Pub Date : 2026-01-03DOI: 10.1016/j.jlp.2025.105909
Peng Gao , Jun-Cheng Jiang , Qian Xu , Jie Wu , Yan Tang , An-Chi Huang
This investigation establishes a source-term inversion framework for hazardous gas escapes in chemical industrial parks by employing a hybrid Genetic Algorithm–Particle Swarm Optimization (GA-PSO) and an enhanced Gaussian plume model. The following are the enhancements: a ground-reflection coefficient to mitigate boundary effects, an effective source height corrected by the jet trajectory under temperature differences and by leakage inclination, and search robustness through adaptive crossover/mutation and Sobol quasi-random initialization. Forward simulations are combined with concentration measurements along mobile patrol routes to estimate the location, release rate, and inclination of the breach. The proposed approach significantly reduces relative errors in comparison to the conventional plume model. It provides the greatest performance at low wind speeds and denser sensor spacing, while accuracy is degraded by higher winds or sparse sensors. The sensitivity to wind speed and monitoring distance is quantified, providing actionable guidance for rapid localization and emergency response in chemical parks.
{"title":"Inversion of the source of gas pipeline leaks using a Gaussian plume optimization approach","authors":"Peng Gao , Jun-Cheng Jiang , Qian Xu , Jie Wu , Yan Tang , An-Chi Huang","doi":"10.1016/j.jlp.2025.105909","DOIUrl":"10.1016/j.jlp.2025.105909","url":null,"abstract":"<div><div>This investigation establishes a source-term inversion framework for hazardous gas escapes in chemical industrial parks by employing a hybrid Genetic Algorithm–Particle Swarm Optimization (GA-PSO) and an enhanced Gaussian plume model. The following are the enhancements: a ground-reflection coefficient to mitigate boundary effects, an effective source height corrected by the jet trajectory under temperature differences and by leakage inclination, and search robustness through adaptive crossover/mutation and Sobol quasi-random initialization. Forward simulations are combined with concentration measurements along mobile patrol routes to estimate the location, release rate, and inclination of the breach. The proposed approach significantly reduces relative errors in comparison to the conventional plume model. It provides the greatest performance at low wind speeds and denser sensor spacing, while accuracy is degraded by higher winds or sparse sensors. The sensitivity to wind speed and monitoring distance is quantified, providing actionable guidance for rapid localization and emergency response in chemical parks.</div></div>","PeriodicalId":16291,"journal":{"name":"Journal of Loss Prevention in The Process Industries","volume":"100 ","pages":"Article 105909"},"PeriodicalIF":4.2,"publicationDate":"2026-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145938719","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-31DOI: 10.1016/j.jlp.2025.105906
Tianyu Zhou, Zhixiang Xing, Longtai Qi, Yecheng Liu
Ammonium polyphosphate was successfully encapsulated within a urea-formaldehyde resin shell via in-situ polymerization, yielding flame-retardant microcapsules. The synthesized microcapsules exhibited effective flame retardancy, as confirmed by various characterization techniques and ignition tests. The synthesized flame-retardant microcapsules (APP@UF) were uniformly integrated into the electrolyte matrix and subsequently assembled into electrochemical cells for performance evaluation. During thermal runaway in lithium-ion batteries, the internal temperature escalates. Upon reaching 210 °C, the microcapsule shell undergoes rupture, releasing APP to suppress the thermal runaway reactions within the battery, thereby achieving lithium-ion battery safety based on the concept of active protection. Furthermore, the microcapsules demonstrated stable dispersion in commercial lithium-ion electrolytes. Coin cells were assembled using electrolyte mixtures containing varying mass fractions of the microcapsules. At an addition level of 2 wt%, the battery retained 85.52 % of its capacity after 100 cycles under constant current charge-discharge conditions. The incorporation of microcapsules enhances battery safety without compromising electrochemical performance, presenting a viable strategy for improving the initial safety of lithium-ion batteries during thermal runaway.
{"title":"Enhancing the safety of lithium-ion batteries: synthesis and performance evaluation of APP@UF microcapsule electrolyte additives","authors":"Tianyu Zhou, Zhixiang Xing, Longtai Qi, Yecheng Liu","doi":"10.1016/j.jlp.2025.105906","DOIUrl":"10.1016/j.jlp.2025.105906","url":null,"abstract":"<div><div>Ammonium polyphosphate was successfully encapsulated within a urea-formaldehyde resin shell via in-situ polymerization, yielding flame-retardant microcapsules. The synthesized microcapsules exhibited effective flame retardancy, as confirmed by various characterization techniques and ignition tests. The synthesized flame-retardant microcapsules (APP@UF) were uniformly integrated into the electrolyte matrix and subsequently assembled into electrochemical cells for performance evaluation. During thermal runaway in lithium-ion batteries, the internal temperature escalates. Upon reaching 210 °C, the microcapsule shell undergoes rupture, releasing APP to suppress the thermal runaway reactions within the battery, thereby achieving lithium-ion battery safety based on the concept of active protection. Furthermore, the microcapsules demonstrated stable dispersion in commercial lithium-ion electrolytes. Coin cells were assembled using electrolyte mixtures containing varying mass fractions of the microcapsules. At an addition level of 2 wt%, the battery retained 85.52 % of its capacity after 100 cycles under constant current charge-discharge conditions. The incorporation of microcapsules enhances battery safety without compromising electrochemical performance, presenting a viable strategy for improving the initial safety of lithium-ion batteries during thermal runaway.</div></div>","PeriodicalId":16291,"journal":{"name":"Journal of Loss Prevention in The Process Industries","volume":"100 ","pages":"Article 105906"},"PeriodicalIF":4.2,"publicationDate":"2025-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145938717","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The nonlinear interactions of human, machine, environmental, and management factors within long-distance pipeline systems constitute complex scenarios of risk evolution. However, systematic research on the types, functions, and models of safety barriers applicable to risk management has not yet been carried out. Therefore, this study developed a risk management model that incorporates multiple strategies including hard measures, soft measures, support measures, and emergency measures based on the multi-dimensional safety barriers of engineering technology, maintenance, personnel operations, and emergency measures. First, through expert consultations and systematic coding, we analyzed fundamental attributes, including spatiotemporal distribution, risk characteristics, and control measures, of 2013 safety incidents from China's largest pipeline enterprise, and applied cluster analysis to systematically classify these incidents. Second, we used Social Network Analysis (SNA) to explore the network topology of risk factors and control measures across different safety incident types, thereby identifying critical control measures in the overall complex system. Finally, the integrated weights of the control measures were determined by combining the Analytic Hierarchy Process (AHP) with centrality metrics, thereby quantifying the effectiveness of control measures in the risk management model. The results show that static equipment, management execution, procedure compliance, and source control are critical control measures in the pipeline system risk framework, with calculated weights of 0.118, 0.115, 0.115, and 0.114, respectively. This study promotes a paradigm shift in risk management from linear management measures to systemic safety barriers.
{"title":"Risk management model for long-distance pipelines based on multi-dimensional safety barriers: An analytical framework in control measures research","authors":"Qian Wang , Fanjie Liang , Weichun Chang , Ruipeng Tong","doi":"10.1016/j.jlp.2025.105910","DOIUrl":"10.1016/j.jlp.2025.105910","url":null,"abstract":"<div><div>The nonlinear interactions of human, machine, environmental, and management factors within long-distance pipeline systems constitute complex scenarios of risk evolution. However, systematic research on the types, functions, and models of safety barriers applicable to risk management has not yet been carried out. Therefore, this study developed a risk management model that incorporates multiple strategies including hard measures, soft measures, support measures, and emergency measures based on the multi-dimensional safety barriers of engineering technology, maintenance, personnel operations, and emergency measures. First, through expert consultations and systematic coding, we analyzed fundamental attributes, including spatiotemporal distribution, risk characteristics, and control measures, of 2013 safety incidents from China's largest pipeline enterprise, and applied cluster analysis to systematically classify these incidents. Second, we used Social Network Analysis (SNA) to explore the network topology of risk factors and control measures across different safety incident types, thereby identifying critical control measures in the overall complex system. Finally, the integrated weights of the control measures were determined by combining the Analytic Hierarchy Process (AHP) with centrality metrics, thereby quantifying the effectiveness of control measures in the risk management model. The results show that static equipment, management execution, procedure compliance, and source control are critical control measures in the pipeline system risk framework, with calculated weights of 0.118, 0.115, 0.115, and 0.114, respectively. This study promotes a paradigm shift in risk management from linear management measures to systemic safety barriers.</div></div>","PeriodicalId":16291,"journal":{"name":"Journal of Loss Prevention in The Process Industries","volume":"100 ","pages":"Article 105910"},"PeriodicalIF":4.2,"publicationDate":"2025-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145880062","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-30DOI: 10.1016/j.jlp.2025.105907
Zainab Ali Bu Sinnah
Artificial Intelligence (AI) is increasingly transforming process safety by enabling early detection of equipment failures that could escalate into fires, explosions, or toxic releases. This study presents an interpretable hybrid machine learning framework that integrates ensemble tree classifiers with bio-inspired optimization algorithms for predictive maintenance in industrial settings. While demonstrated on CNC machinery, the framework is generalizable to safety-critical process equipment, enabling early detection of operational anomalies that could potentially escalate into process safety hazards. Using a twelve-month dataset of 2500 operating cycles from machinery representative of chemical and process plants, recursive feature elimination identified seven key process variables: hydraulic and coolant pressures, coolant and hydraulic-oil temperatures, spindle speed, torque, and cutting force that capture essential thermomechanical behavior associated with unsafe operating conditions. The hybrid models, validated through stratified 5-fold cross-validation, achieved test accuracies exceeding 0.98 and demonstrated robustness to industrial variability. Fourier Amplitude Sensitivity Test (FAST) analysis provided transparent, physically interpretable insights, highlighting torque and hydraulic pressure as dominant predictors of potential process hazards, while revealing synergistic effects of spindle speed and cutting force. By combining real-world sensor data, advanced optimization, and explainable AI, this framework enables proactive identification of safety-critical equipment degradation, supports inherently safer operations, and addresses key challenges of trustworthiness and interpretability in AI for process safety.
{"title":"Explainable AI-driven predictive maintenance for mitigating process safety risks in safety-critical industrial equipment","authors":"Zainab Ali Bu Sinnah","doi":"10.1016/j.jlp.2025.105907","DOIUrl":"10.1016/j.jlp.2025.105907","url":null,"abstract":"<div><div>Artificial Intelligence (AI) is increasingly transforming process safety by enabling early detection of equipment failures that could escalate into fires, explosions, or toxic releases. This study presents an interpretable hybrid machine learning framework that integrates ensemble tree classifiers with bio-inspired optimization algorithms for predictive maintenance in industrial settings. While demonstrated on CNC machinery, the framework is generalizable to safety-critical process equipment, enabling early detection of operational anomalies that could potentially escalate into process safety hazards. Using a twelve-month dataset of 2500 operating cycles from machinery representative of chemical and process plants, recursive feature elimination identified seven key process variables: hydraulic and coolant pressures, coolant and hydraulic-oil temperatures, spindle speed, torque, and cutting force that capture essential thermomechanical behavior associated with unsafe operating conditions. The hybrid models, validated through stratified 5-fold cross-validation, achieved test accuracies exceeding 0.98 and demonstrated robustness to industrial variability. Fourier Amplitude Sensitivity Test (FAST) analysis provided transparent, physically interpretable insights, highlighting torque and hydraulic pressure as dominant predictors of potential process hazards, while revealing synergistic effects of spindle speed and cutting force. By combining real-world sensor data, advanced optimization, and explainable AI, this framework enables proactive identification of safety-critical equipment degradation, supports inherently safer operations, and addresses key challenges of trustworthiness and interpretability in AI for process safety.</div></div>","PeriodicalId":16291,"journal":{"name":"Journal of Loss Prevention in The Process Industries","volume":"100 ","pages":"Article 105907"},"PeriodicalIF":4.2,"publicationDate":"2025-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145938721","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-30DOI: 10.1016/j.jlp.2025.105908
Hongwei Li , Cangsu Xu , Xiaolu Li , Francis Oppong , Wenjian Wei , Yuntang Li , Jia Sun
While ammonia combustion in oxygen-enriched conditions offers low-carbon potential, its explosive behavior under practical pressurization and preheating is not yet well understood. To address this gap, this study aims to characterize ammonia explosions in a 1.67 L constant-volume combustion chamber under oxygen-enriched conditions (25 % and 30 %), across equivalence ratios (Φ = 0.8–1.2), initial pressures (Pi = 1–3 bar), and initial temperatures (Ti = 313–373 K). Results indicate that with increasing initial pressure and oxygen concentration, the maximum explosion pressure (Pmax), maximum pressure rise rate (dP/dtmax), and deflagration index (KG) all increase, significantly enhancing explosion intensity. While Pmax, dP/dtmax, and KG exhibit low sensitivity to initial temperature. This simultaneously increases the combustion and explosion heat released rate (HRR) and elevates the maximum heat release rate (HRRmax). The heat loss (Qloss) decreases with rising oxygen concentration and initial temperature, but increases with a higher initial pressure. Chemical kinetics simulations reveal that the reactions R1 (H + O2 ⇔ O + OH), R50 (NH2 + HO2 ⇔ H2NO + OH), R48 (NH2 + NO ⇔ NNH + OH), and R157 (HNOH + NH2 ⇔ H2NN + H2O) are most sensitive to pressure changes, while Pmax exhibits a strong, nearly linear correlation with [H + O + OH]max. The global reaction pathway elucidates that the oxygen-enrichment enhances combustion efficiency and suppresses NOx accumulation by promoting the multi-step oxidation pathway of NH to generate N2. Under high-pressure conditions, the primary pathway for NO consumption shifts from N2O to NNH, thereby generating N2. These findings provide key insights for the safe utilization of oxygen-enriched ammonia combustion.
{"title":"Ammonia combustion under oxygen-enriched conditions: Explosion characteristics and chemical kinetic mechanism","authors":"Hongwei Li , Cangsu Xu , Xiaolu Li , Francis Oppong , Wenjian Wei , Yuntang Li , Jia Sun","doi":"10.1016/j.jlp.2025.105908","DOIUrl":"10.1016/j.jlp.2025.105908","url":null,"abstract":"<div><div>While ammonia combustion in oxygen-enriched conditions offers low-carbon potential, its explosive behavior under practical pressurization and preheating is not yet well understood. To address this gap, this study aims to characterize ammonia explosions in a 1.67 L constant-volume combustion chamber under oxygen-enriched conditions (25 % and 30 %), across equivalence ratios (<em>Φ</em> = 0.8–1.2), initial pressures (<em>P</em><sub>i</sub> = 1–3 bar), and initial temperatures (<em>T</em><sub>i</sub> = 313–373 K). Results indicate that with increasing initial pressure and oxygen concentration, the maximum explosion pressure (<em>P</em><sub>max</sub>), maximum pressure rise rate (<em>dP/dt</em><sub>max</sub>), and deflagration index (<em>K</em><sub>G</sub>) all increase, significantly enhancing explosion intensity. While <em>P</em><sub>max</sub>, <em>dP/dt</em><sub>max</sub>, and <em>K</em><sub>G</sub> exhibit low sensitivity to initial temperature. This simultaneously increases the combustion and explosion heat released rate (<em>HRR</em>) and elevates the maximum heat release rate (<em>HRR</em><sub>max</sub>). The heat loss (<em>Q</em><sub>loss</sub>) decreases with rising oxygen concentration and initial temperature, but increases with a higher initial pressure. Chemical kinetics simulations reveal that the reactions R1 (H + O<sub>2</sub> ⇔ O + OH), R50 (NH<sub>2</sub> + HO<sub>2</sub> ⇔ H<sub>2</sub>NO + OH), R48 (NH<sub>2</sub> + NO ⇔ NNH + OH), and R157 (HNOH + NH<sub>2</sub> ⇔ H<sub>2</sub>NN + H<sub>2</sub>O) are most sensitive to pressure changes, while <em>P</em><sub>max</sub> exhibits a strong, nearly linear correlation with [H + O + OH]<sub>max</sub>. The global reaction pathway elucidates that the oxygen-enrichment enhances combustion efficiency and suppresses NO<sub>x</sub> accumulation by promoting the multi-step oxidation pathway of NH to generate N<sub>2</sub>. Under high-pressure conditions, the primary pathway for NO consumption shifts from N<sub>2</sub>O to NNH, thereby generating N<sub>2</sub>. These findings provide key insights for the safe utilization of oxygen-enriched ammonia combustion.</div></div>","PeriodicalId":16291,"journal":{"name":"Journal of Loss Prevention in The Process Industries","volume":"100 ","pages":"Article 105908"},"PeriodicalIF":4.2,"publicationDate":"2025-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145880058","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-27DOI: 10.1016/j.jlp.2025.105904
Shuo Liu , Yanan Qian , Yi Yang , Yong Pan , Juncheng Jiang , Bing Sun , Yun-Ting Tsai
The present study examined the ability of varying loadings of methyldiethanolamine (MDEA) to inhibit presulphided bimetallic catalysts. Four catalysts containing 0, 1, 3, and 5 wt% nitrogen were prepared, and X-ray diffraction and X-ray photoelectron spectroscopy were employed to verify ex situ sulphidation. Fourier transform infrared spectroscopy was used to identify amino groups (–NH2); the relative concentrations of these groups increased with MDEA loading, indicating their central role in inhibiting catalysis. Scanning electron microscopy and ammonia temperature-programmed desorption results revealed that MDEA addition promoted microcrystal aggregation and reduced total acidity by 37.9 %, 49.0 %, and 28.9 % after 1, 3, and 5 wt% nitrogen incorporation, respectively. Specifically, weak acid sites were reduced by 27.0 % and 31.9 %, whereas medium-strength acid sites were reduced by 49.7 % and 67.5 % in the 1 and 3 wt% nitrogen-modified catalysts, respectively. These findings suggest that the –NH2 groups primarily inhibited catalysis by interacting with medium-strength acid sites. The differential scanning calorimetry results revealed that catalyst stability first increased before decreasing with increasing MDEA content, however, it remained consistently higher than that of the catalyst without basic nitrogen compounds, reaching the maximum value at 3 wt% loading. These results demonstrate that the functional nitrogen compounds inhibited the activity and enhanced the stability of the presulphided bimetallic catalysts.
{"title":"Inhibition of presulphided bimetallic catalysts by functional nitrogen compounds","authors":"Shuo Liu , Yanan Qian , Yi Yang , Yong Pan , Juncheng Jiang , Bing Sun , Yun-Ting Tsai","doi":"10.1016/j.jlp.2025.105904","DOIUrl":"10.1016/j.jlp.2025.105904","url":null,"abstract":"<div><div>The present study examined the ability of varying loadings of methyldiethanolamine (MDEA) to inhibit presulphided bimetallic catalysts. Four catalysts containing 0, 1, 3, and 5 wt% nitrogen were prepared, and X-ray diffraction and X-ray photoelectron spectroscopy were employed to verify ex situ sulphidation. Fourier transform infrared spectroscopy was used to identify amino groups (–NH<sub>2</sub>); the relative concentrations of these groups increased with MDEA loading, indicating their central role in inhibiting catalysis. Scanning electron microscopy and ammonia temperature-programmed desorption results revealed that MDEA addition promoted microcrystal aggregation and reduced total acidity by 37.9 %, 49.0 %, and 28.9 % after 1, 3, and 5 wt% nitrogen incorporation, respectively. Specifically, weak acid sites were reduced by 27.0 % and 31.9 %, whereas medium-strength acid sites were reduced by 49.7 % and 67.5 % in the 1 and 3 wt% nitrogen-modified catalysts, respectively. These findings suggest that the –NH<sub>2</sub> groups primarily inhibited catalysis by interacting with medium-strength acid sites. The differential scanning calorimetry results revealed that catalyst stability first increased before decreasing with increasing MDEA content, however, it remained consistently higher than that of the catalyst without basic nitrogen compounds, reaching the maximum value at 3 wt% loading. These results demonstrate that the functional nitrogen compounds inhibited the activity and enhanced the stability of the presulphided bimetallic catalysts.</div></div>","PeriodicalId":16291,"journal":{"name":"Journal of Loss Prevention in The Process Industries","volume":"100 ","pages":"Article 105904"},"PeriodicalIF":4.2,"publicationDate":"2025-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145880060","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-24DOI: 10.1016/j.jlp.2025.105902
Xinglin Wen , Junjie Gu , Yong Pan , Ahmed Mebarki , Juncheng Jiang
Catalytic hydrogenation serves as a cornerstone technology in the fine chemical and pharmaceutical sectors, offering substantial benefits in atom economy and resource efficiency. However, the development of highly efficient catalysts remains constrained by safety risks under harsh operating conditions and the flammability of hydrogen. Focusing on the representative nitrobenzene (NB) hydrogenation system, which yields core products including aniline (AN) and cyclohexylamine (CHA), this review systematically traces the development of catalysts for aromatic nitro-compound hydrogenation. It highlights rational nanostructural design strategies, including encompassing nanostructured catalysts, single atom catalysts, and metal-organic framework (MOF) composites, to achieve high activity and selectivity. Furthermore, we analyze metal-support interactions in both noble (Ru, Pd, Pt) and non-noble (Ni, Co, Fe) metal systems, with emphasis on support-derived electronic and spatial effects in representative catalysts (e.g., Pt/CeO2, Ru/NC). The reaction mechanism of NB hydrogenation is elucidated in terms of substrate adsorption configurations, hydrogen activation pathways, and hydrogen spillover, which collectively underpin safe reaction control. Key structural modulation approaches such as alloying/doping, hollow architecture design, and facet engineering are also summarized. Finally, the review outlines future challenges and opportunities in balancing catalytic performance with process safety, providing theoretical support for the development of catalysis science.
{"title":"Safety-oriented catalytic hydrogenation based on supported catalysts: research progress and perspectives","authors":"Xinglin Wen , Junjie Gu , Yong Pan , Ahmed Mebarki , Juncheng Jiang","doi":"10.1016/j.jlp.2025.105902","DOIUrl":"10.1016/j.jlp.2025.105902","url":null,"abstract":"<div><div>Catalytic hydrogenation serves as a cornerstone technology in the fine chemical and pharmaceutical sectors, offering substantial benefits in atom economy and resource efficiency. However, the development of highly efficient catalysts remains constrained by safety risks under harsh operating conditions and the flammability of hydrogen. Focusing on the representative nitrobenzene (NB) hydrogenation system, which yields core products including aniline (AN) and cyclohexylamine (CHA), this review systematically traces the development of catalysts for aromatic nitro-compound hydrogenation. It highlights rational nanostructural design strategies, including encompassing nanostructured catalysts, single atom catalysts, and metal-organic framework (MOF) composites, to achieve high activity and selectivity. Furthermore, we analyze metal-support interactions in both noble (Ru, Pd, Pt) and non-noble (Ni, Co, Fe) metal systems, with emphasis on support-derived electronic and spatial effects in representative catalysts (e.g., Pt/CeO<sub>2</sub>, Ru/NC). The reaction mechanism of NB hydrogenation is elucidated in terms of substrate adsorption configurations, hydrogen activation pathways, and hydrogen spillover, which collectively underpin safe reaction control. Key structural modulation approaches such as alloying/doping, hollow architecture design, and facet engineering are also summarized. Finally, the review outlines future challenges and opportunities in balancing catalytic performance with process safety, providing theoretical support for the development of catalysis science.</div></div>","PeriodicalId":16291,"journal":{"name":"Journal of Loss Prevention in The Process Industries","volume":"100 ","pages":"Article 105902"},"PeriodicalIF":4.2,"publicationDate":"2025-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145880059","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-24DOI: 10.1016/j.jlp.2025.105900
Fei Wang , Yu Peng , Jun He , Longlong Yang
The synergistic inhibitory impact of the two-phase inhibitor CO2/K2C2O4·H2O on methane/coal dust explosion was examined in this work. Variations in peak explosion overpressure, flame propagation dynamics, and deflagration flame temperature under various suppression settings were examined using a transparent horizontal explosion pipeline system. The combined application of 10 % CO2 and 200 g/m3 K2C2O4·H2O powder reduced the peak explosion overpressure by 91.5 %, the deflagration flame temperature by 28 %, and the flame length by 15.8 %. The results show that the suppression zone created by CO2/K2C2O4·H2O achieved a more significant inhibition effect compared to single inhibitors. We discovered that the dilution impact of CO2 and the potassium-containing compounds generated from the breakdown of K2C2O4·H2O can greatly lower the concentration of active free radicals in the combustion environment by using CHEMKIN to investigate the combined inhibitory mechanism of CO2/K2C2O4·H2O. The foundation of this study was a non-premixed suppression system made of CO2 and K2C2O4·H2O that was intended to inhibit developed flame and explosion propagation processes. The findings offer a theoretical foundation for the creation of multiphase inhibitors and hierarchical suppression systems.
{"title":"Experimental study on the synergistic inhibition of methane/coal dust explosion by CO2/K2C2O4·H2O","authors":"Fei Wang , Yu Peng , Jun He , Longlong Yang","doi":"10.1016/j.jlp.2025.105900","DOIUrl":"10.1016/j.jlp.2025.105900","url":null,"abstract":"<div><div>The synergistic inhibitory impact of the two-phase inhibitor CO<sub>2</sub>/K<sub>2</sub>C<sub>2</sub>O<sub>4</sub>·H<sub>2</sub>O on methane/coal dust explosion was examined in this work. Variations in peak explosion overpressure, flame propagation dynamics, and deflagration flame temperature under various suppression settings were examined using a transparent horizontal explosion pipeline system. The combined application of 10 % CO<sub>2</sub> and 200 g/m<sup>3</sup> K<sub>2</sub>C<sub>2</sub>O<sub>4</sub>·H<sub>2</sub>O powder reduced the peak explosion overpressure by 91.5 %, the deflagration flame temperature by 28 %, and the flame length by 15.8 %. The results show that the suppression zone created by CO<sub>2</sub>/K<sub>2</sub>C<sub>2</sub>O<sub>4</sub>·H<sub>2</sub>O achieved a more significant inhibition effect compared to single inhibitors. We discovered that the dilution impact of CO<sub>2</sub> and the potassium-containing compounds generated from the breakdown of K<sub>2</sub>C<sub>2</sub>O<sub>4</sub>·H<sub>2</sub>O can greatly lower the concentration of active free radicals in the combustion environment by using CHEMKIN to investigate the combined inhibitory mechanism of CO<sub>2</sub>/K<sub>2</sub>C<sub>2</sub>O<sub>4</sub>·H<sub>2</sub>O. The foundation of this study was a non-premixed suppression system made of CO<sub>2</sub> and K<sub>2</sub>C<sub>2</sub>O<sub>4</sub>·H<sub>2</sub>O that was intended to inhibit developed flame and explosion propagation processes. The findings offer a theoretical foundation for the creation of multiphase inhibitors and hierarchical suppression systems.</div></div>","PeriodicalId":16291,"journal":{"name":"Journal of Loss Prevention in The Process Industries","volume":"100 ","pages":"Article 105900"},"PeriodicalIF":4.2,"publicationDate":"2025-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145836591","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-24DOI: 10.1016/j.jlp.2025.105899
Yun-Ting Tsai , Jiarui Xu , Lin Ding , Yi Yang
Nitrocellulose (NC) is a highly flammable and explosive dangerous chemical that can cause thermal runaway accidents during storage and transportation. This study investigated the effects of five common metal carbonates (Na2CO3, Li2CO3, K2CO3, NaHCO3, and ZnCO3) on the thermal hazards and reaction kinetics of NC using differential scanning calorimetry (DSC) and a C80 microcalorimeter system. The results indicated that the addition of metal carbonates significantly reduced the initial decomposition temperature and the maximum exothermic temperature of NC, increased the heat of exotherm and decreased the reaction activation energy, accelerating the thermal decomposition process of NC. Among these, K2CO3, NaHCO3, and ZnCO3 showed noticeable catalytic effects, with K2CO3 exhibiting the most significant enhancement. Kinetic analysis based on the Kissinger method and the FWO method showed that K2CO3 significantly reduced the activation energy of NC, accelerating its decomposition process. The thermodynamic model further proved that K2CO3 significantly reduced the self-accelerating decomposition temperature of NC. The results revealed the serious incompatibility between NC and metal carbonates (especially K2CO3), exacerbating the thermal risk. Future studies should explore safer alternatives or stabilizers for NC-based systems.
{"title":"Influence and thermodynamic study of metal carbonates on the thermal hazards of nitrocellulose fibers","authors":"Yun-Ting Tsai , Jiarui Xu , Lin Ding , Yi Yang","doi":"10.1016/j.jlp.2025.105899","DOIUrl":"10.1016/j.jlp.2025.105899","url":null,"abstract":"<div><div>Nitrocellulose (NC) is a highly flammable and explosive dangerous chemical that can cause thermal runaway accidents during storage and transportation. This study investigated the effects of five common metal carbonates (Na<sub>2</sub>CO<sub>3</sub>, Li<sub>2</sub>CO<sub>3</sub>, K<sub>2</sub>CO<sub>3</sub>, NaHCO<sub>3</sub>, and ZnCO<sub>3</sub>) on the thermal hazards and reaction kinetics of NC using differential scanning calorimetry (DSC) and a C80 microcalorimeter system. The results indicated that the addition of metal carbonates significantly reduced the initial decomposition temperature and the maximum exothermic temperature of NC, increased the heat of exotherm and decreased the reaction activation energy, accelerating the thermal decomposition process of NC. Among these, K<sub>2</sub>CO<sub>3</sub>, NaHCO<sub>3</sub>, and ZnCO<sub>3</sub> showed noticeable catalytic effects, with K<sub>2</sub>CO<sub>3</sub> exhibiting the most significant enhancement. Kinetic analysis based on the Kissinger method and the FWO method showed that K<sub>2</sub>CO<sub>3</sub> significantly reduced the activation energy of NC, accelerating its decomposition process. The thermodynamic model further proved that K<sub>2</sub>CO<sub>3</sub> significantly reduced the self-accelerating decomposition temperature of NC. The results revealed the serious incompatibility between NC and metal carbonates (especially K<sub>2</sub>CO<sub>3</sub>), exacerbating the thermal risk. Future studies should explore safer alternatives or stabilizers for NC-based systems.</div></div>","PeriodicalId":16291,"journal":{"name":"Journal of Loss Prevention in The Process Industries","volume":"100 ","pages":"Article 105899"},"PeriodicalIF":4.2,"publicationDate":"2025-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145836622","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-24DOI: 10.1016/j.jlp.2025.105892
Yi-Hao Huang , Wun-Yu Chen , Yet-Pole I
This study presents a three-dimensional multi-hazard integrated risk analysis framework applicable to various confined industrial indoor environments or similar high-hazard facilities. The framework enables simultaneous assessment of fire, explosion, and toxic gas consequences and individual risk, addressing the limitations of traditional QRA tools in predicting complex three-dimensional hazard evolution within semiconductor cleanrooms and similar airflow-driven environments. As a result, it provides enhanced practical value and technical capability for comprehensive risk evaluation. The proposed approach incorporates two advanced computational fluid dynamics tools, the fire dynamics simulator (FDS), which is used for simulating fire behavior and smoke movement, and the flame acceleration simulator (FLACS), which is employed for modeling explosion dynamics and overpressure effects. These tools were applied to simulate representative accident scenarios including an isopropanol pool fire, a hydrogen explosion and ammonia gas dispersion, which are commonly encountered in semiconductor manufacturing. To quantify the risk to personnel, a customized risk analysis application was developed using the C# programming language. This application processes simulation data to calculate individual risk values. The system evaluates seven key hazard parameters, including thermal radiation from fire and explosion, carbon monoxide concentration, smoke density, overpressure, impulse pressure, and toxic gas dispersion. Maximum physical effects and fatality probabilities are also determined for each hazard. This framework integrates simulation results generated from different CFD grid systems and supports consequence analysis through dynamic visualization techniques. These include iso-surface rendering, cross-sectional plots and time-sequenced animation. Under worst-case conditions where protective or mitigation measures fail, the estimated individual risk within the cleanroom environment ranges from 1.71 × 10−9 to 3.21 × 10−5 persons/year. The findings demonstrate that the simulation-driven methodology provides an effective tool for informing decision-making in managing fire, explosion and toxic gas risks. The developed approach offers a flexible and robust solution for conducting quantitative evaluations of cleanroom safety, enabling both toxic dispersion analysis and explosion overpressure evaluation.
{"title":"An integrated 3D risk analysis framework using CFD tools for fire, explosion, and toxic gas hazards in a semiconductor cleanroom","authors":"Yi-Hao Huang , Wun-Yu Chen , Yet-Pole I","doi":"10.1016/j.jlp.2025.105892","DOIUrl":"10.1016/j.jlp.2025.105892","url":null,"abstract":"<div><div>This study presents a three-dimensional multi-hazard integrated risk analysis framework applicable to various confined industrial indoor environments or similar high-hazard facilities. The framework enables simultaneous assessment of fire, explosion, and toxic gas consequences and individual risk, addressing the limitations of traditional QRA tools in predicting complex three-dimensional hazard evolution within semiconductor cleanrooms and similar airflow-driven environments. As a result, it provides enhanced practical value and technical capability for comprehensive risk evaluation. The proposed approach incorporates two advanced computational fluid dynamics tools, the fire dynamics simulator (FDS), which is used for simulating fire behavior and smoke movement, and the flame acceleration simulator (FLACS), which is employed for modeling explosion dynamics and overpressure effects. These tools were applied to simulate representative accident scenarios including an isopropanol pool fire, a hydrogen explosion and ammonia gas dispersion, which are commonly encountered in semiconductor manufacturing. To quantify the risk to personnel, a customized risk analysis application was developed using the C# programming language. This application processes simulation data to calculate individual risk values. The system evaluates seven key hazard parameters, including thermal radiation from fire and explosion, carbon monoxide concentration, smoke density, overpressure, impulse pressure, and toxic gas dispersion. Maximum physical effects and fatality probabilities are also determined for each hazard. This framework integrates simulation results generated from different CFD grid systems and supports consequence analysis through dynamic visualization techniques. These include iso-surface rendering, cross-sectional plots and time-sequenced animation. Under worst-case conditions where protective or mitigation measures fail, the estimated individual risk within the cleanroom environment ranges from 1.71 × 10<sup>−9</sup> to 3.21 × 10<sup>−5</sup> persons/year. The findings demonstrate that the simulation-driven methodology provides an effective tool for informing decision-making in managing fire, explosion and toxic gas risks. The developed approach offers a flexible and robust solution for conducting quantitative evaluations of cleanroom safety, enabling both toxic dispersion analysis and explosion overpressure evaluation.</div></div>","PeriodicalId":16291,"journal":{"name":"Journal of Loss Prevention in The Process Industries","volume":"100 ","pages":"Article 105892"},"PeriodicalIF":4.2,"publicationDate":"2025-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145938639","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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