High Pressure Temperature Research Articles

Pipeline and Rotating Pump Condition Monitoring Based on Sound Vibration Feature-Level Fusion

The rotating pump of pipelines are susceptible to damage based on extended operations in a complex environment of high temperature and high pressure, which leads to abnormal vibrations and noises. Currently, the method for detecting the conditions of pipelines and rotating pumps primarily involves identifying their abnormal sounds and vibrations. Due to complex background noise, the performance of condition monitoring is unsatisfactory. To overcome this issue, a pipeline and rotating pump condition monitoring method is proposed by extracting and fusing sound and vibration features in different ways. Firstly, a hand-crafted feature set is established from two aspects of sound and vibration. Moreover, a convolutional neural network (CNN)-derived feature set is established based on a one-dimensional CNN (1D CNN). For the hand-crafted and CNN-derived feature sets, a feature selection method is presented for significant features by ranking features according to their importance, which is calculated by ReliefF and the random forest score. Finally, pipeline and rotating pump condition monitoring is applied by fusing the significant sound and vibration features at the feature level. According to the sound and vibration signals obtained from the experimental platform, the proposed method was evaluated, showing an average accuracy of 93.27% for different conditions. The effectiveness and superiority of the proposed method are manifested through comparison and ablation experiments.

Insights into predicting equilibrium conditions of clathrate hydrates of methane + water-soluble hydrate former

This study aims to improve the prediction of equilibrium conditions in methane hydrate systems by incorporating diverse water-soluble hydrate formers and applying advanced machine learning techniques. Methane hydrates, which naturally form under high pressure and low temperature, can be more efficiently formed or dissociated by altering thermodynamic conditions using these hydrate formers. Accurate prediction of these conditions is crucial for optimizing gas storage and energy applications. In this research, molecular descriptors and operational parameters, such as mole fraction and pressure, are used as input variables to predict equilibrium temperature. Machine learning methods, including Decision Trees (DT), Random Forests (RF), Support Vector Machines (SVM), and Multi-Layer Perceptron (MLP), were employed with a novel data-splitting approach based on hydrate formers rather than traditional sample-based methods. Among these models, the RF achieved the highest performance, with a coefficient of determination (R2) of 0.930, a root mean square error (RMSE) of 1.71, and an average absolute relative deviation (AARD) of 0.48%. Feature selection, preprocessing, and Shapley Additive Explanations (SHAP) provided valuable insights into the influence of specific variables on model predictions. Additionally, a supplementary examination, termed the reduced model, highlights the critical role of proper feature selection, with certain features regarded as less important yet essential for the functionality of distance-based models, particularly for models like SVM and MLP. This work advances methane hydrate research by offering a more accurate and interpretable framework for predicting hydrate equilibrium, addressing key gaps in previous studies, and extending its applicability to a broader range of systems. Moreover, the introduction of a former-based data-splitting method improves generalization across different hydrate formers, while the use of SHAP values for model interpretability offers deeper insights into the relationships between molecular descriptors and hydrate equilibrium conditions. This study paves the way for improved selection of hydrate formers in hydrate systems.

CO2 Foam Stabilized by Viscoelastic Surfactant: Effects of Chelating Agents’ Type, pH, and Water Chemistry on Microstructure, Stability, and Rheology of Foam

Summary This research fully investigates the impact of chelating agent pH, chelating agent’s type, water chemistry, and viscoelastic surfactant (VES) concentration on the rheology and stability of CO2 foam under harsh reservoir conditions. In this regard, a modified high-pressure high-temperature (HPHT) foam rheometer and HPHT foam analyzer were implemented to study the foam rheology and stability at 100°C and 1,000 psi. Additionally, the HPHT viscometer and drop shape analyzer were utilized to understand the role of physicochemical properties on the microstructure, stability, and rheology of CO2 foam. First, the role of L-glutamic acid N,N-diacetic acid (GLDA) pH on the foam properties and foam rheology was investigated; the results showed that GLDA has a significant effect on the viscosity, stability, and foamability of CO2 foam. The optimum foam viscosity was achieved with a GLDA pH of 3, while the highest stability was attained with a GLDA pH ranging between 4 and 7. The highest foamability was achieved with low GLDA pH (3 to 2) due to the formation of high bubble numbers with uniform fine texture. Second, different chelating agents were considered; low pH GLDA provided the highest foam viscosity and stability among diethylene triamine pentaacetic acid (DTPA) salt and ethylenediaminetetraacetic acid (EDTA) disodium salt, while high pH EDTA exhibited the highest foamability. Additionally, three types of water were studied: produced water, sea water, and formation water. The outcomes showed that water salinity significantly impacts the foam formation process, where the formation water presented poor foamability. Finally, the concentration of surfactant has a major effect on the viscosity of CO2 foam; it reached 150 cp at 100/s once the concentration increased to 6 wt%. This study provides a comprehensive understanding of the impact of additives and water chemistry on VES behavior for CO2 foam. Also, the usage of erucamidopropyl hydroxypropylsultain (SURF) is promising for the generation of high stability and foam viscosity at high salinity and high temperature and pressure.

Investigation on flash boiling of superheated acetone spray under low vacuum conditions

Spray Flash Evaporation has recently demonstrated promising results in various fields of application and has more recently shown potential in the elaboration of nanoenergetic materials. This technique offers advantages in terms of morphology, size, and reactivity of the produced materials. However, specific thermodynamic conditions are required to produce these materials using acetone as a solvent: high injection temperature (typically between 80 and 160 °C) and low pressure (generally between 10 and 100 mbar) in the chamber are needed, i.e., superheat level. The study on the formation of acetone droplets in the far-field and under such conditions is lacking. Consequently, we propose here to further understand the relationship between injection temperature and back pressure in the chamber with nucleation and droplets characteristics (velocity, average size, size distribution, and concentration) in order to find optimal conditions for generating theoretically smaller particles through droplet evaporation. The tests were conducted in an unusual range of injection temperatures and pressures for flash boiling but commonly used for the production of energetic particles, from 80 to 200 °C and from 12 to 300 mbar, respectively. By using such conditions, it has been found that increasing the injection temperature and decreasing the back pressure are beneficial for generating a large concentration (up to 27.0 x 106droplets.cm−3) of smaller droplets with a narrow size distribution (down to 2.13 ± 0.13 µm) and high velocity (up to 204.2 m·s−1). It was also shown that there is an injection temperature threshold above 160 °C, beyond which the size distribution widens again by 12 % at 200 °C, and the number of droplets decreases by 64 %. This phenomenon can be observed only if we use a very high superheat level. This study demonstrates that these conditions are likely to promote and ultimately lead to the production of particles that are as fine and uniform in size as possible. Nevertheless, operating at very high injection temperatures (>160 °C) could hinder the nucleation and the formation of uniform droplets due to the high competition between the superheat level (Rp > 1188) and the surface tension of the liquid approaching near-zero values. By introducing the use of criteria related to mechanic and thermodynamics, along with droplet size and velocity, it was also observed that the droplet size is primarily influenced by the nucleation rate, while droplet velocity is influenced by both driving forces (mechanical and thermodynamic). The temperature and pressure in the chamber must therefore be carefully chosen to improve droplet formation and potentially produce smaller, homogeneous particles in size as they evaporate.

Applications of machine learning to high temperature and high pressure environments: A literature review

In recent years, machine learning as a new style of calculation has been developed quickly, and because it can obtain results that experiments cannot achieve, it has become a useful calculation tool in the field of high temperature and high pressure (HTHP). It can simulate and calculate the experimental results according to some calculation principles, such as first-principles, and execute prediction based on models created, such as Gaussian approximation potential, to obtain high-precision results. In addition, its simulation process is very fast, and the cost is not as expensive as that of density functional theory, so machine learning in the field of HTHP computing has aroused great research interest. The rapid development of machine learning makes it a powerful tool to predict some parameter or mechanism of materials and brings a new chance to simulate more complex experimental environments. In this paper, we review some of the most recent applications and insights into machine learning techniques in the fields of mechanics, thermology, electricity, and structural search under the demanding conditions of HTHP.

Sound velocities and thermal equation of state of fcc-iron-nickel alloys at high pressure and high temperature: Implications for the cores of Moon and several planets

Fcc-Fe-Ni alloy is believed to be the most dominant solid constitute of moderate-sized terrestrial planetary cores. Investigating the physical properties, especially the density and sound velocity of Fe-Ni alloys and comparing them with seismic observations is an indispensable approach to constructing compositional models for planetary interiors. In this study, we conducted sound velocity measurements on Fe-Ni alloys with 10 wt.% and 20 wt.% Ni up to ∼13.5 GPa and 1073 K, using the ultrasonic interferometry technique in a multi-anvil apparatus in conjunction with synchrotron radiation. By fitting the experimental data to finite strain equations, the bulk and shear moduli and their pressure and temperature derivatives are derived, yielding KS0 =145.8(14) GPa, G0 = 73.2(7) GPa, KS0’ = 5.89(24), G0’ = 2.89(8), (∂KS/∂T)P = -0.0181(12) GPa/K and (∂G/∂T)P = -0.0393(10) GPa/K for fcc-Fe80Ni20. An examination of the density-velocity relationship shows that compressional wave velocity is insensitive to temperature within the current pressure and temperature range, while shear wave velocity exhibits a large reduction with increasing temperature. Extrapolation of the sound velocities following the finite strain theories suggests that much slower Vs should be expected at pressure and temperature conditions corresponding to those of the lunar core. Possible core density and velocity profiles for other moderate planets and satellites, such as Mars, Mercury, and Ganymede are also calculated.

Synergistic optimization on Seebeck coefficient and electrical conductivity in 2H-MoS2 enabled by progressively evolved stacking faults under high pressure and high temperature

In thermoelectricity, the stacking faults (SFs) have been investigated mainly in phonon transport but rarely in carrier transport. For the layered thermoelectric materials, the layered nature makes them prone to SFs, especially under high pressure because of the induced shear stress between grains. Herein, we take the typical layered 2H-MoS2 as an example to investigate the effect of high-pressure in situ-induced SFs on the thermoelectric transport properties under high pressure and high temperature. It was found that a continuous transition of P-N-P type conductive behavior with increasing pressure was observed in the sign of Seebeck coefficient, finally leading to a not weakened Seebeck coefficient. Furthermore, the in situ-induced SFs enhanced the interlayer interaction and provided transport channels for carriers across the interlayers to boost the electrical conductivity to ∼11 100 S m−1 at 5.5 GPa, 1110 K. Consequently, combined with intrinsic ultralow thermal conductivity of MoS2, a maximum ZT value of 0.191 was obtained at 5.5 GPa, 1110 K, comparable to those doped/composited MoS2. This conduction-type transition induced synergistic optimization on Seebeck coefficient and electrical conductivity could be ascribed to that SFs, which had a progressive evolution process for stabilization with rising pressure, in which some associated defects might be induced, and the band structure could be modified for regulating the carrier distributions and the density of states around the Fermi level. This study provided profound insights of regulating conduction type via dynamically modulating the lattice defects for designing a high-efficiency TE device.

Investigation on the development of Novel PAM structure as high-performance clay inhibitor in HT/HP conditions by using functional groups

Polyacrylamide (PAM) molecular structures are not stable at higher temperatures, limiting their effectiveness in water-based drilling fluid (WBDF) applications. This study focuses on identifying functional groups that can enhance the thermal stability of PAM structure. It presents a comprehensive and comparative analysis of the swelling inhibition capacity of both low and high molecular weight (MW) PAM-based polymers at high temperature and high pressure (HT/HP). The mechanism by which modified PAM interacts with and adsorbs to the clay (Na-MMT) surface is examined, along with an analysis of the surface properties of the clay minerals. Therefore, molecular dynamic (MD) simulation results revealed that the Novel PAM polymers with high MW containing ethyl and benzyl groups demonstrate greater stability and more controlled deformation behavior compared to conventional PAM at HT conditions. Surface modification and hydrophobic effects were observed in the interactions between polymers and Na-MMT. Low MW PAM-based polymers showed larger fluctuations in d-spacing, indicating various or more disruptive interactions. In contrast, the insertion of high MW PAM-based polymer resulted in significantly narrower and lower d-spacing fluctuation ranges. The Novel PAM exhibited superior performance, providing lower d-spacing fluctuations compared to both low MW PAM-based polymers and standard PAM. Across a temperature range from 300 to 600°K, the Novel PAM consistently improved polymer adsorption on the Na-MMT surface compared to standard PAM. Indicating that the modifications effectively reduce the interaction between Na-MMT particles and water molecules while enhancing the interaction between the polymer and Na-MMT, potentially leading to more stable structures in HT/HP environments. The enhanced stability suggests that Novel PAM is more suitable for WBDF applications, as it is less prone to structural changes and can maintain its integrity under harsh conditions. The modifications provide the polymer with better resilience, potentially leading to improved performance in practical applications.

Tracing the origin of volatiles on Earth using nitrogen isotope ratios in iron meteorites

Understanding the relationships between the nitrogen (N) isotope ratios of early solar system planetesimals and terrestrial reservoirs is crucial for tracing the origin of volatiles on Earth. The Earth primarily grew from planetesimals and planetary embryos that accreted rapidly (within ∼1–2 Ma after CAIs) in the inner solar system, also known as the non-carbonaceous (NC) reservoir. Magmatic iron meteorites, which sample the metallic cores of the earliest solar system planetesimals, have emerged as a promising proxy in this exercise. NC irons are distinctly 15N-poor compared to their CC (carbonaceous or outer solar system) counterparts. However, the utility of this proxy is limited by the lack of knowledge of N isotope fractionation during core crystallization. Using high pressure-high temperature experiments, we show that equilibrium N isotopic fractionation between solid and liquid metal (Δ15Nsolid–liquid = δ15Nsolid − δ15Nliquid) is limited (≤1.2 ‰) under conditions relevant for core crystallization. This, combined with the siderophile character of N and limited equilibrium N isotope fractionation during core-mantle differentiation, suggests that the δ15N values of iron meteorites accurately represent the N isotopic composition of their parent bodies. Unlike the variation in the N isotope ratios of NC and CC chondrites, which can be attributed to the effects of parent-body processes acting on organic precursors, the 15N-poor nature of NC irons relative to CC irons likely offers the most definitive evidence for the distinct N isotopic compositions of the earliest inner and outer solar system planetesimals. The N isotopic composition of Earth’s primordial mantle (δ15N = <−40 ‰) suggests that it retains the memory of the early accretion of 15N-poor NC iron meteorite parent body-like planetesimals. The early accreted 15N-poor nitrogen may be stored in the deep mantle, segregated into the core, or lost to space during atmospheric loss caused by impacts. This signature was overprinted by the subsequent accretion and admixing of CC materials, which is reflected in the relatively 15N-rich nature of Earth’s atmosphere (δ15N = 0) and convecting mantle (δ15N = −5 ‰).

Exploring robustness of hybrid membranes under high hydrostatic pressure and temperature.

Bacterial membranes are typically composed of ester-bonded fatty acid (FA), while archaeal membranes consist of ether-bonded isoprenoids, differentiation referred to as the 'lipid divide'. Some exceptions to this rule are bacteria harboring ether-bonded membrane lipids. Previous research engineered the bacterium Escherichia coli to synthesize archaeal isoprenoid-based ether-bonded lipids together with the bacterial FA ester-linked lipids, showing that heterochiral membranes are stable and more robust to temperature, cold shock, and solvents. However, the impact of ether-bonded lipids, either bacterial or archaeal, on membrane robustness, remains unclear. Here, we investigated the robustness, as survival after shock, of E. coli synthesizing either archaeal or bacterial ether-bonded membrane lipids, under high temperature and/or high hydrostatic pressure (HHP). Our findings reveal E. coli with bacterial ether-bonded lipids is more robust under HHP and high temperature. On the contrary, the presence of archaeal ether-bonded membrane lipids in E. coli does not affect the robustness under HHP nor high temperature under the tested conditions. We observed morphological changes induced by the shock treatments including reduced length under high temperature or HHP, and the presence of elongated cells after a shock of HHP and high temperature combined, suggesting the combined treatments impaired cell division. Our results contribute to a deeper understanding of membrane adaptation to extreme environmental conditions and highlight the significance of HHP as a key parameter to investigate the differentiation of membranes during the lipid divide.

Investigation into Enhancing Methane Recovery and Sequestration Mechanism in Deep Coal Seams by CO2 Injection

Injecting CO2 into coal seams to enhance coal bed methane (ECBM) recovery has been identified as a viable method for increasing methane extraction. This process also has significant potential for sequestering large volumes of CO2, thereby reducing the concentration of greenhouse gases in the atmosphere. However, for deep coal seams where formation pressure is relatively high, there is limited research on CO2 injection into systems with higher methane adsorption equilibrium pressure. Existing studies, mostly confined to the low-pressure stage, fail to effectively reveal the impact of factors such as temperature, high-pressure CO2 injection, and coal types on enhancing the recovery and sequestration of CO2-displaced methane. Thus, this study aims to investigate the influence of temperature, pressure, and coal types on ECBM recovery and CO2 sequestration in deep coal seams. A series of CO2 core flooding tests were conducted on various coal cores, with CO2 injection pressures ranging from 8 to 18 MPa. The CO2 and methane adsorption rates, as well as methane displacement efficiency, were calculated and recorded to facilitate result interpretation. Based on the results of these physical experiments, numerical simulation was conducted to study multi-component competitive adsorption, desorption, and seepage flow under high temperature and high pressure in a deep coal seam’s horizontal well. Finally, the optimization of the total injection amount (0.7 PV) and injection pressure (approximately 15.0 MPa) was carried out for the plan of CO2 displacement of methane in a single well in the later stage.

Synthesis of Homoallylamine Covalent Organic Frameworks Via Hosomi-Sakurai Reaction Under Mild Conditions.

One-pot multicomponent reactions (MCRs) are a valuable strategy to synthesize functional covalent organic frameworks (COFs) in a single step. Most reported COF syntheses involve solvothermal processes, and because of the harsh reaction conditions, such as high temperature or high pressure, large-scale production of COFs has been limited. The synthesis of homoallylamine substituted COFs via a one-pot Hosomi-Sakurai reaction is reported. At room temperature the reaction of allyltriethylgermane with either terephthalaldehyde or [1,1'-biphenyl]-4,4'-dicarbaldehyde, and 1,3,5-tris(4-aminophenyl)benzene (TAPB) is catalyzed by Sc(OTf)3 to produce two COFs: TAPB-1P-Allyl COF and TAPB-BP-Allyl COF. The allyl functionalized COFs shows high crystallinity, with micropores ranging from 3.2 to 3.9nm, for TAPB-1P-Allyl COF and TAPB-BP-Allyl COF respectively, and both COFs are hydrolytically stable at different pH levels. Post-synthetic modification of these COFs with iodomethane produces methylated cationic COFs that demonstrates >98% adsorption efficiencies below the detection limit of perfluorooctanoic acid (PFOA) and perfluorodecanoic acid (PFDA) from aqueous solutions. After four cycles adsorption efficiency remains high with concentrations of PFOA below the detection limit.

Designing invert emulsion drilling fluids for high temperature and high-pressure conditions

Good and optimal rheology is a primary requisite for a drilling fluid to achieve better hole-cleaning and barite sag resistance. Conventional thickeners like organophilic clay that provide rheology to invert emulsion fluids degrade with time and thereby fail to maintain sufficient rheology of the drilling fluid. Generally, excess amount of organophilic clay or low gravity solids (LGS) is added to the drilling fluid to enhance rheology. However, addition of excess amount of organoclay or low gravity solids not only increases the cost of drilling but also may severely affect other drilling fluid properties, which will require further treatment. In addition, addition of organoclay or low gravity solids increases the plastic viscosity, decreases the rate of penetration thereby ultimately increasing the cost of drilling. Thus, there was a need to develop a drilling fluid with optimal rheology sufficient to give good hole cleaning and barite sag resistance. This paper describes the formulation of 70pcf, 90pcf and 120pcf organoclay-free invert emulsion drilling fluids formulated with a novel rheology modifier combination of RM1 and RM2. The paper describes the synergistic effect of RM1 and RM2 which is a combination of fatty acid and fatty amine respectively. The fluids were hot rolled at 250°F, 250°F and 350°F respectively and the temperature effect on the rheological and filtration properties were studied. The paper also describes the static aging and contamination studies of 90pcf and 120pcf fluids at 250°F and 350°F respectively. Rheology of the 90pcf invert emulsion fluid was measured across high temperature and high pressure (HTHP) conditions to observe their effects on the fluid properties. 70pcf, 90pcf and 120pcf organoclay-free invert emulsion drilling fluids formulated with the novel rheology modifier combination of RM1 and RM2 showed optimal rheology and low HTHP fluid loss. Static aging studies of 90pcf IEFs at 250°F respectively showed that the fluids are sag-resistant with low top-oil separation. Contamination studies of 90pcf fluid showed that the contaminants have minimal effect on the rheology and filtration properties of the invert emulsion fluid. HTHP rheology of the 90pcf invert emulsion fluid shows consistent rheology across high temperatures and pressures. The paper thus demonstrates the superior performance of the rheology modifier combination to achieve good rheological and filtration properties.

Plasma-Assisted Synthesis of Methanol Through Hydrogenation of Carbon Dioxide With Non-Noble Metal Mixed Oxide Catalysts.

The utilization of carbon dioxide through chemical conversion is a promising approach for the recycling of carbon resources. Despite well-developed industrial processes for CO2 hydrogenation to methanol, the effective use of CO2 as a feedstock remains challenging because of the costly requirements of high temperature and reaction pressure. In this paper, we report the methanol synthesis from CO2 and hydrogen using a dielectric barrier discharge (DBD) reactor under atmospheric pressure with a nickel-cerium-aluminum mixed oxide (Ni/Ce-Al MOx) catalyst. The combined use of plasma and the Ni/Ce-Al MOx catalyst was observed to yield 13.3±0.4 % of methanol, favorably compared to the 2.6±0.5 % yield of the case without catalyst. Microscopy images, selected area electron diffraction patterns, and energy-dispersive X-ray analysis confirmed the presence of fluorite-structured ceria, aluminium, nickel, and nickel oxide particles in the catalyst. The reaction mechanism for the plasma-assisted hydrogenation of CO2 was hypothesized to involve a carbide formation pathway due to the presence of carbide confirmed by X-ray photoelectron spectroscopic characterization.

Effect of temperature on transport index of fish oil-based drilling mud in high pressure high temperature well: a hybrid model approach

Diesel Oil-based drilling mud used in the oil and gas industry causes severe environmental and public health issues due to its high toxicity, especially in high-pressure, high-temperature (HPHT) wells. Therefore, easily biodegradable synthetic oil-based mud with high drilling performance is essential. Fish oil is a bio-oil known for its non-toxicity, high lubricity, thermal stability, and biodegradability. Effective hole cleaning is crucial for drilling performance and is ensured by the rheological properties of drilling mud. While rheological parameter prediction can be performed using an artificial neural network (ANN) based model, such models often fail to provide accurate predictions for unseen data. In contrast, empirical models are more robust and facilitate generalization. This study aims at assessment of the suitability of invert emulsion fish oil-based drilling mud (IEFOBDM) in HPHT wells through evaluation of hole cleaning performance (HCP) using a hybrid approach that combines an ANN with nonlinear regression (NLR) for temperatures ranging from 40 °C to 80 °C.Firstly, an ANN model was developed considering mud weight, temperature, and shear rate. Secondly, the NLR model was used in the prediction of rheological parameters, namely, Yield point (YP) and Plastic viscosity (PV), based on the predicted shear stress from the ANN model. Finally, the performance metrics of the ANN-NLR rheological model were evaluated using the root mean square error (RMSE) and correlation coefficient (R2) and comparison made with the Single ANN rheological model. The results showed the outperformance of ANN-NLR model over the ANN model for rheological parameter prediction, with R2 values of (0.99) for YP and (1) for PV. The predicted PV and YP values were then used for evaluation of transport index (TI) for HCP analysis. The effect of temperature on TI analysis showed this with increase in temperature, TI also increased, indicating the proposed mud providing good HCP under HPHT conditions.

Dynamic Nuclear Polarization with P1 Centers in Diamond.

Substitutional nitrogen impurities within the diamond lattice, known as P1 centers, have unpaired electrons that can mediate microwave driven dynamic nuclear polarization (DNP). In this paper we explore DNP of the bulk 13C spins in micrometer-sized P1 diamond particles and demonstrate a 550-fold DNP enhancement of the bulk 13C spins at room temperature in a 9 T magnetic field or 250 GHz for g ≈ 2 electrons. We study the DNP mechanisms, exploring their dependence on sample spinning frequency and microwave irradiation frequency using both continuous wave and frequency swept microwave irradiation, and discuss the results alongside recent DNP studies in the literature. Even with a modest microwave irradiation power of 160 mW from our frequency swept solid-state microwave source, we achieve a significant 13C signal enhancement, ε = 270 at room temperature. The enhancements were found to increase with the magic angle spinning (MAS) frequency, ωr/2π, and the results provide mechanistic insights into how different electron populations contribute to the observed DNP efficiency. These findings are inherently interesting and of practical importance in view of the recently reported diamond rotors fabricated from P1 high-pressure, high-temperature (HPHT) diamond.

High-Pressure Monosulfide Solid Solution FexNi1−xS Phases: X-Ray Diffraction Analysis and Raman Spectroscopy

High-pressure high-temperature (HPHT) crystalline monosulfide solid solution (Mss) phases (FexNi1−xS, x = 0.90, 0.75, 0.50, 0.25), troilite (FeS I), and α-NiS of the Fe-Ni-S system were synthesized at 7 GPa and 900–1550 °C. The structural parameters of the obtained phases were refined by XRD using the Rietveld method. Factor group analysis revealed the number of active Raman modes for FeS I and α-NiS. Raman spectra of troilite, α-NiS, and Mss phases were obtained. It was shown that the Raman spectra of Mss phases and α-NiS have a similar topology. The Raman spectra of the experimental phases in the Fe-Ni-S system were analyzed with non-negative matrix factorization, which provided a meaningful concentration dependence of the spectral patterns. The spectral components were assigned to the FeS I and α-NiS structures. The structural and spectroscopic studies show linear dependencies of unit cell parameters and spectral components on composition and confirm the existence of a series of monosulfide solid solution FexNi1−xS.

Intensifying Cyclopentanone Synthesis from Furfural Using Supported Copper Catalysts.

This work addresses catalytic strategies to intensify the synthesis of cyclopentanone, a bio-based platform chemical and a potential SAF precursor, via Cu-catalyzed furfural hydrogenation in aqueous media. When performed in a single step, using either uniform or staged catalytic bed configuration, high temperature and hydrogen pressures (180 °C and 38 bar) are necessary for maximum CPO yields (37 and 49 %, respectively). Parallel furanic ring hydrogenation of furfural and polymerisation of intermediates, namely furfuryl alcohol (FFA), limit CPO yields. Employing a two step configuration with optimal catalyst bed can curb this limitation. First, the furanic ring hydrogenation can be suppressed by using milder conditions (i. e., 150 °C and 7 bar, and 14 seconds of residence time). Second, FFA hydrogenation using tandem catalysis, i. e., a mix of β-zeolite and Cu/ZrO2, at 180 °C, 38 bar and 0.6, allows sufficient time for CPO formation and minimises polymerisation of FFA, thereby resulting in 60 % CPO yield. Therefore, this work recommends a split strategy to produce CPO from furfural. Such modularity may aid in addressing flexible market needs.

Innovative machine learning for drilling fluid density prediction: a novel central force search-adaptive XGBoost in HPHT environments

Oil and gas industries are facing a special dilemma when it comes to high-pressure, high-temperature (HPHT) drilling as the accurate forecasting of the drilling fluid density (DFD) is a vital factor for safe and efficient operations. Complicated relationships and inconsistencies in HPHT situations are rarely mapped by current forecasting models, while their buggy performance and safety risks during drilling can be underestimated. In this research, we propose a novel machine learning (ML) approach to enhance the accuracy of DFD anticipation under HPHT conditions: central force search-adaptive extreme gradient boosting (CFS-XGB). This paper uses a dataset that has drilling variables together with the DFD for HPHT situations to examine the accuracy of the CFS-XGB model. Excluding the abnormalities of data or mistakes, the reliability of the original data is maintained by applying min–max normalization. After that, finding the important features with the help of the boosted principal component analysis (BPCA) approach to the normalized data will ensure a major improvement in the CFS-XGB methodology’s prediction efficacy. This research is experimented in the Python platform, and the performance of the proposed CFS-XGB method is analyzed in terms of MSE, R2, and AAPRE metrics. The suggested approach performs better than the current methods in forecasting the drilling fluid concentration in HPHT settings, according to the experimental data. This development in predictive modeling helps increase the productivity and safety of drilling operations, which will eventually help the oil and gas sector manage the challenges posed by HPHT drilling settings.

Experimental Study on Cryogenic Compressed Hydrogen Jet Flames

Cryogenic compressed hydrogen (CcH2) technology combines the advantages of high pressure and low temperature to achieve high hydrogen storage density without liquefying the hydrogen, which has broad application prospects. However, the safety concerns related to cryogenic hydrogen need to be carefully addressed beforehand. In the present work, cryogenic hydrogen jet flames are experimentally investigated for various release pressures and initial temperatures. The flame length and thermal radiation flux were measured for horizontally releasing with nozzle diameters of 0.5–2 mm, temperatures ranging from 93 to 298 K, and initial pressures of 2–10 MPa. The results show that the flame length is dependent on the nozzle diameter, stagnation pressure and temperature. At a given pressure, the flame length, size and total radiant power increase with decreasing temperature, which is attributed to the lower jet flow velocity and higher density of low-temperature hydrogen. The normalized flame length Lf/D is correlated with the pressure ratio and temperature ratio. The correlation can be used to predict the flame length at various hydrogen pressures and temperatures. The normalized flame length of the cryogenic hydrogen jet flame is greater than that of the room-temperature hydrogen jet flame. The radiative heat flux of the flame can be predicted by the mass flow rate of the jet flow.