Search

Petroleum molecular reconstruction method can be used to calculate molecular composition from limited analytical data, which is the basis of the molecular‐level process modeling of petroleum refining. However, due to the problem of multiple solutions, it is difficult to obtain accurate and stable molecular compositional models. Therefore, based on the traditional bulk property constraints, composition similarity was proposed and a new petroleum molecular reconstruction method was proposed. In this article, diesel is taken as the study object, and the method was applied to construct various diesel compositional models. The results showed that the models' bulk properties and molecular fraction distribution were consistent with the experimental data. Finally, the method was applied to construct diesel compositional models of an actual refinery. With the reference oil compositional model as the molecular reference data, the problem of accurate construction of compositional models in a long‐term production process without detailed characterization data was solved. [ABSTRACT FROM AUTHOR]

Abstract Objective: We examined the use of comprehensive and targeted polymerase chain reaction (PCR) of Clostridioides difficile infection (CDI) among immunocompetent patients with and without CDI risk factors across different outpatient settings. A priori, we expected patients with higher CDI risk to be associated with targeted testing to reflect providers incorporating pretest risk factors in their choice of test assay. Design: Retrospective analysis of adult patients from clinic, emergency room, and non-medically acute inpatient settings. Setting: A tertiary academic medical center offering inpatient and outpatient medical, surgical, mental health, and rehabilitation services to Veterans across the Puget Sound region. Patients: Immunocompetent adult patients with ≥1 stool PCR assay performed between January 2016 and December 2019. Intervention: Patients were tested with either a specific tcdB PCR assay or a comprehensive gastrointestinal PCR panel that tests for 22 pathogens. Results: A total of 2,717 tests (74% targeted, 26% comprehensive) were obtained from 2,156 patients, among which 13% detected C. difficile and 7% detected other organisms. The proportion of comprehensive PCR tests increased nearly four-fold from 2016 to 2019 in clinic and emergency room settings, independent of CDI risk factors. Only two CDI risk factors (prior history of CDI and antibiotic use within three months before testing) were associated with increased targeted testing. Conclusion: The use of comprehensive GI PCR among immunocompetent adults with diarrhea is increasing in the outpatient setting. There may be an opportunity for diagnostic stewardship by nudging providers to consider all CDI risk factors at the time of test selection.

We proposed a fast method to solve the petroleum molecular reconstruction problem via initial guess estimation coupled with local optimization algorithm. A virtual oil database was constructed. After inputting the bulk properties of the target oil, several virtual oils with similar bulk properties were selected and their model parameters were used as the initial guesses. Subsequently, we proved that by using a local optimization method, the optimal model parameters can be rapidly obtained. The diesel and vacuum gas oil compositional models were exemplified as case studies. The results show that the proposed method presented faster computational time, which is within the range of 20–50 times that of frequently used global algorithms. Moreover, the optimal solution of the proposed method exhibited higher accuracy. In addition, the effect of the number of virtual oils and the parallel computation performance were also investigated. [ABSTRACT FROM AUTHOR]

In this presented work, a heavy petroleum fluid catalytic cracking (FCC) process model based on the use of a hybrid structural unit and bond‐electron matrix (SU‐BEM) framework on a molecular level has been developed. The SU‐BEM uses a simplified structural unit to represent the petroleum's molecular structure and chemical conversion, while retaining substantial details regarding atom‐connectivity. The chemical reaction information from the FCC unit was characterized in terms of reaction rules, indicating the conversion between structural units. After implementing via iteration the reaction rules on feedstock molecules, a complex molecular reaction network was created, containing all the primary product molecules (~3,800) and the reactions (~7,500). Next, the process mathematical model was built, including the micro‐kinetic model and the FCC unit reactor model. For validation purposes, the product yield was selected as a predicted variable. Following a parameter estimation procedure, a good agreement between the calculated and experimental values was observed. [ABSTRACT FROM AUTHOR]

For decades, laboratory managers in the area of molecular genetic testing have struggled to adapt to rapid technological change, growing demand, evolving regulatory frameworks, and frequently changing best practice guidelines. While impressive progress has been made, the scale and scope of these challenges is unlikely to decline in the near future. Instead the challenges are likely to become even more imposing as a result of the emerging new clinical applications, the need for increasingly comprehensive international regulatory and quality assurance frameworks, and the rapidly growing demand for molecular genetic testing in the developing world. All of these challenges can be expected to create new pressures in the areas of cost and efficiency. Efforts to increase the effectiveness and adaptability of quality assurance frameworks should be prioritized with increased attention by scholars, policymakers, and laboratory managers. This review will introduce and familiarize the reader with the basic historical trajectory for the development of quality management frameworks and standardization practices involved in the management of molecular genetic testing laboratories. This review will also identify recurrent dynamics that have posed challenges for quality assurance in the field. [ABSTRACT FROM AUTHOR]

Highlights • A hybrid framework combining structural units and a bond-electron matrix is proposed. • Flexibility of the probability density functions (PDFs) set-up module. • Applicability of the method to different petroleum fractions from diesel to slurry oil. Abstract In this paper, we developed a method to represent petroleum molecules and reconstruct the molecular composition of petroleum fractions. A hybrid framework combining structural units and a bond-electron matrix (SU-BEM) was proposed to represent petroleum molecules in a convenient way and retain all the detailed atomic information. The structural units and bond-electron matrix represent the basic structural components and the atom connectivity of petroleum molecules, respectively. The group contribution method was implemented in the framework to predict the physical and chemical properties of petroleum molecules based on their chemical structures. Good agreement was observed for the property calculations of pure low-carbon number components. A flexible probability density function (PDF) sequence module was developed and used in the sampling procedure to obtain the molecular quantities used in the compositional models. The PDF parameters, as well as molecular compositions, were optimized by minimizing the differences between predicted and experimental properties. The method was validated for applications involving diesel, vacuum gas oil, and fluid catalytic cracking slurry oil. [ABSTRACT FROM AUTHOR]

Objective: We examined the use of comprehensive and targeted polymerase chain reaction (PCR) of Clostridioides difficile infection (CDI) among immunocompetent patients with and without CDI risk factors across different outpatient settings. A priori, we expected patients with higher CDI risk to be associated with targeted testing to reflect providers incorporating pretest risk factors in their choice of test assay., Design: Retrospective analysis of adult patients from clinic, emergency room, and non-medically acute inpatient settings., Setting: A tertiary academic medical center offering inpatient and outpatient medical, surgical, mental health, and rehabilitation services to Veterans across the Puget Sound region., Patients: Immunocompetent adult patients with ≥1 stool PCR assay performed between January 2016 and December 2019., Intervention: Patients were tested with either a specific tcdB PCR assay or a comprehensive gastrointestinal PCR panel that tests for 22 pathogens., Results: A total of 2,717 tests (74% targeted, 26% comprehensive) were obtained from 2,156 patients, among which 13% detected C. difficile and 7% detected other organisms. The proportion of comprehensive PCR tests increased nearly four-fold from 2016 to 2019 in clinic and emergency room settings, independent of CDI risk factors. Only two CDI risk factors (prior history of CDI and antibiotic use within three months before testing) were associated with increased targeted testing., Conclusion: The use of comprehensive GI PCR among immunocompetent adults with diarrhea is increasing in the outpatient setting. There may be an opportunity for diagnostic stewardship by nudging providers to consider all CDI risk factors at the time of test selection., Competing Interests: The authors declare that they have no conflict of interests to report., (© The Author(s) 2023.)

• WT-GA approach was proposed to analysis NIR spectra for the first time. • The obtained models could predict the distillation temperatures of diesel well. • Compared with the others, the proposed approach was more simple and effective. • This study provided the convenience of applications for on-line NIR detection. The distillation temperature of petroleum is the significant information for the determination of refinery operating conditions. As the standard laboratory test method, ASTM D86 is often cost, time-consuming and not well suitable for on-line determination. In this paper, we proposed a simple approach to the prediction the key temperatures in diesel distillation process based on the raw near infrared (NIR) spectra of samples. After the NIR spectrum was decomposed by discrete wavelet transform to get the different NIR sub-signals, the selected sub-signals by genetic algorithm (GA) were superposed to form the new effective signal. Then stepwise regression was employed to build the linear prediction models. The proposed strategy was applied to predict the five distillation temperatures of diesel simultaneously, and the obtained R p 2 values of independent external test set were more than 0.96 as well as the average relative errors (ARE) were lower than 1%, which showed that the predicted values were well correlated with the reference values. Compared with the other conventional methods, such as PLS, iPLS, siPLS and stepwise, the proposed approach could obtain more accurate and reliable prediction models. This study not only indicated the validity of the new approach, but also provided an important support for the further realization of on-line NIR detection to predict the distillation temperatures. [ABSTRACT FROM AUTHOR]

• Molecular-level coupling simulation can describe complex reaction network in refinery. • Molecular matrix with structure and composition can transmit information among units. • Simulation can reveal reaction pathways and synergistic effect of molecules. For the highly integrated system in the petrochemical industry, establishing a coupling simulation model for the units that were closely related at the molecular level was a big challenge due to the difficulty of massive and effective data interaction. Based on the structure-oriented lumping (SOL) method, the molecular composition matrix, which included material molecular information quantitatively, made it possible to build up the coupling simulation model. An interoperable molecular composition matrix including 1228 row vectors connected the delayed coking model and the hydrotreating model in series. The coupling simulation model of delayed coking and hydrotreating process was established at the molecular level. In addition to predicting the molecular composition of the products, the simulation model could track the reaction path and reflect the synergistic transformation effect of hydrocarbon and non-hydrocarbon molecules. And the simulation model could also quantitatively calculate the influence of changes in upstream reaction conditions on downstream products. The coupling simulation model provided useful explorations to achieve the petroleum molecular management throughout the whole petrochemical process. [ABSTRACT FROM AUTHOR]

[Display omitted] • A decoupled discretization strategy was proposed for molecular-level kinetic model. • A molecular-level diesel hydrotreating kinetic model was built to validate the strategy. • The strategy was applied to FCC and accurately calculated the product distribution. The molecular conversion of complex mixture involves a large number of species and reactions. The corresponding kinetic model consists of a series of ordinary differential equations with severe stiffness, leading to an exponentially growing computational time. To reduce the computational time, we proposed a mass-temperature decoupled discretization strategy for a large-scale molecular-level kinetic model. The method separates the mass balance and heat balance calculations in the rigorous adiabatic reactor model and divided the reactor into several isothermal segments. After discretization, the differential equations for heat balance can be replaced by algebraic equations between nodes. We used a molecular-level diesel hydrotreating kinetic model as the case to validate the proposed method. A good agreement between the discretization model and rigorous model was observed while the computational time was significantly shortened. Moreover, the method was also extended to heavy oil fluid catalytic cracking and accurately calculated the product composition and temperature distribution. [ABSTRACT FROM AUTHOR]

Early industrialism was influenced by the organization of cottage industries, and in a similar vein, many of today's creative industries emerge largely from networked small-scale initiatives or cultural scenes. Collaborations and interactions are the backbone of the contemporary Do-It-Yourself (DIY) or 'maker culture', a distributed milieu of open software programmers and hardware hackers, but also crafters, backyard tinkerers, hobbyists and homesteaders. The scene is held together by micro-management tactics, or 'molecular' management, using protocols to guide collaborative innovation and shared craft practices, forming an emergent and innovative creative cottage industry. The maker culture is thus less of a DIY and more a do-it-together culture, merging collaborative play and interactions, often for the sake of shared curiosity. The mindset of the participants is that of the explorative craftsman; using a practical attitude of sharing ideas, methods and skills among practitioners, and the interactions are managed in a flat and meshworked manner through the use of protocols. The text specifically examines the protocols of the maker movement, finding an immediate connection between hardware protocols, like the 'makers bill of rights' guiding the principles of open source hardware, and the principles reflected in the social protocols of two hacker spaces. The maker culture is not only a loose network of dispersed tinkerers, it is also a close-knit molecular assemblage of materials, tools, skills and makers. [ABSTRACT FROM AUTHOR]

[Display omitted] • A molecular-level heavy petroleum hydrotreating model was developed. • FT-ICR MS data was used to verify the model. • ~17,000 molecules and ~25,000 reactions were automatically generated. The establishment of a molecular-level process model is critical for heavy petroleum hydrotreating optimization. This paper focuses on constructing a heavy petroleum compositional model and hydrotreating process model with a more accurate molecular detail. Besides the bulk property data, the detail molecular characterization data from high-resolution mass spectrometry was used to guide the compositional and kinetic model development. Under the framework of structural unit and bond-electron matrix (SU-BEM), more than 12,000 representative molecules were constructed to form a heavy petroleum molecular structure library. The probability density functions (PDFs) were combined to constrain the molecular composition of the heavy petroleum. The optimal molecular composition was obtained by optimizing the PDFs parameters. 18 reaction rules were formulated to express the heavy petroleum molecular conversion pathways. The reaction network was generated automatically and transformed mathematically into a micro-kinetic model. The total numbers of involved reactions and molecules were ~ 25,000 and ~ 17,000, respectively. The model parameters were globally optimized according to experimental data. The model results show good agreement with the bulk property data. Moreover, the predicted molecular distribution and molecular conversion regulations are consistent with the high-resolution mass spectrometry data. [ABSTRACT FROM AUTHOR]

• A systematic gasoline molecular performance evaluation model was established. • The optimal gasoline molecules using advanced property prediction model was screened. • The molecular performance distribution characteristics of blending stocks were compared. • The effect of conversion pathway on the molecular performance was investigated. The future production of clean gasoline requires the evaluation of molecular performance. In this paper, we established a systematic performance evaluation model for molecules in the gasoline range. Antiknock, cleanliness, power, stability, and evaporation performance were investigated and are related to the production of high-quality and clean gasoline. Corresponding quantitative structure–property relationship (QSPR) models were developed to predict the octane number, yield sooting index (YSI), combustion heat, unsaturated bond content, and Reid vapor pressure. The obtained models precisely predict these key properties using only the molecular structure as the input. Several applications were made to show the benefit of the molecular performance evaluation model, including the screening of optimal gasoline molecules, the molecular performance distribution of gasoline mixtures, and the effect of the gasoline molecular conversion pathway. The developed model is potentially a useful tool for the identification of optimal gasoline molecules and related process design. [ABSTRACT FROM AUTHOR]