Intermediate Process Research Articles

Application of response surface methodology for the modelling and optimisation of bio-oil yield via intermediate pyrolysis process of sugarcane bagasse

ABSTRACT The search for renewable resources has grown globally as a result of the harmful effects of fossil fuel use on the environment, such as global warming and acid rain. Biomass fuels do not contribute to the accumulation of carbon dioxide in the atmosphere. This study utilised response surface methodology for the optimisation of pyrolysis process parameters (temperature, heating rate, reaction time, nitrogen flow rate, and particle size) at five levels of experimental runs to enhance bio-oil production from the intermediate pyrolysis of sugarcane bagasse. The bio-oil yield increased continuously with an increase in T (320–520°C) and H (7.5–12.5°C/min) due to complete pyrolysis, while a decrease in bio-oil was noticed at a T (520–720°C) and H (22.5–27.5°C/min) due to secondary cracking such as thermal cracking, repolymerisation and recondensation that might enhance the yield of NCG and biochar. The optimum bio-oil yield (46.7 wt%) was achieved at a temperature, reaction time, heating rate, nitrogen flow rate, and particle size of 493.7°C, 15.5 min, 24.5°C/min, 225 cm3/min, and 0.1 mm, respectively. Results showed that the predicted data closely correlated with the experimental data (p < 0.05, R2 = 0.9891). Hence, the model is suitable and can accurately predict the experimental data. The presence of alkene, alcohol, and ester makes the bio-oil applicable for energy generation to power heavy equipment, ships, compressor, and boilers. Likewise, the presence of by-products such as oleic acids, methyl ester, 9,17-octadecdienal, and 9,12-octadecadienoyl chloride makes it suitable as fuel for high-speed diesel engines, powering heavy machines, vehicle locomotion, marine equipment, mining types of machinery, and manufacturing industries.

Women directors, board attendance, and corporate financial performance

AbstractResearch Question/IssueUsing insights from an in‐depth qualitative interview study, we propose an input‐process‐output model where the link between women directors (input) and corporate financial performance (output) is mediated by board attendance and where board attendance serves as a proxy of several intermediate but latent board processes. Further, we dig deeper into the nonlinearities of female boardroom representation by analyzing in how far the postulated mediation depends on the number of women in the boardroom.Research Findings/InsightsAnalyzing quantitative data from German supervisory boards over an 11‐year period, we find the link between women directors and corporate financial performance to be partially mediated by board attendance, and we find the mediation to depend on whether there is more than just one “token” woman in the boardroom. When there is only one woman in the boardroom, her presence is positively linked to board attendance, but the higher board attendance does not to translate into a better corporate financial performance.Theoretical/Academic ImplicationsOur study contributes to theory, by inductively enriching our understanding of how and when women directors and corporate financial performance are linked.Practitioner/Policy ImplicationsOur study encourages firms to appoint more than one woman to the boardroom to profit from an enhanced board attendance that will then also translate into a better corporate financial performance.

Synergistic Effects of Phase Transition and Electron‐Spin Regulation on the Electrocatalysis Performance of Ternary Nitride

AbstractTransition metal nitrides (TMNs) have great potential use in energy storage and conversion owing to tunable electronic and bonding characteristics. Novel iron rich nitrides nanoparticles anchored on the N‐doped porous carbon, named as (CoxFe1–x)3N@NPC (0 ≤ x &lt; 0.5) are designed here. The synergistic effects of phase transition and electron‐spin regulation on oxygen electrocatalysis are testified. A core–shell structure of (CoxFe1–x)3N with high dispersibility is induced by an intermediate phase transition process, which significantly suppresses coarsening of the metallic nitrides. The Co incorporation regulates d‐band electrons spin polarization. The t2g5eg1 of FeII with the ideal eg electron filling boosts intrinsic activity. (Co0.17Fe0.83)3N@NPC with optimal cobalt content holds electronic configuration with moderate eg electron filling (t2g5eg1), which balances the adsorption of *O2 and the hydrogenation of *OH, improving bifunctional catalytic performances. Both liquid and solid‐state zinc–air batteries assembled based (Co0.17Fe0.83)3N@NPC cathodes substantially deliver higher peak power density and remarkable energy density.

The Additive-Subtractive Process Chain - a Review

In recent years, metal additive manufacturing developed intensively and became a relevant technology in industrial production of highly complex and function integrated parts. However, almost all additively manufactured parts must be post-processed in order to fulfil geometric tolerances, surface quality demands and the desired functional properties. Thus, additive manufacturing actually means the implementation of additive-subtractive process chains. Starting with the most relevant additive processes (powder-based PBF-LB, LMD-p and wire-based WAAM and LMD-w/WLAM), considering intermediate process steps (heat treatment and shot peening) and ending up with post-processing material removal processes (with defined and undefined cutting edges), this paper gives an overview of recent research findings with respect to a comprehensive scientific investigation of influences and interactions within the additive-subtractive process chain. This includes both the macroscopic geometric scale and the microscopic scale of the material structure. Finally, conclusions and future perspectives are derived and discussed.

Effective recovery of calcium and sulfur resources in FGD gypsum: Insights from the mechanism of reduction roasting and the conversion process of sulfur element

Flue gas desulfurized (FGD) gypsum is produced during the removal of SO2 from flue gas. The reductive decomposition of FGD gypsum to calcium sulfide (CaS) is a crucial method for resource utilization. This study investigated the reduction roasting behavior and mechanism to enrich and recycle the calcium and sulfur resources in FGD gypsum effectively. Firstly, thermodynamics calculation revealed that the complete reduction of CaSO4 to CaS is feasible. Experimental results showed that more than 95 % of the FGD gypsum can be reduced to CaS. Subsequently, the kinetic parameters of the reduction process were calculated. The results indicate that the reaction is controlled by the phase boundary, which is a typical shrinking sphere reaction process. Based on the kinetic study, the micromorphological transformation during the reduction process were studied. The results show that the reduction reaction initially starts from the boundary and gradually occurs towards the core. Finally, the reduction roasting mechanism is proposed. The intermediate processes of calcium sulfate reduction behavior were studied through XRD and XPS. The phase conversion and behavior of the main elements S in the process were explored. The results indicate that the process is a step-by-step reduction, and the transformation of S is SO42−-SO32−-S22−-S2−. The reduction product forms a hollowed-out spheroid structure that cannot only effectively enrich Ca and S resources, but also provide advantageous conditions for their subsequent reuse.

The Agulhas Current Transports Signals of Local and Remote Indian Ocean Nitrogen Cycling

AbstractThe greater Agulhas Current region is an important component of the climate system, yet its influence on carbon and nutrient cycling is poorly understood. Here, we use nitrate isotopes (δ15N, δ18O, Δ(15–18) = δ15N–δ18O) to trace regional water mass circulation and investigate nitrogen cycling in the Agulhas Current and adjacent recirculating waters. The deep and intermediate waters record processes occurring remotely, including partial nitrate assimilation in the Southern Ocean and denitrification in the Arabian Sea. In the thermocline and surface, tropically sourced waters are biogeochemically distinct from adjacent subtropically sourced waters, confirming inhibited lateral mixing across the current core. (Sub)tropical thermocline nitrate δ15N is lower (4.9–5.8‰) than the sub‐thermocline source, Subantarctic Mode Water (6.9‰); we attribute this difference to local N2 fixation. Using a one‐box model to simulate the newly fixed nitrate flux, we estimate a local N2 fixation rate of 7–25 Tg N.a−1, with the upper limit likely biased high. In the mixed layer, nitrate δ15N and δ18O rise in unison, indicating that phytoplankton nitrate assimilation dominates in surface waters, with nitrification restricted to deeper waters. Because nitrate assimilation and nitrification are vertically decoupled, the rate of nitrate assimilation plus N2 fixation can be used to approximate carbon export. Thermocline and mixed‐layer nitrate Δ(15–18) is low, due to both N2 fixation and coupled partial nitrate assimilation and nitrification. Similarly low‐Δ(15–18) nitrate in Agulhas rings indicates leakage of low‐δ15N nitrogen into the South Atlantic, which should be recorded in the organic matter sinking to the seafloor, providing a potential tracer of past Agulhas leakage.

Squeezing More Past Knowledge for Online Class-Incremental Continual Learning

Continual learning (CL) studies the problem of learning to accumulate knowledge over time from a stream of data. A crucial challenge is that neural networks suffer from performance degradation on previously seen data, known as catastrophic forgetting, due to allowing parameter sharing. In this work, we consider a more practical online class-incremental CL setting, where the model learns new samples in an online manner and may continuously experience new classes. Moreover, prior knowledge is unavailable during training and evaluation. Existing works usually explore sample usages from a single dimension, which ignores a lot of valuable supervisory information. To better tackle the setting, we propose a novel replay-based CL method, which leverages multi-level representations produced by the intermediate process of training samples for replay and strengthens supervision to consolidate previous knowledge. Specifically, besides the previous raw samples, we store the corresponding logits and features in the memory. Furthermore, to imitate the prediction of the past model, we construct extra constraints by leveraging multi-level information stored in the memory. With the same number of samples for replay, our method can use more past knowledge to prevent interference. We conduct extensive evaluations on several popular CL datasets, and experiments show that our method consistently outperforms state-of-the-art methods with various sizes of episodic memory. We further provide a detailed analysis of these results and demonstrate that our method is more viable in practical scenarios.

Formation of CH2O and UHC emissions during catalyst-heating operation in compression ignition engines: High-speed FID and mid-IR extinction diagnostics

To comply with increasingly stringent pollutant emissions regulations, catalyst-heating operation in diesel engines is critical to achieving rapid light-off of exhaust aftertreatment catalysts during the first minutes of cold start. Current approaches to catalyst-heating operation typically involve one or more late post injections to retard combustion phasing and increase exhaust gas temperatures. The ability to retard post injection timings while maintaining acceptable pollutant emissions levels is pivotal for improved catalyst-heating operations. This experimental study aims to provide further insight into unburned hydrocarbons (UHC) and formaldehyde (CH2O) formation under catalyst-heating operation.In this study, high-speed laser extinction based measurements of CH2O are demonstrated in an optically accessible exhaust runner, and high-speed UHC measurements are also performed using a fast flame ionization detector analyzer during catalyst-heating operation. Time-resolved CH2O and UHC emission measurements are used to analyze the effect of each injection event in a five-injection strategy (two pilots, one main and two posts) on the pollutant emissions. The first pilot injection generates a significant amount of UHC unevenly distributed in the chamber, with UHC trapped primarily in the upper-cylinder and inside-the-bowl regions. The fuel delivered with the second pilot injection partially burns the unburned fuel from the first pilot injection particularly in inner-bowl region, creating short-chain hydrocarbons corresponding to formation of CH2O. UHC is dramatically reduced in the presence of the main injection, reinforcing the hypothesis by showing large CH2O emission during intermediate and later exhaust process. The first post injection produces UHC and CH2O in the upper-cylinder area due to over-mixing, which is further promoted by the second post injection, while these post-injections do not substantially affect near-bowl emissions.

Adjusting microstructure and improving mechanical property of additive manufacturing 316L based on process optimization

In additive manufacturing (AM), printing defects or columnar-coarse grains due to an inappropriate process parameter often damage the mechanical properties of AM metals, which significantly reduce the quality and application fields of AM parts. In this work, the overlap ratio are optimized to adjust grain morphology and improve mechanical properties of 316L stainless steel fabricated by direct energy deposition (DED). In addition, the effects of fundamental process parameters (such as laser power, scanning speed, and overlap ratio) on the molten-pool size, density, grain morphology, and mechanical properties of DED-316L are systematically studied. By optimizing process parameters (such as overlap ratio, laser power, and scanning speed), the penetrating-columnar-grains morphology is eliminated, and a full dense (>99.9%) DED-316L with finer grains is achieved, without either adjusting the chemical composition of 316L or adding any intermediate processes (such as in-situ rolling, ultrasonic treatment, laser shock peening, or cryogenic cooling). Due to the refined grains and twinning induced plasticity (TWIP) effect, strength and plasticity of DED-316L are simultaneously enhanced. To be more specific, compared to Sample (overlap ratio-4%, laser power-720 W, scanning speed-8 mm/s) without process optimization, the tensile strength and yield strength of Sample (overlap ratio-70%, laser power-720 W, scanning speed-20 mm/s) with process optimization are individually improved by 20.3% and 18.4%, while the total elongation and uniform elongation are increased by 176.7% and 173%, respectively.

Tamil Speech Synthesizer App for Android: Text Processing Module Enhancement

Objectives: Designing dynamic computer systems that are effective, efficient, simple, and satisfying to use is becoming extremely important in this age of information and communication technology. Text to Speech or Speech Synthesis is one of the many methods being investigated by researchers to improve Human-Computer Interaction. The goal here is to improve the text processing component of the Tamil voice synthesizer by including a text normalizer and loan word identification that is efficient and reliable. Methods: Text normalization is conducted on unconstrained Tamil text to turn non-standard terms into common words to reduce confusing utterances during intermediate word processing. Loan/Native words in Tamil literature are detected to enhance the Tamil voice synthesizer system’s pronunciation model. Findings: During normalization, non-standard Tamil words are replaced with standard ones to reduce ambiguous utterances during interim processing. A pronunciation model is built to improve the Tamil speech synthesizer system by identifying loan words in Tamil text. A syllable classifier is presented in this study, based on a decision list approach, which can handle various types of non-stationary sounds. Novelty: We also disclose a ’loan/native word classifier’ based on multiple linear regressions that perform well even with small words of three syllables. Such sophisticated text processors are required in today’s dominating Digital, Information-Communication Technology, and Human-Computer Interaction age. Keywords: Mobile Communication Technology; HumanComputer Interaction; Speech Synthesis Affirms; Syllable Classifier; Prerecorded database

Aturan Hukum Lembaga Keuangan Mikro Syariah (Bmt Dan Koperasi Syariah) Beserta Akad Akadnya

Law No. 1 of 2013 concerning Microfinance Institutions was born, LKMS in Indonesia are known as Baitul Mal wa Tamwil (BMT) or Sharia Savings and Loans and Financing Cooperatives (KSPPS) which are generally incorporated as cooperatives. Based on sharia principles, cooperatives are legally incorporated under the supervision of the ministry of cooperatives and small and medium enterprises. The existence of this dualism of legal regulations has led to overlapping regulations, supervision and guidance by related agencies, as well as contradictions in the regulations between one another. This legal problem requires a solution through the reformulation of legal regulations relating to Islamic MFIs. Microfinance institutions (MFIs) in Indonesia are currently growing rapidly and have an important role in improving the people's economy. The rapid development of this MFI is because almost 51.2 million units or 99.9% of business actors in the Indonesian economy are dominated by micro and small business units (Ali sakti: 2013). MFIs can be said to be one of the important pillars in the financial intermediation process needed by small and medium-sized communities for consumption and production as well as storing their business results. In Indonesia, MFIs are regulated in Law no. 1 of 2013 concerning Microfinance Institutions. According to Article 1 (1) of Law no. 1 of 2013 concerning Microfinance Institutions, what is meant by MFIs are: financial institutions specifically established to provide business development services and community empowerment, either through loans or financing in micro-scale businesses to members and the public, managing deposits, as well as providing development consulting services business that is not solely for profit. Based on the definition above, it can be understood that an MFI is a financial institution that functions as an intermediary institution that aims not only to seek profit (profit motive), but also has other goals, namely social motives whose activities are more in the nature of community development.

Mating-Induced Common and Sex-Specific Behavioral, Transcriptional Changes in the Moth Fall Armyworm (Spodoptera frugiperda, Noctuidae, Lepidoptera) in Laboratory.

The intermediate process between mating and postmating behavioral changes in insects is still poorly known. Here, we studied mating-induced common and sex-specific behavioral and transcriptional changes in both sexes of Spodoptera frugiperda and tested whether the transcriptional changes are linked to postmating behavioral changes in each sex. A behavioral study showed that mating caused a temporary suppression of female calling and male courting behavior, and females did not lay eggs until the next day after the first mating. The significant differences on daily fecundity under the presence of males or not, and the same or novel males, suggest that females may intentionally retain eggs to be fertilized by novel males or to be fertilized competitively by different males. RNA sequencing in females revealed that there are more reproduction related GO (gene ontology) terms and KEGG (Kyoto encyclopedia of genes and genomes) pathways (mainly related to egg and zygote development) enriched to upregulated DEGs (differentially expressed genes) than to downregulated DEGs at 0 and 24 h postmating. In males, however, mating induced DEGs did not enrich any reproduction related terms/pathways, which may be because male reproductive bioinformatics is relatively limited in moths. Mating also induced upregulation on soma maintenance (such as immune activity and stress reaction) related processes in females at 0, 6 and 24 h postmating. In males, mating also induced upregulation on soma maintenance related processes at 0 h postmating, but induced downregulation on these processes at 6 and 24 h postmating. In conclusion, this study demonstrated that mating induced sex-specific postmating behavioral and transcriptional changes in both sexes of S. frugiperda and suggested that the transcriptional changes are correlated with postmating physiological and behavioral changes in each sex.

Combined wind lidar and cloud radar for high-resolution wind profiling

Abstract. This paper introduces an experimental setup for retrieving horizontal wind speed and direction profiles with a high temporal and vertical resolution for process studies and validation of convection-permitting model simulations. The CMTRACE (tracing convective momentum transport in complex cloudy atmospheres) campaign used collocated wind lidar and cloud radar measurements to retrieve seamless wind profiles from near the surface up to cloud tops. It took place in Cabauw, the Netherlands, between 13 September and 3 October 2021. The intermediate processing steps for generating the level 1 and level 2 data, such as second trip echoes filtering, offset correction, wind retrieval, re-gridding, and flagging, are described. In level 1 (https://doi.org/10.5281/zenodo.6926483, Dias Neto, 2022a), the data from lidar and radars are kept in the original spatial and temporal resolution, while in level 2 (https://doi.org/10.5281/zenodo.6926605, Dias Neto, 2022b), they are regridded to a common spatial and temporal resolution. Statistical analyses of the lidar's and radar's wind speed and direction profiles indicate a correlation higher than 0.95 for both variables. The bias of wind direction and speed calculated between radar's and lidar's observations are 0.24∘ and −0.16 m s−1, respectively. The foreseen initial application of the datasets includes the study of convective momentum transport and its validation in regional weather forecasts and large-eddy simulation hindcasts.

Diffusion Coupling Kinetics in Multisite Catalysis: A Microkinetic Framework

Multicomponent (or multisite) catalysts are gaining increasing importance and popularity in heterogeneous catalysis and yet the cooperation mechanism among them remains obscure and intriguing. In this work, a vital and characteristic phenomenon in the two-component catalytic systems, the diffusion of surface intermediates, and the induced activity enhancement by coupling with the surface reactions is systematically investigated with both rigorous theoretical deduction and microkinetic simulations. By virtue of the proposed pseudo-fluctuation method, a general analytical framework is established with the two-step reaction model and the influence and origin of intermediate diffusion are elaborated. We quantify that the difference of the chemical potential of surface intermediates on different sites leads to the diffusion and determines the diffusion flowing from the strong adsorption site to the weak adsorption site. More importantly, we demonstrate that an enhancement in the overall reaction rate can be achieved by integrating the advantages of different components. Specifically, the optimum promotion effect would appear when the adsorption abilities of the two-component catalysts for the surface intermediate are around the chemical potential of the reactant and product, respectively. From the aspect of practical preparation methods, the coupling kinetics of the mechanically mixed catalysts and the alloy-typed catalysts are theoretically compared and a preliminary strategy for choosing the coupled components is proposed. We believe that this work provides a fundamental insight into the understanding and manipulation of the intermediate diffusion process.

Promoting photoelectrochemical water oxidation of BiVO4 photoanode via Co-MOF-derived heterostructural cocatalyst

The sluggish surface reaction kinetic is the bottleneck limiting the photoelectrochemical (PEC) water oxidation of BiVO4 photoanode, especially for the porous structured BiVO4 with high surface area. Here, Co-based metal–organic frameworks (MOFs) were modified on porous BiVO4 photoanode followed by calcining in the N2 atmosphere, forming BiVO4-MOF-N2 photoanode. The MOF-derived heterostructural cocatalysts significantly enhanced the photocurrent density of BiVO4-MOF-N2, reaching 2.32 mA·cm−2 (1.23 V vs RHE), about 1.15 times that of BiVO4-MOF and 2.64 times that of pristine BiVO4. The comparative study of BiVO4-MOF-N2, BiVO4-MOF, and pristine BiVO4 photoanodes suggested that the Co-MOF-derived heterostructural cocatalyst had a much stronger effect on promoting the surface reactions than pure MOF. The BiVO4-MOF-N2 photoanode had the highest charge transfer efficiency of 63.1 % at 1.3 V vs RHE and the lowest charge transfer resistivity compared with BiVO4 and BiVO4-MOF. Both Co-active centers and conductive carbon matrix contributed to the enhanced charge transfer of BiVO4-MOF-N2 photoanode. A MOF-loading-time dependent PEC performance of BiVO4 photoanode also indicated that the intermediate charge transfer process from BiVO4 to active centers strongly affected the final charge transfer and PEC performances. This work provides new insights into the design of high-performance photoelectrochemical electrodes based on heterostructural cocatalysts.

Multi-physics coupling simulation investigation of semi-solid A380 aluminum alloy during intermediate frequency electromagnetic stirring process

Multi-physics coupling simulation investigation of semi-solid A380 aluminum alloy during intermediate frequency electromagnetic stirring process

Blockchain based Automated Construction Model Accuracy Prediction using DeepQ Decision Tree

A growth of Industry 4.0 standards are increasing day by day. Various research application and problem statements are coming to create multiple automation environments. Blockchain technology is the important evolution to produce dynamic and avoid intermediate middleware processing systems. In this paper we propose a blockchain based automated construction modelling and analysis system. Here we check the efficiency of the system by using collaboration, transparency, workflow and reliable data model. DeepQ based classification and prediction method is used to measure the accuracy index. Decision tree algorithm is used to divide the process model and generate the chain codes. 1500 trained dataset and 750 dataset is taken from Revit construction model set and apply blockchain codes to process the dataset. The simulations are taken effectively and reach the accuracy as 96%.

Inter-Industry Transfer of Intermediate Virtual Water Scarcity Risk: The Case of China

Multiple factors need to be considered when allocating water resources, among which water scarcity risk is often ignored. However, the unmet water demand of upstream sectors with high water dependency will exacerbate water scarcity, and lead to potential economic risk to the industrial chain. To solve it, we propose a method to quantify the intermediate virtual water scarcity risk transfer via the intermediate use matrix and Leontief inverse matrix, and apply it to virtual water trade in China in 2018. Meaningful conclusions are drawn as follows: (i) Although the water-use efficiency of all sectors in China increased steadily from 2007 to 2018, the overall input concentration of virtual water scarcity risk showed a rising trend, reflecting the gradual increase in the vulnerability of the industrial chain to water shortage. (ii) The virtual water scarcity risk in China mainly transferred through the secondary industry. The secondary industry accounted for 51.8% of the output and 71.8% of the input in the intermediate virtual water transfer, while 77.0% and 74.7%, respectively, in intermediate virtual water scarcity risk output and input. (iii) From 2007 to 2018, agriculture, chemical industry, metallurgy, electricity and heat supply always ranked as the top four of intermediate virtual water scarcity risk output sectors. As their downstream sectors, the construction industry, metallurgy, and other services are stable within the top four input sectors. (iv) The virtual water scarcity risk upstream transmitted is significantly dispersed after the intermediate inputs process, indicating that abundant import relationships are conducive to reduce the risk taken in. From the perspective of intermediate input, this paper argues that it is necessary to both ensure the water supply of the upstream source sectors and disperse the downstream import sources. Moreover, enriching industrial structures and closing production linkages between sectors is also beneficial for promoting sustainable economic development.

Physics-Informed Neural Network Integrating PointNet-Based Adaptive Refinement for Investigating Crack Propagation in Industrial Applications

Crack is one of the critical factors that degrade the performance of machinery manufacturing equipment. Recently, physics-informed neural networks (PINNs) have received attention due to their strong potential in solving physical problems. For fracture problems, PINNs have been used to predict crack paths by minimizing the variational energy of discrete domains where refined meshes are necessary. To obtain refined meshes, posteriori adaptive refinement techniques are commonly used to perform local refinement of the mesh based on errors in the intermediate calculation process; thus, they require pretest calculations. However, it is computationally expensive to precalculate complex problems, especially crack propagation. To solve this problem, we propose a PointNet-based adaptive refinement method to avoid precalculation when constructing the discrete domain. The proposed method is applied to simulate crack propagation using a PINN. Results show that the proposed method can be used to obtain reliable results efficiently when using the PINN framework.

Effects of Missing Linker Defects on the Elastic Properties and Mechanical Stability of the Metal–Organic Framework HKUST-1

The defects can naturally exist or be artificially designed in metal–organic frameworks (MOFs), which could significantly affect their mechanical properties. In this paper, the elastic properties of HKUST-1 with randomly distributed missing linker defects are investigated by reactive molecular dynamics simulations together with the strain-fluctuation method. Although all elastic constants of HKUST-1 are found to reduce due to the linker missing, the cubic symmetry is retained in the defective HKUST-1, indicating that the simplified Born stability criterion is still applicable in determining its mechanical stability. On the basis of the simplified Born stability criterion together with direct compression simulations, the critical pressure of instability of HKUST-1 with randomly distributed defects is found to almost linearly decrease as the defect concentration grows. The mechanical instability is similarly attributed to the compression mode in both pristine and defective HKUST-1. Moreover, the direct compression simulations indicate an obvious intermediate transition process existing during the structural collapse of the defective HKUST-1, which is absent in its pristine counterpart. Overall, this work is expected to provide a more precise understanding of the mechanical properties of realistic MOFs.