the available exhaust gas temperature measurements and operation condition variables. The goal of this monitoring is the automatic detection of anomalies in the combustion chambers, and possible faults in the measurement thermocouples in the gas turbine as soon as possible. Four gas turbines were studied, each one equipped with twenty-one thermocouples located at the exhaust gas outlet to measure the temperature in each combustion chamber. These sensors are located at the exhaust of the gas turbine, symmetrically distributed on a circle.The anomaly detection method developed is based on an ensemble that combines models characterizing the normal behavior expected without anomalies but also the analysis of the actual temperatures of the gas turbine. In particular, neural networks and principal component analysis (PCA) have been applied. These models are used to compare the current performance of the gas turbine with past performance in reference periods known as normal operating conditions, in which a homogeneous distribution of exhaust gas temperatures is observed and a functional relationship between these temperatures and the operating variables such as power output must be fulfilled. If the behavior observed is significantly different from what the designed system expects, it is analyzed to find the cause of this anomaly that could be focused on a specific thermocouple or some combustion chambers. The failure will be associated with a combustion chamber failure if several thermocouples from the same combustion chamber are shown as faulty. This is very useful for planning maintenance and for saving time by removing the problem observed. This paper describes the methods used and real cases of application, which have not been applied as a whole independent analysis system in previous researches. The results obtained have validated the strategy proposed.Gas turbines can fail due to different components, but the main focus of this article will be gas turbines combustor faults.

In Situ Pulsed Hydrogen Implantation in Atom Probe Tomography.

The investigation of hydrogen in atom probe tomography appears as a relevant challenge due to its low mass, high diffusion coefficient, and presence as a residual gas in vacuum chambers, resulting in multiple complications for atom probe studies. Different solutions were proposed in the literature like ex situ charging coupled with cryotransfer or H charging at high temperature in a separate chamber. Nevertheless, these solutions often faced challenges due to the complex control of specimen temperature during hydrogen charging and subsequent analysis. In this paper, we propose an alternative route for in situ H charging in atom probe derived from a method developed in field ion microscopy. By applying negative voltage nanosecond pulse on the specimen in an atom probe chamber under a low pressure of H2, it is demonstrated that a high dose of H can be implanted in the range 2-20 nm beneath the specimen surface. An atom probe chamber was modified to enable direct negative pulse application with controlled gas pressure, pulse repetition rate, and pulse amplitude. Through electrodynamical simulations, we show that the implantation energy falls within the range 100-1,000 eV and a theoretical depth of implantation was predicted and compared to experiments.