Chemical Engineering Research Articles

Chemical disorder effects on Gilbert damping of FeCo alloys

The impact of the local chemical environment on the Gilbert damping in the binary alloy Fe100−xCox is investigated, using computations based on density functional theory. By varying the alloy composition x as well as Fe-Co atom positions we reveal that the effective damping of the alloy is highly sensitive to the nearest-neighbor environment, especially to the amount of Co and the average distance between Co-Co atoms at nearest-neighbor sites. Both lead to a significant local increase (up to an order of magnitude) of the effective Gilbert damping, originating mainly from variations of the density of states at the Fermi energy. In a global perspective (i.e., making a configuration average for a real material), those differences in damping are masked by statistical averages. When low-temperature explicit atomistic dynamics simulations are performed, the impact of short-range disorder on local dynamics is observed to also alter the overall relaxation rate. Our results illustrate the possibility of local chemical engineering of the Gilbert damping, which may stimulate the study of new ways to tune and control materials aiming for spintronics applications. Published by the American Physical Society 2024

Bubble Theory and its Applications in Underwater Explosion, Marine Cavitation, and Seismic Exploration

AbstractBubbles play crucial roles in various fields, including naval and ocean engineering, chemical engineering, and biochemical engineering. Numerous theoretical analyses, numerical simulations, and experimental studies have been conducted to reveal the mysteries of bubble motion and its mechanisms. These efforts have significantly advanced research in bubble dynamics, where theoretical study is an efficient method for bubble motion prediction. Since Lord Rayleigh introduced the theoretical model of single-bubble motion in incompressible fluid in 1917, theoretical studies have been pivotal in understanding bubble dynamics. This study provides a comprehensive review of the development and applicability of theoretical studies in bubble dynamics using typical theoretical bubble models across different periods as a focal point and an overview of bubble theory applications in underwater explosion, marine cavitation, and seismic exploration. This study aims to serve as a reference and catalyst for further advancements in theoretical analysis and practical applications of bubble theory across marine fields.

Discovery of highly potent and ALK2/ALK1 selective kinase inhibitors using DNA-encoded chemistry technology

Activin receptor type 1 (ACVR1; ALK2) and activin receptor like type 1 (ACVRL1; ALK1) are transforming growth factor beta family receptors that integrate extracellular signals of bone morphogenic proteins (BMPs) and activins into Mothers Against Decapentaplegic homolog 1/5 (SMAD1/SMAD5) signaling complexes. Several activating mutations in ALK2 are implicated in fibrodysplasia ossificans progressiva (FOP), diffuse intrinsic pontine gliomas, and ependymomas. The ALK2 R206H mutation is also present in a subset of endometrial tumors, melanomas, non-small lung cancers, and colorectal cancers, and ALK2 expression is elevated in pancreatic cancer. Using DNA-encoded chemistry technology, we screened 3.94 billion unique compounds from our diverse DNA-encoded chemical libraries (DECLs) against the kinase domain of ALK2. Off-DNA synthesis of DECL hits and biochemical validation revealed nanomolar potent ALK2 inhibitors. Further structure-activity relationship studies yielded center for drug discovery (CDD)-2789, a potent [NanoBRET (NB) cell IC50: 0.54 μM] and metabolically stable analog with good pharmacological profile. Crystal structures of ALK2 bound with CDD-2281, CDD-2282, or CDD-2789 show that these inhibitors bind the active site through Van der Waals interactions and solvent-mediated hydrogen bonds. CDD-2789 exhibits high selectivity toward ALK2/ALK1 in KINOMEscan analysis and NB K192 assay. In cell-based studies, ALK2 inhibitors effectively attenuated activin A and BMP-induced Phosphorylated SMAD1/5 activation in fibroblasts from individuals with FOP in a dose-dependent manner. Thus, CDD-2789 is a valuable tool compound for further investigation of the biological functions of ALK2 and ALK1 and the therapeutic potential of specific inhibition of ALK2.

Multi-Criteria Decision Making in Chemical and Process Engineering: Methods, Progress, and Potential

Multi-criteria decision making (MCDM) is necessary for choosing one from the available alternatives (or from the Pareto-optimal solutions obtained by multi-objective optimization), where the performance of each alternative is quantified against several criteria (or objectives). This paper presents a comprehensive review of the application of MCDM methods in chemical and process engineering. It systematically outlines the essential steps in MCDM including the various normalization, weighting, and MCDM methods that are critical to decision making. The review draws on published papers identified through a search in the Scopus database, focusing on works by authors with more contributions to the field and on highly cited papers. Each selected paper was analyzed based on the MCDM, normalization, and weighting methods used. Additionally, this paper introduces two readily available programs for performing MCDM calculations. In short, it provides insights into the MCDM steps and methods, highlights their applications in chemical and process engineering, and discusses the challenges and prospects in this area.

Abstract 4136847: Administration of the Recombinant Activated Protein C Rescues the Cardiac Vulnerability to Ischemic Insults in Aging through Modulating Inflammatory Response during Ischemia and Reperfusion

Introduction: Activated protein C (APC) is an endogenous vitamin-K-dependent serine protease and exhibits therapeutic potential for ischemic heart disease. The APC derivatives with anticoagulant and/or cytoprotective properties were produced through chemical engineering to characterize the functional domain of APC for limiting ischemia/reperfusion (I/R) injury. Hypothesis: The thromboinflammatory regulation by APC ameliorates ischemic insults caused by I/R through the receptor EPCR/PAR1. Methods: Young (3 months)/aged (24 months) wild type C57BL/6J mice and PAR1 R46Q/R46Q (block cleavage by APC) knock in mutant (3 months, C57BL/6J) mice were subjected to ligation of left anterior descending coronary artery with 45 min of ischemia. 5 min prior to reperfusion, wild type APC, cytoprotective selective APC-2Cys, or anticoagulant selective APC-E170A (0.2 μg/kg i.v.) was administered followed by 24 hr of reperfusion. The left ventricles of hearts were used for immunoblotting and flow cytometry analysis. Results: APC and APC-2Cys but not APC-E170A reduced I/R-induced myocardial infarction. Echocardiography showed that APC and APC-2Cys but not APC-E170A can rescue systolic dysfunction by I/R in young/aged WT but not in PAR1 R46Q/R46Q mice. Biochemical analysis showed that administration of APC and APC-2Cys inhibited activation of inflammation signaling c-Jun N-terminal protein kinase (JNK) and NF-κB by I/R and reduced mRNA levels of the proinflammatory cytokines TNFα and IL-6 in young/aged WT but not in PAR1 R46Q/R46Q hearts. The plasma cytokine array demonstrated that APC and APC2-Cys reduced potency of pro-inflammatory cytokines and apoptotic signaling cytokines during I/R. Moreover, I/R-triggered inflammasome NLRP3 was reduced by APC and APC-2Cys in young/aged WT but not in PAR1 R46Q/R46Q hearts. The flow cytometry showed that APC and APC-2Cys increased lymphocyte and decreased myeloid cell abundance and increased the recruitment of inflammation-mediating CD8a + T-cells during I/R in young/aged WT but not PAR1 R46Q/R46Q hearts, indicating that the APC/EPCR/PAR1 axis mediates APC's immune regulation under I/R. Moreover, APC and APC-2Cys reduced I/R-triggered macrophage abundance in young/aged WT hearts, although the proportion of M1 and M2 macrophages was unchanged. Conclusions: The cytoprotective domain of APC is critical for its cardioprotection against ischemic insults. EPCR/PAR1 receptor complex mediates APC's immune regulation in aging during I/R conditions.

A review on the role of various machine learning algorithms in microwave-assisted pyrolysis of lignocellulosic biomass waste

The fourth industrial revolution will heavily rely on machine learning (ML). The rationale is that these strategies make various business operations in many sectors easier. ML modeling is the discovery of hidden patterns between multiple process parameters and accurately predicting the test values. ML has provided a wide range of applications in Chemical Engineering. One major application of ML can be found in the microwave-assisted pyrolysis (MAP) of lignocellulose bio-waste. MAP is an energy-efficient technology to obtain high-saturated hydrogen-rich liquid fuels. The main focus of this review study is understanding the utilization of various types of ML algorithms, including supervised and unsupervised techniques in microwave-assisted heating techniques for diverse biomass feedstocks, including waste materials like used tea powder, wood blocks, kraft lignin, and others. In addition to developing effective ML-based models, alternative traditional modeling approaches are also explored. In addition to various thermochemical conversion processes for biomass, MAP is also briefly reviewed with several case studies from the literature. The conventional modeling methodology for biomass pyrolysis with microwave heating is also discussed for comparison with ML-based modeling methodologies.

Advancing nonlinear problem solutions: Newton-like iterative techniques for varied convergence orders using homotopy perturbation

Abstract Iterative methods are crucial in numerical analysis for approximating solutions to nonlinear problems encountered in various fields, such as biomathematics, thermodynamics, chemical engineering, and fluid mechanics. This paper introduces innovative iterative methods of convergence orders three and six to eight, developed using the homotopy perturbation technique (HPT). We address the limitations of traditional derivative-based methods by incorporating divided differences, resulting in derivative-free schemes with optimal convergence properties. We present four newly designed algorithms (HPM1, HPM2, HPM3, and HPM4) and provide a comprehensive convergence analysis. Numerical simulations and basins of attraction demonstrate the superior performance of the proposed methods compared to existing methods of the same order. The proposed methods exhibit faster convergence and larger basins of attraction, making them highly effective for solving nonlinear equations. Our new numerical methods rely on approximations and iterative processes, with each small step bringing us closer to the exact solution. Exploring these numerical methods encourages us to apply mathematics to solve challenging problems in physics, engineering, finance, and more.

Programmable orientation of blue phase soft photonic crystal

Understanding the structure formation and its underlying physical mechanism is a fundamental topic in condensed matter systems, with both academic and practical implications. Soft matter is playing a remarkable role in current era of information explosion, demonstrating enormous potential in integrated functional photonics. As unique soft photonic crystals with cubic symmetries, not only liquid crystalline blue phases (BPs) have circularly polarized selective reflection and ultra-fast electro-optical response, but also their three-dimensional photonic structures increase degrees-of-freedom for multiplexed optical modulation. In the thriving field of soft-matter-based photonics, precise and programmable engineering of BP crystal orientation is of vital importance for planar optical elements, which remains a challenging task due to the complexity of the nucleation process as well as the interaction between the BP building blocks and the boundary conditions. Aiming to gain a comprehensive understanding of how to tailor the orientation of BP crystals for the photonic applications of next generation, here we discuss the solutions for uniformity improvement and orientation control of BP crystals, about which a few of examples in combination with the underlying mechanisms are explained. In addition, the remaining challenges and the efforts that are expected are also reviewed. We expect this work provides a deeper understanding of phase transitions and resulting structures in soft crystals, which may open encouraging perspectives for their applications in photonics, biosensing, interfacial, and chemical engineering.

Nitrogen-doped Ga2O3 current blocking layer using MOCVD homoepitaxy for high-voltage and low-leakage Ga2O3 vertical device fabrication

In this Letter, a high-quality and high-resistivity nitrogen (N)-doped Ga2O3 current blocking layer (CBL) is grown utilizing metal-organic chemical vapor deposition homoepitaxial technology. By using nitrous oxide (N2O) as oxygen source for Ga2O3 growth and N source for doping and controlling the growth temperature, the grown CBL can effectively achieve high (∼1019 cm−3) or low (∼1017 cm−3) N doping concentrations, as well as high crystal quality. Furthermore, the electrical properties of the developed CBL are verified at the device level, which shows that the device using the CBL can withstand bidirectional voltages exceeding 3.5 kV with very low leakage (≤1 × 10−4 A/cm2). This work can pave the way for the realization of high-voltage and low-leakage Ga2O3 vertical devices, especially metal-oxide-semiconductor field effect transistors.

Toward Sustainable Utilization and Production of Tartaric Acid.

Global efforts toward establishing a circular carbon economy have guided research interests towards exploring renewable technologies that can replace environmentally harmful fossil fuel-based production routes. In this context, sugar-based bio-derived substrates have been identified as renewable molecules for future implementation in chemical industries. Tartaric acid, a special C4 bio-compound with two hydroxyl and carboxylic groups in the structure, displays great potential for the food, polymer, and pharmaceutical industries due to its unique biological reactivity and performance-enhancing properties. To this point, there has yet to be a comprehensive literature review and perspective on the applications and synthesis of tartaric acid. As such, we have conducted a detailed and thorough outlook and discussion in terms of biological activity, organic synthesis, catalysis, structural characterization and synthetic routes. Lastly, we provide a critical discussion on the applications and synthesis of tartaric acid to give our insights into developing sustainable chemical technologies for the future.

Steering diffusion selectivity of chemical isomers within aligned nanochannels of metal-organic framework thin film

The movement of molecules (i.e. diffusion) within angstrom-scale pores of porous materials such as metal-organic frameworks (MOFs) and zeolites is influenced by multiple complex factors that can be challenging to assess and manipulate. Nevertheless, understanding and controlling this diffusion phenomenon is crucial for advancing energy-economic membrane-based chemical separation technologies, as well as for heterogeneous catalysis and sensing applications. Through precise assessment of the factors influencing diffusion within a porous metal-organic framework (MOF) thin film, we have developed a chemical strategy to manipulate and reverse chemical isomer diffusion selectivity. In the process of cognizing the molecular diffusion within oriented, angstrom-scale channels of MOF thin film, we have unveiled a dynamic chemical interaction between the adsorbate (chemical isomers) and the MOF using a combination of kinetic mass uptake experiments and molecular simulation. Leveraging the dynamic chemical interactions, we have reversed the haloalkane (positional) isomer diffusion selectivity, forging a chemical pathway to elevate the overall efficacy of membrane-based chemical separation and selective catalytic reactions.

Preface: 7th International Conference on Chemical Engineering and Advanced Materials (CEAM 2024)

The 2024 7th International Conference on Chemical Engineering and Advanced Materials (CEAM 2024) was held in Philadelphia, USA during September 28-29, 2024. This conference aims to provide opportunities for all participants to exchange new innovative ideas and application experiences as well as to provide a platform where possible innovators can think of new ventures, generate contacts and networks for future collaboration. The CEAM 2024 topics include chemical engineering, biological chemistry, biological pharmacy, food science, chemical materials, nano materials, materials processing engineering, and advanced materials applications. This conference brought together leaders from industry and academia to exchange and share their experiences, present research results, explore collaborations, and to spark new ideas, with the aim of developing new projects and exploiting new technology. On behalf of the conference organizers, we would like to thank the reviewers for their time and effort in reviewing the papers. Their feedbacks to the authors have been excellent and useful to ensure high quality papers for the conference. Our appreciation to all keynote speakers for sharing their thoughts and experiences with respect to various topics. Our sincere thanks also go to all attendees from all around the world for participating in the conference. Finally, we would like to thank the organizing committee members for their hard work, cooperation, and insights in ensuring the success of this conference. Scientific Committee of CEAM 2024 Philadelphia, USA

Advances in Carbon Dioxide Catalytic Conversion and Applications

To achieve the global climate goals set out in the Paris Agreement, reducing carbon dioxide (CO2) emissions and utilizing resources have become key areas of focus within international energy technology research and development. CO2 can be converted into high-value chemicals, including hydrocarbons, alcohols and hydrocarbons, through the catalytic technology. This process can potentially address environmental issues while generating economic benefits. This paper presents a review of the principal products resulting from the catalytic conversion of CO2, together with an examination of their practical applications. These include hydrogenation of olefins, light aromatics, methanol, polyols, and synthetic bioconversion technologies. The development of catalysts with high conversion and selectivity represents a key area of current research. In the future, it will be necessary to combine physical, chemical, and biological technologies to establish an engineered heterogeneous carbon sequestration technology system to achieve the efficient conversion and utilization of CO2.

An entropy measure-based study on flow pattern of gas–liquid two-phase flow in a U-Tube

U-tubes are widely applied in gas–liquid two-phase transportation in chemical engineering. The diverse flow patterns within these tubes significantly affect the pressure loss, heat transfer efficiency, and even the fluid-induced vibration amplitude of the tubes. This study explores the complex flow pattern features in a U-tube in a vertical plane and focuses on recognizing them. For the acquisition and classification of flow patterns, a Computational Fluid Dynamics (CFD) model for gas–liquid two-phase flow is first established, and its quantitative calculation error is ensured to be less than 5%. Then, the spatiotemporal evolution characteristics of flow patterns is analyzed. The real-time pressure drop response is chosen as the representation signal, and its nonlinear features in the time and frequency domain under different flow patterns are explored. A nonlinear time series is constructed by extracting a segment from the real-time pressure drop data, and six entropy measures are applied to analyze and identify them. Finally, the sensitivity of entropy measures to both the time series lengths and the tested sections are evaluated. Results show that there are six typical flow patterns in a U-tube. According to most entropy measures, the bubble flow has the highest complexity; however, the plug flow presents the lowest complexity. In the U-bend, pressure drop signals for the bubble and annular flows show random fluctuations within a specific range, in contrast to the marked periodicity in plug flow signals, while wavy and slug flows exhibit intermittent peak values. Including the upstream and downstream straight pipes in the analysis, rather than focusing solely on the U-bend, significantly increases the complexity of the stratified, plug, and slug flows. Fuzzy entropy is an effective tool for identifying the six flow patterns, demonstrating good resilience to variations in the length of the data series. This characteristic makes it highly useful for real-time identification of flow patterns in the U-bend sections of non-transparent U-tubes, offering considerable potential in chemical equipment.

Advances in Spectro-Microscopy Methods and their Applications in the Characterization of Perovskite Materials.

Perovskite materials are promising contenders as the active layer in light-harvesting and light-emitting applications if their long-term stability can be sufficiently increased. Chemical and structural engineering are shown to enhance long-term stability, but the increased complexity of the material system also leads to inhomogeneous functional properties across various length scales. Thus, scanning probe and high-resolution microscopy characterization techniques are needed to reveal the role of local defects and the results promise to act as the foundation for future device improvements. A look at the parameter space: technique-specific sample penetration depth versus probe size highlights a gap in current methods. High spatial resolution combined with a deep penetration depth is not yet achievable. However, multimodal measurement technique may be the key to covering this parameter space. In this perspective, current advanced spectro-microscopy methods which have been applied to perovskite materials are highlighted.

Modeling the Production Process of Lignin Nanoparticles Through Anti-Solvent Precipitation for Properties Prediction

Global warming has recently intensified research interest in renewable polymer chemistry, with significant attention directed towards lignin nanoparticle (LNP) synthesis. Despite progress, LNP industrial application faces challenges: (1) reliance on kraft lignin from declining raw biomass processes, (2) sulfur-rich and condensed lignin use, (3) complex lignin macroparticles to LNP conversion, using harmful and toxic solvents, and, above all, (4) lack of control over the LNP production process (i.e., anti-solvent precipitation parameters), resulting in excessive variability in properties. In this work, eco-friendly LNPs with tailored properties were produced from a semi-industrial organosolv process by studying anti-solvent precipitation variables. Using first a parametric and then a Fractional Factorial Design, predictions of LNP sizes and size distribution, as well as zeta-potential, were derived from a model over beech by-products organosolv lignin, depending on initial lignin concentration (x1, g/L), solvent flow rate (x2, mL/min), antisolvent composition (x3, H2O/EtOH v/v), antisolvent ratio (x4, solvent/antisolvent v/v), and antisolvent stirring speed (x5, rpm). This novel chemical engineering approach holds promise for overcoming the challenges inherent in industrial lignin nanoparticle production, thereby accelerating the valorization of lignin biopolymers for high value-added applications such as cosmetics (sunscreen or emulsion) and medicine (encapsulation, nanocarriers), a process currently constrained by significant limitations.

Physical–Chemical–Biological Pretreatment for Biomass Degradation and Industrial Applications: A Review

Lignocellulosic biomass, including agricultural, forestry, and energy crop waste, is one of Earth’s most abundant renewable resources, accounting for approximately 50% of global renewable resources. It contains cellulose, hemicellulose, and lignin, making it crucial for biofuels and bio-based chemicals. Due to its complex structure, single-pretreatment methods are inefficient, leading to the development of combined pretreatment technologies. These methods enhance cellulose accessibility and conversion efficiency. This paper analyzes the principles, advantages, and disadvantages of various combined pretreatment methods and their practical benefits. It highlights recent research achievements and applications in biofuel, biochemical production, and feed. By integrating multiple pretreatment methods, biomass degradation efficiency can be significantly improved, energy consumption reduced, and chemical reagent use minimized. Future advancements in combined physical, chemical, and biological pretreatment technologies will further enhance biomass utilization efficiency, reduce energy consumption, and protect the environment, providing robust support for sustainable renewable energy development and ecological protection.

Spatial benefit difference of fertilizer reduction and substitution policy based on grid scale: A case study of the Heihe River Basin

Agriculture green development faces the challenge of balancing the application of both organic and chemical fertilizers. Formulating effective policies to harmonize these applications is essential for ensuring food security and environmental sustainability. However, there is a lack of studies investigating the economic and environmental benefits of policy implementation at the grid scale, and insufficient research has been conducted on the subsequent impacts these policies have on diverse crops. Therefore, this paper develops the SIMPLE-G-Heihe model to simulate the impacts of green agricultural policies on multiple crops planting in arid regions. This model addresses limitations found in the SIMPLE-G model, which supported a single crop and lacked organic fertilizer substitution simulation. The results show that: (1) Merely increasing subsidies for organic fertilizers is insufficient to significantly enhance yields, and improving the efficiency of fertilizer utilization should also be emphasized. (2) Combining improvements in fertilizer technology with subsidies for organic fertilizers can concurrently support economic advancement and environmental mitigation. Research indicates that integrating a 3% organic fertilizer subsidy with an 8% improvement in chemical fertilizer technology increases vegetable output value by 0.27% and reduces N2O emissions by 1.09%. (3) The upstream areas of the Heihe River Basin show a significant reduction in fertilizer use. Fertilizer input is mainly reduced for vegetables in the upstream areas, while for wheat and maize, the reduction is primarily in the midstream and upstream areas. The findings discuss the spatial heterogeneity and flexibility of policy impacts, providing valuable insights for the implementation of green agriculture strategies in China.

Optimization of chemical engineering control for large-scale alkaline electrolysis systems based on renewable energy sources

In the context of renewable energy, dynamic control is crucial for large-scale alkaline water electrolysis systems. Under traditional Proportional-Integral-Derivative (PID) control, the system's temperature and impurity levels may exceed safe limits during sudden load changes, compromising system safety. Therefore, this study proposes a control strategy based on mathematical models of system temperature and impurities, including Model Predictive Control (MPC) for temperature and Optimal Curve Tracking (OCT) for impurities. The MPC controller offsets the disturbances in temperature caused by current fluctuations through state prediction, while the OCT controller ensures that impurity levels remain within safe limits. Real-time application of these control strategies is achieved through MATLAB-PLC communication, validating controller performance. Experimental results show that the MPC controller exhibits excellent dynamic response and stability in controlling the stack temperature, with a maximum temperature peak deviation of only 2.9 K and a temperature fluctuation range of 5.9 K. This represents a reduction of 1.6 K in peak deviation compared to traditional PID controllers and significantly decreases the temperature fluctuation range. The OCT controller also demonstrates good safety and stability in controlling hydrogen to oxygen (HTO) impurity levels, consistently maintaining the HTO content at the set upper limit of 1.5%, thereby expanding the safe operational range of the system and reducing the need for frequent adjustments to the system setpoints.

Numerical investigation on the liquid jet and the dynamics of the near-wall cavitation bubble under an acoustic field

The dynamics of the near-wall cavitation bubble in an acoustic field are the fundamental forms of acoustic cavitation, which has been associated with promising applications in ultrasonic cleaning, chemical engineering, and food processing. However, the potential physical mechanisms for acoustic cavitation-induced surface cleaning have not been fully elucidated. The dynamics of an ultrasonically driven near-wall cavitation bubble are numerically investigated by employing a compressible two-phase model implemented in OpenFOAM. The corresponding validation of the current model containing the acoustic field was performed by comparison with experimental and state-of-the-art theoretical results. Compared to the state without the acoustic field, the acoustic field can enhance the near-wall bubble collapse due to its stretching effect, causing higher jet velocities and shorter collapse intervals. The jet velocity in the acoustic field increases by 80.2%, and the collapse time reduces by 40.9% compared to those without an acoustic field for γ = 1.1. In addition, the effects of the stand-off distances (γ), acoustic pressure wave frequency (f), and initial pressure (p*) on the bubble dynamic behaviors were analyzed in depth. The results indicate that cavitation effects (e.g., pressure loads at the wall center and the maximal bubble temperature) are weakened with the increase in the frequency (f) owing to the shorter oscillation periods. Furthermore, the maximum radius of bubble expansion and the collapse time decrease with increasing f and increase with increasing p*. The bubble maximum radius reduces by 12.6% when f increases by 62.5% and increases by 20.5% when p* increases by 74%.