Mechanism reduction for multicomponent surrogates: A case study using toluene reference fuels
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biofuels (including algae and biomass), hydrogen a↗
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On the application of betweenness centrality in chemical network analysis: Computational diagnostics and model reduction
Here, the concept of shortest path and betweenness centrality (BC) is introduced in combustion systems, with its application demonstrated in chemical network analysis and skeletal mechanism generation. After establishing the graphical representation of a chemical network for given pressure, temperature, and species concentrations, a metric BC is defined to rank the shortest paths passed by other nodes between the pair of source and target node, and as such captures the dominant indirect kinetic pathways between any pair of nodes in the network for computational diagnostics. As a result, the controlling pathways are retained by collecting the species with larger BC values. Such a notion then indicates that the index of importance of species could then be assigned based on their BC values to further guide skeletal mechanism generation. Unlike existing methods, the betweenness centrality approach takes into account of both the fluxes between species and their relative positioning within the chemical network. To demonstrate its potential utility to combustion studies, the approach was applied to the GRI-3.0, LLNL and USC-Mech II mechanisms to identify the important pathways in the chemical network at each local reaction state, and develop skeletal mechanisms from all reaction state samples in auto-ignition and perfectly stirred reactor (PSR) simulations. The performance of the BC ranking is compared to the methods of directed relation graph (DRG), DRG with error propagations (DRGEP) and sensitivity analysis (SA), and is shown to possess sufficient utility in producing skeletal mechanisms with good accuracy and flexibility for the cases studied.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Response of flame thickness and propagation speed under intense turbulence in spatially developing lean premixed methane–air jet flames
Direct numerical simulations of three-dimensional spatially-developing turbulent Bunsen flames were performed at three different turbulence intensities. We performed these simulations using a reduced methane–air chemical mechanism which was specifically tailored for the lean premixed conditions simulated here. A planar-jet turbulent Bunsen flame configuration was used in which turbulent preheated methane–air mixture at 0.7 equivalence ratio issued through a central jet and was surrounded by a hot laminar coflow of burned products. The turbulence characteristics at the jet inflow were selected such that combustion occured in the thin reaction zones (TRZ) regime. At the lowest turbulence intensity, the conditions fall on the boundary between the TRZ regime and the corrugated flamelet regime, and progressively moved further into the TRZ regime by increasing the turbulent intensity. The data from the three simulations was analyzed to understand the effect of turbulent stirring on the flame structure and thickness. Furthermore, statistical analysis of the data showed that the thermal preheat layer of the flame was thickened due to the action of turbulence, but the reaction zone was not significantly affected. A global and local analysis of the burning velocity of the flame was performed to compare the different flames. Detailed statistical averages of the flame speed were also obtained to study the spatial dependence of displacement speed and its correlation to strain rate and curvature.
36 MATERIALS SCIENCE↗
Additional chain-branching pathways in the low-temperature oxidation of branched alkanes
Chain-branching reactions represent a general motif in chemistry, encountered in atmospheric chemistry, combustion, polymerization, and photochemistry; the nature and amount of radicals generated by chain-branching are decisive for the reaction progress, its energy signature, and the time towards its completion. In this study, experimental evidence for two new types of chain-branching reactions is presented, based upon detection of highly oxidized multifunctional molecules (HOM) formed during the gas-phase low-temperature oxidation of a branched alkane under conditions relevant to combustion. The oxidation of 2,5-dimethylhexane (DMH) in a jet-stirred reactor (JSR) was studied using synchrotron vacuum ultra-violet photoionization molecular beam mass spectrometry (SVUV-PI-MBMS). Specifically, species with four and five oxygen atoms were probed, having molecular formulas of C 8 H 14 O 4 (e.g., diketo-hydroperoxide/keto-hydroperoxy cyclic ether) and C 8 H 16 O 5 (e.g., keto-dihydroperoxide/dihydroperoxy cyclic ether), respectively. The formation of C 8 H 16 O 5 species involves alternative isomerization of OOQOOH radicals via intramolecular H-atom migration, followed by third O 2 addition, intramolecular isomerization, and OH release; C 8 H 14 O 4 species are proposed to result from subsequent reactions of C 8 H 16 O 5 species. The mechanistic pathways involving these species are related to those proposed as a source of low-volatility highly oxygenated species in Earth's troposphere. At the higher temperatures relevant to auto-ignition, they can result in a net increase of hydroxyl radical production, so these are additional radical chain-branching pathways for ignition. Furthermore, the results presented herein extend the conceptual basis of reaction mechanisms used to predict the reaction behavior of ignition, and have implications on atmospheric gas-phase chemistry and the oxidative stability of organic substances.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Effect of turbulence–chemistry interactions on chemical pathways for turbulent hydrogen–air premixed flames
This paper considers the kinetic pathways of hydrogen oxidation in turbulent, premixed H 2 –air flames. It assesses the relative roles of different reaction steps in H 2 oxidation relative to laminar flames, and the degree to which turbulence–chemistry interactions alters the well understood oxidation pathway that exist in laminar flames. This is done by analyzing the turbulent, lean (Φ = 0.4), H 2 –air flame DNS database from Aspden et al. [17]. The relative roles of dominant reaction steps in heat release and radical formation/consumption are analyzed at different Karlovitz numbers and compared with laminar stretched flame calculations from counterflow flames and perfectly stirred reactors. It is found that both the progress variable conditioned and spatially integrated contributions of the dominant reactions remain qualitatively similar between a highly turbulent and a laminar unstretched flame. Larger changes, up to a factor of about two, occur in the relative roles of reactions with secondary influences on heat release and radical production/consumption. These results suggest that the kinetic routes through which H 2 is oxidized remain essentially constant between laminar, unstretched flames and high Karlovitz number flames.
Premixed flames↗
A comprehensive iso-octane combustion model with improved thermochemistry and chemical kinetics
Iso-Octane (2,2,4-trimethylpentane) is a primary reference fuel and an important component of gasoline fuels. Furthermore, it is a key component used in surrogates to study the ignition and burning characteristics of gasoline fuels. This paper presents an updated chemical kinetic model for iso-octane combustion. Specifically, the thermodynamic data and reaction kinetics of iso-octane have been re-assessed based on new thermodynamic group values and recently evaluated rate coefficients from the literature. The adopted rate coefficients were either experimentally measured or determined by analogy to theoretically calculated values. New alternative isomerization pathways for peroxy-alkyl hydroperoxide ($\dot{O}$OQOOH) radicals were added to the reaction mechanism. The updated kinetic model was compared against new ignition delay data measured in rapid compression machines (RCM) and a high-pressure shock tube. Our experiments were conducted at pressures of 20 and 40 atm, at equivalence ratios of 0.4 and 1.0, and at temperatures in the range of 632–1060 K. The updated model was further compared against shock tube ignition delay times, jet-stirred reactor oxidation speciation data, premixed laminar flame speeds, counterflow diffusion flame ignition, and shock tube pyrolysis speciation data available in the literature. Finally, the updated model was used to investigate the importance of alternative isomerization pathways in the low temperature oxidation of highly branched alkanes. When compared to available models in the literature, the present model represents the current state-of-the-art in fundamental thermochemistry and reaction kinetics of iso-octane; and thus provides the best prediction of wide ranging experimental data and fundamental insights into iso-octane combustion chemistry.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
A further experimental and modeling study of acetaldehyde combustion kinetics
Acetaldehyde is an important intermediate and a toxic emission in the combustion of fuels, especially for biofuels. To better understand its combustion characteristics, a detailed chemical kinetic model describing the oxidation of acetaldehyde has been developed and comprehensively validated against various types of literature data including laminar flame speeds, oxidation and pyrolysis in shock tubes, chemical structure of premixed flames, and low-temperature oxidation in jet-stirred reactors. To extend the validation range, the chemical structure of a counterflow flame fueled by acetaldehyde at 600 Torr has been measured using vacuum ultra-violet photoionization molecular-beam mass spectrometry. In addition, ignition delay times at 10 atm and 700-1100 K were measured in a rapid compression machine, and a negative temperature coefficient (NTC) behavior was observed. Here, the present kinetic model well reproduces the results of various acetaldehyde combustion experiments covering wide ranges of temperatures (300–2300 K) and pressures (0.02–10 atm), and explains well the observed NTC behavior based on the competition between multiple oxidation pathways for the methyl radicals and their self-recombination forming ethane, a relatively stable species at temperatures below 1000 K.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
An experimental and kinetic modeling study of the oxidation of hexane isomers: Developing consistent reaction rate rules for alkanes
Alkanes are key components in gasoline, jet and diesel fuels and considerably influence the combustion behavior of these fuels because of their wide range of reactivity. An improved understanding of their combustion behavior and the development of chemical kinetic models that can accurately simulate their combustion behavior are important for the development of next-generation internal-combustion and gas-turbine engines. The current work provides here improved insight into oxidation mechanisms of a representative family of hydrocarbon fuels, specifically the hexane isomers: n-hexane, 2-methylpentane, 3-methylpentane, 2,2-dimethylbutane and 2,3-dimethylbutane. These isomers provide carbon “skeletons” ranging from straight-chained to highly-branched and provide a framework for the subsequent development of kinetic mechanisms for larger alkanes. New ignition delay times for the four branched hexane isomers were measured in a high-pressure shock tube and in a rapid compression machine, both at stoichiometric conditions (φ = 1), p = 15 bar and X O2 = 21% over temperatures from 600 to1300 K. These data were combined with previously published measurements under the same conditions for the remaining n-hexane isomer to provide a complete body of experimental data for kinetic modeling analysis. In addition, very recent experimental measurements of individual intermediate chemical species concentrations from all five hexane isomers in a jet-stirred reactor are also included and provide another family of data for further assessment of hexane isomer reactivity. Different reactivities were observed for each hexane isomer in each experimental facility, resulting from differences in their molecular structures. Consistent reaction rate rules have been applied to develop a combined detailed chemical kinetic model for all five hexane isomers. Kinetic model validation studies are reported to show that the current model reproduces well the ignition delay times of all five alkane isomers, as well as their variations in reactivity over a wide range of temperatures and other operating conditions. Equally important, these results show that it is not necessary to have a separate, different kinetic model for each isomer of a family of alkane fuels and that a single, coherent, integrated set of reaction rate classes and rules is sufficient to accurately describe combustion rates of combustion of straight-chain n-alkanes and branched-chain alkane fuels. This suggests strongly that a single set of reaction classes and rate rules should be sufficient to describe combustion kinetics of alkane fuels of any size and degree of branching.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Cool flame chemistry of diesel surrogate compounds: n -Decane, 2-methylnonane, 2,7-dimethyloctane, and n -butylcyclohexane
Elucidating the formation of combustion intermediates is crucial to validate reaction pathways, develop reaction mechanisms and examine kinetic modeling predictions. While high-temperature pyrolysis and oxidation intermediates of alkanes have been thoroughly studied, comprehensive analysis of cool flame intermediates from alkane autoxidation is lacking and challenging due to the complexity of intermediate species produced. Here, jet-stirred reactor autoxidation of four C 10 alkanes: n -decane, 2-methylnonane, 2,7-dimethyloctane, and n -butylcyclohexane, as model compounds of diesel fuel, was investigated from 500 to 630 K using synchrotron vacuum ultraviolet photoionization molecular beam mass spectrometry (SVUV-PIMS). Around 100 intermediates were detected for each fuel. The classes of molecular structures present during the autoxidation of the representative paraffinic functional groups in transport fuels, i.e., n -alkanes, branched alkanes, and cycloalkanes were established and were found to be similar from the oxidation of various alkanes. A theoretical approach was applied to estimate the photoionization cross sections of the intermediates with the same carbon skeleton as the reactants, e.g., alkene, alkenyl keto, cyclic ether, dione, keto-hydroperoxide, diketo-hydroperoxide, and keto-dihydroperoxide. These species are indicators of the first, second, and third O 2 addition reactions for the four C 10 hydrocarbons, as well as bimolecular reactions involving keto-hydroperoxides. Chemical kinetic models for the oxidation of these four fuels were examined by comparison against mole fraction of the reactants and final products obtained in additional experiments using gas chromatography analysis, as well as the detailed species pool and mole fractions of aforementioned seven types of intermediates measured by SVUV-PIMS. This works reveals that the models in the literature need to be improved, not only the prediction of the fuel reactivity and final products, but also the reaction network to predict the formation of many previous undetected intermediates.
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Data-driven selection of stiff chemistry ODE solver in operator-splitting schemes
Most computational fluid dynamics simulations of practical combustion applications employ operator-splitting schemes, where chemistry and transport are separated and integrated with distinct numerical methods. The changes in composition due to chemistry are evaluated by solving ordinary differential equations (ODE) in each cell of the computational domain, which typically dominates the computational cost when detailed chemistry is considered. In this work, a data-driven approach for the selection of chemistry ODE solvers in operator-splitting schemes is presented. Neural networks are used to predict the ODE solvers CPU times and errors for a given thermochemical state. This allows the selection of an optimal ODE solver on a cell-by-cell, timestep-by-timestep basis. The models are trained using a wide set of thermochemical states generated through partially-stirred reactors and flames simulations. The methodology is validated by quantifying the prediction errors, the classification accuracy, and the computational speedup. The model predicts the optimal ODE solver for 70 to 95% of the validation cases and decreases the computional cost by a factor of 3 or more. The generalizability of the methodology to different chemical mechanisms and different fuels is assessed and it is shown that the model’s performance is only slightly degraded and its applicability is significantly enhanced if the inputs to the neural networks are restricted to a small set of thermochemical state variables present in most chemical mechanisms. In conclusion, the models are used in an homogeneous reactor case and a multi-dimensional CFD simulation of a diesel spray at high pressure where a speedup of more than 3 is achieved.
42 ENGINEERING↗
An experimental and kinetic modeling study of cyclopentane and dimethyl ether blends
Cyclopentane is a suitable naphthene, or cycloalkane, in a palette for multi-component gasoline surrogate fuels due to its presence in market fuels and its relevance to alkyl substituted cyclopentanes also present. However, the previous oxidation studies of cyclopentane have primarily focused on neat mixtures. Blending cyclopentane with dimethyl ether in this work therefore serves to inform our understanding of, and improve predictive models for, multi-component mixtures. Here, the auto-ignition of cyclopentane/dimethyl ether blends was studied in a high-pressure shock tube and in a rapid compression machine. A wide range of temperatures (650 – 1350 K) and elevated pressures of 20 and 40 bar were studied at equivalence ratios of 0.5, 1.0 and 2.0 in air for two blending ratios (30/70 and 70/30 mole% cyclopentane/di-methyl ether mixtures). A detailed kinetic model for cyclopentane was revised to capture the measured ignition delay times and apparent heat release rates in this study. Literature ignition delay time, jet-stirred reactor, and laminar burning velocity measurements of neat cyclopentane were used as additional validation. Improvements to the kinetic model were based on recent literature studies related to sub-models including cyclopentene and cyclopentadiene which allowed the removal of previous local rate-constant optimizations. Low temperature reactivity of cyclopentane was found to be controlled by the branching ratio between concerted elimination of HO͘ 2 and the strained formation of Q̇OOH radicals in agreement with previous studies. In this study, the low branching ratio of Q̇OOH formation increases the influence of a competing consumption pathway for cyclopentyl-peroxy (CPTO͘ 2 J) radicals. The sensitivity of the simulated ignition delay times to the formation of cyclopentyl hydroperoxide (CPTO 2 H), from CPTO͘ 2 J and HO͘ 2 , is discussed. The current model is used to analyze the influence of dimethyl ether on the reactivity of cyclopentane in the context of previous literature studies of dimethyl ether binary blends with ethanol and toluene.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Probing O 2 -dependence of tetrahydrofuranyl reactions via isomer-resolved speciation
Low-temperature oxidation of tetrahydrofuran involves competing reactions that depend on temperature, pressure, and oxygen concentration, including ring-opening and subsequent oxidation of initial radicals ($\dot{R}$), HOO-elimination yielding dihydrofuran isomers, and the formation of peroxy radicals ($RO\dot{O}$). Here, the latter species, upon isomerization, lead to hydroperoxy-substituted radicals ($\dot{Q}OOH$) that undergo reaction either via unimolecular decomposition or second-O 2 -addition. Quantitative measurements of partially oxidized intermediates formed from each type of reaction provide critical constraints that are required for accurate modeling of combustion. To examine the influence of temperature and oxygen concentration on intermediates from tetrahydrofuran, isomer-resolved speciation measurements were conducted at 810 Torr in a jet-stirred reactor (JSR) from 500 – 1000 K. Resulting from negative-temperature coefficient behavior, species concentrations peaked at two temperatures, 600 K and 800 K, which were then selected for separate experiments to quantify O 2 -dependence using concentrations of 0.37 • 10 18 – 7.40 • 10 18 molecules cm –3 .
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Autoignition of cyclohexane at low-to-intermediate temperatures: Rapid compression machine experiments and improved comprehensive chemical kinetic model
Cycloalkanes are an important class of hydrocarbons found in conventional and alternative transportation fuels. Being one of the simplest practical cycloalkanes, cyclohexane is often used as a surrogate in studies to understand the oxidation, ignition, and sooting characteristics of cycloalkanes more broadly. Although cyclohexane has been extensively studied, very limited datasets for cyclohexane oxidation at low-to-intermediate temperatures are available in the literature. Moreover, the literature autoignition data from rapid compression machines (RCMs) did not provide information on volume histories or experimental heat transfer characteristics which can significantly impact model predictions, thereby hindering the detailed validation of chemical kinetic models. It has also been observed that the cyclohexane kinetic models developed so far are not able to predict the literature data across a wide range of operating and mixture conditions. Hence, further studies are recommended to understand and improve model predictions for cyclohexane oxidation. In this study, RCM experiments were conducted using cyclohexane/air mixtures at varying compressed pressures (P C =15, 20, and 30 bar), equivalence ratios (ϕ=0.5, 1.0, and 2.0), and compressed temperatures (T C =670–960 K). The current RCM results of cyclohexane were found to complement well with the literature data, with the first-stage IDTs at high pressures and volume histories at all test conditions being first reported for better development and validation of chemical kinetic models. Additionally, a detailed chemical kinetic model for the cyclohexane oxidation has been developed and validated using both newly acquired experimental IDTs in this study and literature experimental studies (IDTs in RCMs and STs, species profiles in jet-stirred reactors, and laminar burning velocities). Unlike literature models, the proposed model was observed to provide an overall better prediction for experimental results over a wide range of conditions. Chemical kinetic analysis of the developed model was further conducted to identify the reaction pathways controlling the autoignition of cyclohexane.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
A novel implicit hybrid machine learning model and its application for reinforcement learning
A novel methodology to develop implicit hybrid models is presented. PyTorch is used to integrate physics-based equations with machine learning models. Automatic differentiation of the hybrid model is leveraged to solve the implicit equations. Iterative solving enables gradient based updates to the machine learning model. The novel methodology is compared to an explicit hybrid approach on a continuously stirred tank reactor (CSTR). The novel method results in a lower modelling error. Both hybrid models effectively train with noisy data. To test the implicit hybrid model, it is employed as a reinforcement learning (RL) training model. The RL algorithm trained on the hybrid model outperforms real time optimization of the CSTR and performs nearly as well as RL trained directly on the CSTR and a traditional gradient based approach. Training RL directly on the CSTR requires over 60,000 system interactions compared to 6000 historical data points for hybrid model development.
42 ENGINEERING↗
Physics-guided neural networks with engineering domain knowledge for hybrid process modeling
As neural networks are more frequently used to solve problems in science and engineering, the methods used to incorporate scientific knowledge into these networks are becoming increasingly complex. Here, this work breaks down these complicated techniques into a set of basic strategies which can easily be applied to diverse situations. Several novel neural networks are built using the categories laid out in this work. These networks are tested on simulated data from a continuous stirred tank reactor (CSTR) model to evaluate the advantages provided by each network. The three points demonstrated in this work are: (1) architectural hybrid models can speed up convergence and reduce the amount of data necessary to train a model; (2) adding a physics-guided loss function can improve model generalization and make models more physically consistent; (3) using physics-guided initialization and transfer learning improves accuracy and speeds up convergence, but can harm generalizability if used incorrectly.
42 ENGINEERING↗
High-Fidelity Simulations of Gravity Currents Using a High-Order Finite-Difference Spectral Vanishing Viscosity Approach
This numerical work investigates the potential of a high-order finite-difference spectral vanishing viscosity approach to simulate gravity currents at high Reynolds numbers. The method introduces targeted numerical dissipation at small scales through altering the discretisation of the second derivatives of the viscous terms in the incompressible Navier-Stokes equations to mimic the spectral vanishing viscosity (SVV) operator, originally designed for the regularisation of spectral element method (SEM) solutions of pure advection problems. Using a sixth-order accurate finite-difference scheme, the adoption of the SVV method is straightforward and comes with a negligible additional computational cost. In order to assess the ability of this high-order finite-difference spectral vanishing viscosity approach, we performed large-eddy simulations (LES) of a gravity current in a channelised lock-exchange set-up with our SVV model and with the well-known explicit static and dynamic Smagorinsky sub-grid scale (SGS) models. The obtained data are compared with a direct numerical simulation (DNS) based on more than 800 million mesh nodes, and with experimental measurements. A framework for the energy budget is introduced to investigate the behaviour of the gravity current. First, it is found that the DNS is in good agreement with the experimental data for the evolution of the front location and velocity field as well as for the stirring and mixing inside the gravity current. Secondly, the LES performed with less than 0.4% of the total number of mesh nodes compared to the DNS, can reproduce the main features of the gravity currents, with the SVV model yielding slightly more accurate results. It is also found that the dynamic Smagorinsky model performs better than its static version. For the present study, the static and dynamic Smagorinsky models are 1.8 and 2.5 times more expensive than the SVV model, because the latter does not require the calculation of explicit SGS terms in the Navier-Stokes equations nor spatial filtering operations.
direct numerical simulation↗
The kinetics of the reactions of ground-state NH with N 2 O and implications for ammonia combustion
Quantum chemistry and canonical transition state theory have been applied to derive rate constants k for reactions of 3 Σ − imidogen with nitrous oxide. 3 channels were quantified. The fastest leads to NNH+NO and may be summarized as k = 2.8 × 10 7 T 1.68 exp.(−23.1 kcal mol −1 /RT) cm 3 mole −1 s −1 . Two much slower pathways lead to N 2 + 3 HNO and spin-forbidden 1 HNO. Modeling of literature data, from an NH 3 /O 2 flame and jet-stirred reactor measurements on dilute NH 3 /N 2 O mixtures, with the new kinetic information suggests that these channels are too slow to consume N 2 O significantly, and confirms that a widely used proposed rate constant for NH+N 2 O overestimates the reactivity.
Marshall, Paul [University of North Texas, Denton,↗
Recycling of waste automotive laminated glass and valorization of polyvinyl butyral through mechanochemical separation
Due to strong binding, optical clarity, adhesion to many surfaces, toughness and flexibility polyvinyl butyral (PVB) resin films are commonly used in the automotive and architectural application as a protective interlayer in the laminated glass. Worldwide million tons of PVB waste generated from end-of-life automotive associated with various environmental issues. Stringent environmental directive, higher land cost eliminates land filling option, needs a study, we have developed a mechanochemical separation process to separate PVB resins from glass and characterized the separated PVB through various techniques, i.e., scanning electron microscope (SEM), energy-dispersive X-ray spectroscopy (EDS), infrared spectroscopy (IR) and nuclear magnetic resonance spectroscopy (NMR). Commercial nonionic surfactants D201 used for the mechanochemical separation purpose. Through parameter optimization following conditions are considered to be the optimum condition; 30 vol% D201, stirring speed of 400 rpm, 35 °C temperature, operation time 1 h, and dilute D201 volume to waste automotive laminated glass weight ratio of ≈25. The technology developed in our laboratory is sustainable, environmentally friendly, techno-economical feasible process, capable of mass production (recycling). - Highlights: • Waste automotive laminated glass and polyvinyl butyral mechanochemically separated. • An economical total recovery and environment-friendly process has been developed. • It is a global problem rather than regional environmental issue has been addressed. • Without using hazardous chemical wastes are being converted to a wealth.
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