Ideal Size Research Articles

Nonlinear effects of board size and board independence on corporate sustainability performance: international evidence

Purpose This study aims to examine the nonlinear effects of board size and board independence on the corporate sustainability performance of listed firms worldwide. Design/methodology/approach This study uses the global environmental, social and governance (ESG) dataset from the Thomson Reuters database, which includes a sample of 23,766 firm-year observations from 33 countries from 2011 to 2022. Findings The results indicate that board size and independence have positive impacts on corporate sustainability performance; however, these relationships are nonlinear. The authors find an inverted U-shaped relationship for board size. After the optimal point, the positive relationship between board size and corporate sustainability performance becomes negative. Board independence, however, has a positive exponential relationship in which the positive effect increases exponentially after the optimal point. The results are robust to a battery of tests, including alternative measures for corporate sustainability performance, board independence and different estimation procedures. Research limitations/implications This study illustrates empirical evidence on the nonlinear effect of board size and board independence on corporate sustainability performance, which explains the mixed evidence involving board size and independence in corporate sustainability literature and offers a complementary research approach in the literature on board dynamics. Practical implications This study has practical implications for investors aiming for sustainable and ethical investment choices, as they should be mindful of matters relating to board composition, particularly the appointment of independent directors and ideal board size. Originality/value Extensive empirical evidence has examined the relationship between corporate governance variables and corporate sustainability performance. This study introduces the effect of the nonlinear relationship between board size and board independence on corporate sustainability performance using international evidence.

Impacts of electric vehicle charging stations and DGs on RDS for improving voltage stability using honey badger algorithm

The intelligent computational technique used in this research handles the multi-objective voltage stability optimization (MOVSO) problem in radial distribution systems (RDS). The objectives of the proposed research are to minimize network loss, lower the average voltage deviation index (AVDI), and improve the voltage stability index (VSI) of RDS by taking into account the recently created distributed generators (DGs) and electric vehicle charging stations (EVCSs). To address the MOVSO problem, a novel and innovative honey badger algorithm (HBA) optimization technique is put forth. The two stages of HBA, known as the "digging" and "honey" phases, are responsible for effectively identifying the ideal position and appropriate quantity of EVCSs and DGs. The standard IEEE 33 node test system with different case studies is considered to validate the performance of HBA. The simulation results of improved voltage profile, minimized power loss, AVDI and improved VSI are tabulated. The proposed HBA fine-tunes the ideal position and size of the EVCSs to significantly enhance RDS performance under higher loading circumstances. To demonstrate the efficacy and originality of the suggested HBA, the numerical results are contrasted with those of earlier soft computing techniques.

ONLINE MEASUREMENT OF FLOUR PARTICLE SIZE DISTRIBUTION USING PIEZOELECTRIC SENSOR

Obtaining the ideal particle size is a vital factor in dust processes, from turning wheat into flour to cement and calcite production. However, the technology to measure particle size instantaneously during the production phase is still an area under development. These measurements made with electro-optical methods have limited use in industry due to their difficulties and excessive costs. Studies conducted with innovative acoustic emission sensors offer new hopes in particle size detection. These sensors can successfully measure the dimensions of a wide range of materials, from coal dust to metal powders to grass particles. Our study shows that these sensors can also measure the size of light flour particles instantaneously. Using developed method, the dimensions of five types of flour mixtures in the size ranges of 0-80 µm, 80-118 µm, 118-150 µm, 150-180 µm and 180-212 µm could be measured and classified with 100% success. Considering its potential to increase the efficiency of the milling process, this technology could revolutionize the milling industry.

Effects of Preformed Composition and Pore Size on Microstructure and Properties of SiCf/SiC Composites via Reactive Melt Infiltration

This study investigated the influence of preformed composition and pore size on the microstructure and properties of SiCf/SiC composites fabricated via reactive melt infiltration (RMI). The process began with the impregnation of SiC fiber cloth with phenolic resin, followed by lamination and pyrolysis. Subsequent steps included further impregnations with phenolic resin, SiC slurry, and carbon black slurry, each followed by additional pyrolysis. This process resulted in three types of preforms, designated as PP, PS, and PC. These preforms exhibited a multimodal distribution of pore size, with peak pore diameters around 5 μm for PP, ranging from 200 nm to 4 μm for PS, and approximately 150 nm for PC. The preforms were then subjected to molten silicon infiltration at 1600 °C under vacuum for 1 h to create SiCf/SiC composites. The PP preform contained only pyrolytic carbon, leading to a composite with high closed porosity and unreacted carbon, resulting in poor mechanical properties. The PS preform, which was impregnated with SiC particles, displayed an optimized pore size distribution but retained significant amounts of residual silicon and carbon in the final composite. In contrast, the PC preform featured both an ideal pore size distribution and an adequate amount of carbon, achieving high density and low porosity with reduced residual phases in the final composite. This optimization led to a flexural strength of 152.4 ± 15.4 MPa, an elastic modulus of about 181.1 ± 0.1 GPa, and a thermal conductivity of 27.7 W/mK in the SiCf/SiC composites product. These findings underscore the importance of preform optimization in enhancing the performance of SiCf/SiC composites, potentially paving the way for more reliable nuclear fuel cladding solutions.

Quantitative in silico analysis for patient-specific annuloplasty in bicuspid aortic valve regurgitation

Bicuspid aortic valve (BAV) patients are more predisposed to aortic regurgitation. Annuloplasty is a crucial therapeutic intervention, however, determining its ideal size remains a clinical challenge. This study aims to quantify the effects of varying annuloplasty sizes on treating BAV regurgitation, providing optimal size range for effective treatment while avoiding complications. Annuloplasty was simulated on a patient-specific BAV model using 19–27 mm diameter Hegar dilators to reduce the basal ring and elastic ring sutures to constrain it. Finite element simulation was performed to simulate BAV motion, followed by computational fluid dynamics simulation to obtain hemodynamic parameters at peak systole. Results show that as the basal ring size decreased, the leaflet coaptation area increased, accompanied by a reduction in maximum principal stress at the coaptation zone. However, the reduction in annuloplasty size significantly elevated the peak systolic flow velocity within the sinus, particularly near the basal ring, leading to a higher wall shear stress in the adjacent region. Moreover, an excessively small basal ring diameter induced a sharp increase in transvalvular pressure gradient. These findings suggest that the small-sized annuloplasty enhances BAV function and durability, whereas excessive ring reduction may aggravate mechanical burden on the aortic root, potentially resulting in long-term complications such as tissue damage and stenosis. Thus, these factors establish critical upper and lower limits for optimal annuloplasty sizing.

Negative Body Image and Limited Nutrition Knowledge among Collegiate Dancers Signals Need for Screening and Support.

Introduction: The collegiate environment may exacerbate body image issues and eating disorders (EDs) among dancers. This study seeks to evaluate the complex relationships between body image perceptions, risk of EDs, and nutrition knowledge among collegiate dancers. Methods: A convenience sample of collegiate dancers was recruited via announcements, flyers, and email to complete the Body Image Assessment Scale-Body Dimensions (BIAS-BD), anthropometrics, and an electronic survey evaluating ED risk (Eating Attitudes Test; EAT-26), nutrition knowledge, and dietary habits. Body distortion (perceived vs actual size) and dissatisfaction (perceived vs ideal size) were measured. Data analysis included descriptive statistics and t-tests for group and gender-specific data. Results: Thirty-eight collegiate dancers (82% female, 79% with a healthy BMI) participated in the body image assessment. Females (n = 31) exhibited body distortion (P = .006) with a mean BMI = 22.05, mean perceived BMI = 23.27, and a mean ideal BMI = 21.78. Body dissatisfaction was identified but not statistically significant. Males' perceptions of females' ideal BMI = 25.16 were significantly higher than the females' own perceptions (BMI = 21.78, P = .033). No significant body distortion or dissatisfaction was observed among males (n = 7). Female perceptions of the ideal male BMI = 23.96 aligned closely with males' self-views. On the EAT-26, females (n = 28) average score was 11.82, indicating higher risk than males (n = 4), whose average score was 7.75. High ED risk was identified in 18.75% of participants (EAT-26 scores ≥ 20). Nutrition knowledge was limited, with <50% correct responses. The majority sought dietary advice from peers (65.7%) or friends (57.1%), with 37.1% following restrictive diets (eg, vegan, pescatarian, lactose-free). Conclusion: Collegiate female dancers demonstrated body distortion and ED risk despite maintaining a healthy BMI. The limited nutrition knowledge, reliance on non-expert nutrition advice, and tendency towards restrictive eating patterns observed with increased ED risk is worrisome. Thereby necessitating educational interventions focused on nutrition and body image to maintain the dancers' health.

Forecasting Realized Volatility: The Choice of Window Size

ABSTRACTDifferent window sizes may produce different empirical results. However, how to choose an ideal window size is still an open question. We investigate how the window size affects the predictive performance of volatility. The empirical results show that the loss function for volatility prediction takes on a U‐shape as the window size increases. This suggests that if the window size is chosen too large or too small, the loss function tends to be large and the model's predictive accuracy decreases. A window size of between 1000 and 2000 observations is ideal for various assets because it can produce relatively minimal forecast errors. From an asset allocation perspective, a mean–variance investor can obtain sizeable utility by using a model with a low loss function value for her portfolio. Moreover, the results are robust in a variety of settings.

Learners'-Teachers'-Parents' Approaches towards EFL Learning: A Case Study at Elementary Levels’ Bangla-Medium Schools in Khulna Metropolitan City, Bangladesh

This study explores the multidimensional attitudes towards learners, teachers, and parents at Bangla-medium schools in the Khulna Metropolitan City of Bangladesh. The initial and first institutional learning starts from elementary schools, indicating pre-primary, nursery, and class one to class five. So, it is crucial to build the foundation of EFL learning platforms where the learners' four language skills can be developed. Considering its standing and global importance, English is a vital language in the workplace, education, and facilitating international communication and cross-border trade and business. The critical goals of the study are to comprehend the viewpoints and approaches of primary school pupils in Bangla-medium schools, the instructional methodologies used by teachers, and the role that parents play in helping their kids acquire the language. Questionnaires, focus group discussions, and classroom observations have been used to collect data and examine the expectations, motives, and difficulties each stakeholder encounters. The results emphasize how crucial interactive teaching strategies are, how important a supportive family environment is, and how learners' particular attitudes toward developing their language skills. The study also recommends how to improve the overall efficacy of English language Learning by organizing teachers' training programs, using English as the medium of instruction, appointing more skilled English Language teachers, making an ideal class size, using digital pedagogical materials tools to develop suprasegmental features; to align curriculum with students' interests; to ensure student-oriented teaching; and to make parental awareness at the primary level in Khulna Metropolitan City.

The Effect of Mixed Lipid Concentrations and Sucrose on the Size of the Lipid Nanoparticles Containing mRNAs

The development of messenger RNA (mRNA) vaccines has been transformed using lipid nanoparticles (LNPs) as delivery systems. This study evaluates the impact of lipid mixture molar concentration and the addition of sucrose as a cryoprotectant on the size and stability of LNPs encapsulating mRNA. Using a microfluidic mixing technique, we formulated LNPs with varying lipid concentrations and analyzed their size, size distribution, and encapsulation efficiency through dynamic light scattering and a RiboGreen assay. Results indicated that higher lipid concentrations not only improved encapsulation efficiency but also maintained LNPs within the ideal size range of 80-120 nm, crucial for optimal biodistribution and immune cell uptake. Furthermore, the addition of sucrose significantly stabilized the LNPs against size changes during freeze-thaw cycles, particularly at lower temperatures. This study underscores the importance of optimizing lipid and sucrose concentrations to enhance the stability and functionality of LNPs, providing insights that could enhance the efficacy and storage stability of mRNA vaccines. HIGHLIGHTS The variation in molar concentrations of mixed lipids affects the particle size of LNP-mRNA. Buffer exchange using a membrane filter with centrifugation technique can reduce the size and uniformity of LNP particle distribution. The addition of sucrose affects the particle size of LNP-mRNA. The addition of 10 % sucrose as a cryoprotectant can maintain the particle size of LNP-mRNA at 4 and –20 °C. GRAPHICAL ABSTRACT

Using discrete choice modeling to understand the drivers of reproductive delay in the United Kingdom

The ideal family size in the UK is, on average, two children. However, there is a fertility gap, the difference between wanted and achieved family size, of around one in three children, which is largely caused by extended delays to reproduction. Standard quantitative methods used to identify what causes these delays have limitations, often relying on macro-level data which conveys little about individual needs, or applying longitudinal methods that produce outdated results because only once people have completed their reproductive years is it possible to infer which life-course factors led to later-age childbearing. This study is the first to overcome these challenges by applying a discrete choice experiment to reveal the barriers that people are facing right now. This innovative methodology allows the estimation of the relative importance of the barriers and the distance between them measured in months of reproductive delay. Among other things, the results show that for men and women, partner support was more important than finances or housing, although support means different things depending on the level of education with more educated women prioritizing hands-on fathers and household gender equality, whereas less-educated women strongly desired stable partnerships. Men favored partner readiness and neighborhood quality. These, and the other findings shown here, provide detailed insight into the contemporary causes of delayed fertility in the UK.

Forecasting Africa’s fertility decline by female education groups

While female education has long been recognized as a key driver of fertility decline during the process of demographic transition and most population projection models consider it implicitly or explicitly in their forecasts of overall fertility, there still is need for a method to forecast education-specific fertility trends directly. Here we propose a method for projecting education-specific fertility declines for cohorts of women in Sub-Saharan Africa based on all available demographic and health surveys data for African countries (including 1.03Mio cases). We study at different levels of aggregation (sample clusters, strata, and national) the associations between ideal family size and completed cohort fertility for education groups, on the one hand, and the average level of education in those units, on the other. The consistently very strong empirical associations suggest a plausible narrative by which a higher prevalence of educated women in a spatial unit influences the fertility levels of women in all specific education categories. Empirical associations between education-specific cohort fertility trends at the national level and newly available quality-adjusted human capital data for these cohorts are then operationalized to produce education-specific population projections as they are needed for-among other uses-the shared socioeconomic pathways scenarios that are widely used in the climate change research community. Sensitivity analyses including out-of-sample projections support the validity of the proposed method which is then applied to 37 African countries.

Point spread function engineering enable resolution enhanced imaging for Interferenceless coded aperture correlation holography.

The point spread function (PSF) of an optical system could characterize the resolving ability of the whole optical system for point light sources. Therefore, the imaging performance of the system could be significantly improved by regulating and optimizing the PSF. In this paper, we innovatively propose a single-exposure hologram resolution enhanced cross-correlation (RECC) method for Interferenceless coded aperture holography(I-COACH) system, circumventing the necessity to obtain the point spread hologram (PSH) of an ideal point object. The RECC method firstly acquires an approximate image of a large-size point object by Lucy-Richardson (LR) algorithm in lens imaging mode, and takes it as a PSF to acquire a PSH with ideal size of the I-COACH system by LR algorithm again, and finally acquires a reconstructed image by the single-exposure hologram RECC method. In the RECC method, the approximate ideal PSHs at different axial positions of the system are acquired by offline operation, therefore, it has a high imaging temporal resolution, and the imaging transverse resolution is not affected by the size of the point objects at the time of recording the PSH, which provides a high imaging signal-to-noise ratio and stable resolution. The proposed method provides powerful technical support for further extending the application field of the I-COACH system, and provides technical reference for other incoherent imaging.

Intergenerational transmission of fertility: evidence from China's population control policies

Abstract This paper examines how the number of siblings that parents have affects their fertility decisions in China. The population control policies in China affected individuals unequally across birth cohorts and regions. The exogenous variation in fertility is used to identify the effect of the number of siblings on the number of children for the next generation. The results show that a couple tends to have 0.034–0.068 more children (2.3–4.6% of the average number of children) and is 2.4–6.8 percentage points more likely to violate the One-Child Policy (9.3–27.1% of the violation rate) if the husband and the wife have one more sibling each. Moreover, the effect on fertility is stronger for couples in lower-income provinces where the fertility rate is higher and in rural areas where the One-Child Policy was enforced less strictly. Finally, I show that the ideal family size of the husband and wife is an important channel through which the number of siblings affects fertility. I also find that the effect of people's number of siblings has a larger effect on their ideal number of children than on their actual number of children, suggesting that they are constrained from achieving their fertility ideals.

A hybrid approach based energy management of hybrid energy systems with efficient economic model

ABSTRACT This paper proposes a hybrid AHO-SNN-based energy management (EM) of hybrid energy systems (HES) with an efficient economic model. The proposed hybrid method is combined with the Archerfish Hunting Optimizer (AHO) and Spiking Neural Network (SNN). Commonly, it is named as AHO-SNN technique. The major aim of the AHO-SNN method is the efficient economical modeling of HES and the study of sizing and EM. The comprehensive approach for describing the ideal size EM system (EMS) combination for HES is presented in this paper. The HESs, like fuel cell (FC), electrolyzer (EL), PV, battery energy system (BES), diesel generator (DSL), and hydrogen tank (HT). To determine the ideal size-EMS combination, this new EMS is employed to re-use the analytical as well as economic sizing. The AHO-SNN technique is implemented in the MATLAB software and is compared to various existing techniques. The AHO-SNN method provides an optimum outcome than the existing Particle Swarm optimization (PSO), Heap based optimizer (HBO), and Wild horse optimizer (WHO) methods. The power comparison of the existing technique HBO achieved power is 30 W, WHO is 20 W, WHO is around 10 W. In the proposed technique, the power generated is 40 W, which is way higher than the existing techniques. After implementing the integrated framework, the size of PV is cut in half, from 140 to 60 kW, which reduces the electrolyzer and the size of the hydrogen tank in also cut in half. In addition to a 35% decrease in diesel generator working hours and a 40% reduction in the leveled energy cost, PV degrades at a rate of 0.5%.

Augmenting a Concentrated Solar Power (CSP) Plant With a Solar PV Plant

The search for enhanced dispatchability at decreased prices has led to a surge in research on hybrid renewable energy systems. This paper explores the integration of Photovoltaic (PV) technology with Concentrating Solar Power (CSP) plants to enhance energy generation and economic feasibility, focusing on optimising the size of PV augmentation for existing CSP facilities. The study considers CSP plants with both Time-of-Day (ToD) and single tariffs, employing modelling techniques to assess the synergies between these two technologies. The cost of PV technology has significantly reduced, making it a cost-effective choice for electricity generation compared to CSP. CSP-PV augmentation promises to reduce online and offline auxiliary consumption, resulting in enhanced energy generation and a subsequent reduction in energy production costs. This study aims to explore the advantages of combining solar PV with a CSP system and determine the ideal PV size to maximise return, building upon previous studies to assess the technological and economic potential of integrating solar PV with CSP, focusing on South Africa. It utilises a rigorous analysis, combining the System Advisory Model and PVSyst modelling tool within an MS Excel framework. This economic assessment and sizing exercise aims to maximise profits while adhering to the limitations imposed by the power purchase agreement of a 100 MW CSP facility. The optimal size is 15 MWp for the ToD tariff and 16 MWp for the flat tariff. This highlights the potential for CSP-PV augmentation to improve energy dispatchability and financial viability, making it a compelling solution for existing CSP plants.

Navigating Economies of Scale and Multiples for Nuclear-Powered Data Centers and Other Applications with High Service Availability Needs

Nuclear energy is increasingly being considered for such targeted energy applications as data centers in light of their high capacity factors and low carbon emissions. This paper focuses on assessing the tradeoffs between economies of scale versus mass production to identify promising reactor sizes to meet data center demands. A framework is then built using the best cost estimates from the literature to identify ideal reactor power sizes for the needs of the given data center. Results should not be taken to be deterministic but highlight the variability of ideal reactor power output against the required demand. While certain advocates claim that with the gigawatts of clean, firm energy needed, large plants are ideal, others advocate for SMRs that can be deployed in large quantities and reap the benefits from learning effects. The findings of this study showcase that identifying the optimal size for a reactor is likely more nuanced and dependent on the application and its requirements. Overall, the study does show potential economic promise for coupling nuclear reactors to data centers and industrial heat applications under certain key conditions and assumptions.

Revving Up a Designed Copper Catecholate Porous Organic Polymer for Its Potent Ethylene Adsorption than Ethane.

The potential to produce high-purity C2H4 has made ethylene-selective adsorbents for ethane (C2H6)/ethylene (C2H4) gas mixture separation appealing as viable substitutes for traditional cryogenic distillation. In this aspect, porous organic polymers (POPs) are anticipated to become the next-generation potential adsorbent due to their easily customizable functions and functional sites suitable for gas separation. This article reports the selective C2H4 adsorption over C2H6 using microporous copper(I)-coordinated POP (Cu@Di-POP) via fine-tuning of the π complexation and pore size. The specially designed adsorbent has the ideal pore size and coordinated Cu(I) ions to form π-complexation with C2H4 molecules, which enabled it to adsorb C2H4 (at 1 bar, 24.9, 18.9, and 13.4 cm3 g-1 at 273, 298, and 323 K, respectively) while significantly reducing C2H6 adsorption (at 1 bar, 16.9, 12.7, and 8.8 cm3 g-1 at 273, 298, and 323 K, respectively). At 1 bar, Cu@Di-POP exhibited IAST selectivities of 6.09, 5.60, and 4.13 for C2H4/C2H6 at 273, 298, and 323 K, respectively, suggesting its C2H4 selective behavior, which was further confirmed from the experimental breakthrough measurement. Furthermore, the computational studies carried out with density functional theory highlighted an enhanced charge distribution leading to dπ-pπ conjugation between C2H4 π-electrons and Cu d-electrons, thereby showing a relatively higher interaction energy of -37.23 kcal/mol with C2H4 as compared to -16.06 kcal/mol with C2H6 gas molecules.

Europium-Doped 3D Dimensional Porous Calcium Phosphate Scaffolds as a Strategy for Facilitating the Comprehensive Regeneration of Bone Tissue: In Vitro and In Vivo.

In response to the challenges faced by clinicians treating bone defects caused by various factors, various bone repair materials have been investigated, but the efficiency of bone healing still needs to be improved due to the acting of scaffolds only in a single stage of bone tissue regeneration. We investigated the potential of a novel 3D scaffold to support different stages of bone tissue regeneration, including initial inflammation, proliferation, and remodeling. Eu (0, 0.5, 2, 3.5, 5, and 6.5%) was added to calcium polyphosphate to obtain 3D porous network-doped Eu calcium polyphosphate (EuCPP) scaffolds with ideal mechanical strength and pore size. Both in vitro and in vivo experiments proved that Eu3+ released from 5% EuCPP scaffolds could significantly promote the migration and proliferation of bone marrow stromal cells which effectively promote angiogenesis; 5% EuCPP could significantly upregulate the ratio of OPG/RANKL in MC3T3-E1 and promote the secretion of osteogenic-related growth factors (ALP and OPN) from MC3T3-E1, indicating the potential of the scaffold to inhibit bone resorption and promote bone formation. In conclusion, 5% EuCPP possesses the biological properties of pro-angiogenesis, anti-inflammation, pro-osteogenesis, and inhibiting bone resorption, which may provide a sustained positive effect throughout the process of bone tissue repair.

Ideal Family Size and Reproductive Orientations: An Exploration of Change Over Time in the United States

Drawing on more than 30 years of nationally representative microdata from the General Social Survey, this article comprehensively updates recent trends in ideal family size in the United States. It first documents stability in ideal family sizes between the mid-1980s and 2018, even in the face of a recent fertility decline. Next, the study adopts a latent class approach that identifies typologies of “reproductive orientations,” defined as multidimensional mental models of reproduction encompassing ideal family size, attitudes toward reproductive labor, and views on reproduction contexts. The findings indicate three distinct classes of reproductive orientations: Progressive Familialists, Conservative Familialists, and Blended Egalitarians. Further analyses suggest that the prevalence of these classes has changed over time and that class membership is associated with distinct patterns of childbearing and marriage. These findings deepen contemporary understandings of ideal family size in the United States and have broader implications for how demographers conceptualize and measure fertility preferences across diverse contexts.

Sustainable Heat Generation in Flow from a Molecular Solar Thermal Energy Storage System

As the global deployment of renewable technologies accelerate, finding efficient ways to store energy will aid in responding to shifting energy demands. A prospective option not only in harvesting solar energy but also in emission‐free heating is MOlecular Solar Thermal (MOST) energy storage. A central part of MOST applications is to develop methods to release the stored energy. Herein, the Quadricyclane (QC)‐to‐Norbornadiene catalyzed back reaction is explored in a specially designed packed‐bed reactor. Four distinctly sized and purposely synthesized platinum on activated carbon catalysts are studied to trigger the heat release from the energy‐dense QC isomer. The catalysts are fully characterized using a variety of structural, surface, and spectroscopic techniques. Parameters to optimize catalytic conversion and heat release in flow conditions are explored including particle size and packing behavior, flow rates, and molecular residence times. Moreover, using CO pulse chemisorption technique, site time yield values and a turnover number are reported. Complementary to the flow reactions, computational fluid dynamic simulations applying lattice Boltzmann methods to two catalytic packed beds of different size ranges are done to evaluate fluid‐dynamic behavior within the reactor bed to ascertain the ideal particle size and packing density for catalysis in MOST applications.