Loss Of Efficiency Research Articles

Experience-based transition to robotic surgery in an experienced program in minimally invasive hepatobiliary surgery.

The adoption of robotic techniques in liver surgery introduces significant challenges for their safe integration within hepatobiliary surgery units. This study is designed to investigate the complexities associated with establishing a robotic surgery program. Data on robotic hepatobiliary surgeries were prospectively collected from October 2021 to October 2023. Historical cohorts from the institutional experiences for comparison were hand-assisted (HALS) and purely laparoscopic procedures (PLS). Inverse probability of treatment weighting and propensity score matching were employed to compare outcomes between PLS and robotic resections. The learning curve for robotic surgeries was evaluated by the cumulative sum method. In this study, 454 patients were enrolled (113 robotic surgeries, 157 HALS, and 184 PLS). The posterosuperior segments resections were significantly higher in the robotic group (47.8%) compared to PLS (31.5%) and HALS (35.7%). There were no conversions in the robotic group, in PLS 2.7% and HALS 3.8%. The degree of difficulty according to the median of the IWATE score and IMM score was significantly higher in the robot group (p < 0.001 and p = 0.008, respectively). No significant differences in short-term outcomes were observed between robotic procedures and PLS in a matched subset of patients. Operative efficiency and blood loss improved significantly after the 75th robotic surgery patient, with high-difficulty cases (IWATE ≥ 10) incorporated from the beginning. This study suggests that robotic liver surgery in units with prior experience in minimally invasive liver surgery offers benefits, such as a lower conversion rate and a higher rate of successful difficult resections.

Performance of spherical and flat solar cells under different environmental conditions

This study investigates the performance degradation of spherical and flat solar modules due to dust accumulation. To isolate the effect of dust, both modules were subjected to identical environmental conditions, including irradiance, temperature, and humidity. The results reveal a significant reduction in power efficiency as dust density increases, with a nearly linear relationship observed. Spherical solar modules exhibited a minor decrease in efficiency (±3.64%) compared to flat solar modules (±5.46%) under increased dust density, consistent with prior research. Dust accumulation affects solar cells by causing dust deposition, light scattering, and temperature rise. Flat solar panels are more susceptible to dust accumulation due to their larger surface area, which attracts more dust particles. In contrast, spherical cells’ smaller surface area minimizes dust build-up, making them less prone to efficiency loss. The study also examined the impact of solar intensity and tilt angle on efficiency. Spherical cells demonstrated greater resilience in varying light conditions and tilt angles, maintaining efficiency across a wider range of scenarios than flat panels. These findings emphasize the importance of considering dust accumulation when designing and maintaining solar panels, with spherical modules offering advantages in dusty environments and under changing sunlight conditions.

Numerical investigation on influence of different geometrical cavity flame holders and flame stabilization mechanism in hydrogen fueled multi-strut-based scramjet combustor

A detailed computational study was carried out to explore how the presence of a cavity and cavity angles influence the performance and combustion mechanisms within a scramjet combustor. This research utilized ANSYS Fluent 2021 to create hexahedral meshes and simulate the complex fluid dynamics in scramjet engines equipped with dual strut injectors. The simulations addressed various critical aspects of fluid mechanics, including the continuity, momentum (via the Navier-Stokes equations), and energy equations. These equations were used to model non-reacting flows, while the species transport equations were applied to analyse reacting flows. The turbulence within the combustor was modelled using the standard K-ε model, a common choice for such high-speed aerodynamic evaluations. The study's primary goal was to assess the effects of different geometrical configurations of cavity flame holders on the performance characteristics of an H2-based scramjet combustor overall efficiency, focusing on mixing efficiency, combustion performance, and total pressure loss. Both configurations with and without a cavity were examined. Key findings indicate that incorporating a cavity into the combustor design leads to developing a robust recirculation zone within the cavity area. This recirculation zone is pivotal in enhancing fuel-air mixing and combustion efficiency, with cavity-based combustors showing an earlier onset of combustion and achieving peak combustion efficiencies around 90–95%. The extent of the recirculation region is notably influenced by the proximity of the strut injector to the cavity's length. Additionally, the presence of a shear layer within the cavity generates a weak shock at the cavity's trailing edge. This shock interaction can adversely affect scramjet combustor performance, especially at higher cavity angles (α) and specific geometric configurations, such as an L/D ratio of 4 and α=30°. The L/D ratio of 4 and α=30° combustor model results in a 13.8% increase in turbulence intensity, which raises air-fuel mixing and there by improves mixing and combustion efficiency by 14.23% and 13.34%, compared to the other depth of the cavities. This advantage is critical, especially considering the compact length of the combustor, which is a desirable attribute in scramjet design.

Ray tracing design-optimization & experimental validation of water based optical filter to reduce solar PV module heating

The operating temperature of a photovoltaic (PV) module significantly impacts its efficiency. Increased temperatures reduce the efficiency due to a negative thermal coefficient, which decreases its power above standard test conditions (25 °C, 1000 W/m2). This research targets the reduction of thermal load on PV modules through the incorporation of a water-based optical filter, designed and optimized using ray tracing techniques. The optimal thickness for the glass was determined as 3 mm and 5 mm for the water layers of the filter, providing the best yield. The filter effectively absorbs 92 % of the infrared radiation and 47 % of the ultraviolet spectral flux, significantly reducing heat-induced efficiency losses in the PV module. Water-based optical filter system reduces the module temperature up to 9.80 °C. The optical filter-based PV system achieved a 4.56 % increase in electrical efficiency compared to the reference module, with an average efficiency of 12.19 %. The heated water, reaching up to 48.25 °C, can be reused for various industrial processes, providing both cooling for PV modules and a hot water source, making it versatile and efficient for regions needing both electricity and hot water.

Addressing the efficiency loss and degradation of triple cation perovskite solar cells via integrated light managing encapsulation

Here, we present a holistic encapsulation method for perovskite solar cells to address both optical performance losses at the air-cell interface as well as intrinsic and extrinsic stability challenges. Our one-step method provides shielding to PSCs from oxygen and moisture-induced degradation as well as in situ patterning for light management. As a result of embedding the antireflective coating onto the front side of the cell, the power conversion efficiency (PCE) of the PSCs was increased from 14.1 ± 0.8 % to 15.6 ± 0.8 %, indicating an 8 % relative improvement. Moreover, the encapsulated devices kept their initial performance after 90 % relative humidity and water immersion tests. The outdoor exposure test showed no degradation for the encapsulated cells after 24 h of resting at −17 °C and maximum wind speeds of 7 m/s on average. Additionally, the encapsulation strategy was instrumental in mitigating oxygen and humidity-induced degradation during ISOS-LC tests, retaining up to 80 % of the initial performance for the encapsulated devices after 360 h. This research establishes in situ encapsulation and patterning as a promising solution for reducing optical losses and extrinsic instabilities in PSCs. The choice of flexible encapsulant enables it to be used for both rigid and flexible PSCs in a wide range of applications.

Dual purpose of superheated steam treatment: Inactivating surface pathogens of pork belly and replacing blanching

Superheated steam (SHS) treatment is increasingly recognised as an emerging thermal sterilisation technology in food processing because of its high energy efficiency, time-saving benefits and minimal quality loss in raw materials. The aim of this study was to examine the efficacy of SHS treatment as a high-temperature pre-treatment approach for eliminating foodborne pathogens on the surface of pork belly and to determine its impact on nutritional quality. The SHS treatment at 180 °C and 25 kg h−1 for 50 s achieved sterilisation rates of 98.15% ± 1.70%, 96.59% ± 1.40% and 91.30% ± 2.14% for Salmonella typhimurium, Listeria monocytogenes and Staphylococcus aureus, respectively, which were three times higher than those achieved by microwave (MIC) sterilisation (700 W, 20 s). Furthermore, SHS-treated pork belly exhibited the highest moisture content and lowest cooking loss, with no significant changes in pressing loss and pH values. Compared with samples treated with MIC and blanching (99 °C ± 1 °C, 2 min), those treated with SHS showed significantly lower TBARS value and protein carbonyl content, with an increasing trend in L∗ values. Meanwhile, SHS treatment not only preserved the tenderness of the pork belly to the greatest extent but also yielded the highest sensory score of 7.81 out of 9. These findings indicate the potential of SHS treatment in producing premium-quality pasteurised pork belly.

Finding robustly fair solutions in resource allocation

In this study, we consider resource allocation settings where the decisions affect multiple beneficiaries and the decision maker aims to ensure that the effect is distributed to the beneficiaries in an equitable manner. We specifically consider stochastic environments where there is uncertainty in the system and propose a robust programming approach that aims at maximizing system efficiency while guaranteeing an equitable benefit allocation even under the worst scenario. Acknowledging the fact that the robust solution may lead to high efficiency loss and may be over-conservative, we adopt a parametric approach that allows controlling the level of conservatism and present the decision maker alternative solutions that reveal the trade-off between efficiency and the degree of conservatism when incorporating fairness. We obtain tractable formulations, leveraging the results we provide on the properties of highly unfair allocations. We demonstrate the usability of our approach on project selection and shelter allocation applications.

Leveraging External Aggregated Information for the Marginal Accelerated Failure Time Model.

It is becoming increasingly common for researchers to consider leveraging information from external sources to enhance the analysis of small-scale studies. While much attention has focused on univariate survival data, correlated survival data are prevalent in epidemiological investigations. In this article, we propose a unified framework to improve the estimation of the marginal accelerated failure time model with correlated survival data by integrating additional information given in the form of covariate effects evaluated in a reduced accelerated failure time model. Such auxiliary information can be summarized by using valid estimating equations and hence can then be combined with the internal linear rank-estimating equations via the generalized method of moments. We investigate the asymptotic properties of the proposed estimator and show that it is more efficient than the conventional estimator using internal data only. When population heterogeneity exists, we revise the proposed estimation procedure and present a shrinkage estimator to protect against bias and loss of efficiency. Moreover, the proposed estimation procedure can be further refined to accommodate the non-negligible uncertainty in the auxiliary information, leading to more trustable inference conclusions. Simulation results demonstrate the finite sample performance of the proposed methods, and empirical application on the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial substantiates its practical relevance.

Preprocessing Text Data for the Doc2Vec Model in the Automatic Classification of Tickets in Support Centers of Software Providers

Leading software providers typically implement customer technical support functions, which are crucial for promoting and enhancing the competitiveness of their products and services in global markets. The high volume and heterogeneity of support tickets (functional, temporal, linguistic, etc.) highlight the importance of efficient classification systems. Effective classification optimizes the distribution of these tickets among support center specialists and automates their processing using an established knowledge base. However, classifying these tickets is a loosely formalized task. For companies that have accumulated substantial data on customer requests, automating classification through machine learning methods and natural language processing models, such as Word2Vec, FastText, BERT, and GPT, becomes feasible. It is generally accepted that classification effectiveness primarily depends on the model employed. Nevertheless, the quality of these models is significantly influenced by the nature of the training data. Literature review of the reveals significant research interest in methods for the automatic classification of tickets specifically tailored to the operational conditions of software provider support centers. However, there is a noticeable gap in the literature regarding the impact of data preprocessing on the quality of these models. The article aims to clarify the techniques of data preprocessing and analyze their impact on the effectiveness of text classification, considering the specificity of software provider support centers. This study examines the stages of the automatic classification process for tickets, accounting for the unique characteristics of the data (customer text requests). A relevant set of specified methodological and instrumental tools was developed and tested using open data from a global software provider (DevExpress). The testing involved a database of 165,000 tickets. The study's results indicate that preprocessing can improve classification metrics such as F-measure, Precision, and Recall from 77% to 79%. Additionally, preprocessing significantly reduces the dimensionality of text data (by 48.2%) and increases model training speed (by 26.5%) without loss of accuracy, ensuring cost-efficiency and operational efficiency in the use of computational resources.

Post‐Mortem Analysis of Building‐Integrated Flexible Thin Film Modules

ABSTRACTFlexible, lightweight thin film (TF) photovoltaic (PV) modules offer a unique opportunity for integration into non‐planar surfaces unable to support heavy weights. While such applications increase the potential for PV in urban areas, the reliability implications are yet to be investigated. Here, prototypes of corrugated rooftiles with integrated Cu (In,Ga)Se2 (CIGS) modules were investigated after 3 years of outdoor operation. Their performance before and after the outdoor exposure was compared and defects were localized. An unpackaging method was developed, allowing access to the solar cells for more detailed characterization of present defects without causing additional damage or changes to existing defects. To our knowledge, this was the first time such an unpackaging method was successfully applied to flexible TF PV modules. The relative efficiency loss ranged from 17% to 43%, mostly due to short‐circuit current (ISC) loss and series resistance (RS) increase. The predominant cause of the RS increase was the delamination at the interconnects, ascribed to thermomechanical stresses caused by outdoor temperature fluctuations. The ISC loss was mainly caused by localized delamination of CIGS from the molybdenum (Mo) back‐contact. The occurrence of such delaminated areas pointed to presence of high local stresses during outdoor operation, possibly due to thermal fluctuations, applied deformation and/or mechanical impact. Two other types of delamination defects were found with no observable impact on performance. These results show the necessity for further optimization in the material choice and processing of TF flexible modules, to avoid mechanical stress related failures upon integration into curved surfaces.

Palygorskite improves growth performance and prevents liver damage in avian pathogenic Escherichia coli-challenged broiler chickens at an early age.

Avian pathogenic Escherichia coli (APEC) is a major bacterial infection that causes economic losses in the global poultry industry. Palygorskite (PAL) has been shown to enhance growth performance while improving antioxidative and anti-inflammatory properties of broilers. This study evaluated the protective effects of PAL on growth performance and liver function in broilers subjected to APEC challenge. A total of 320 one-day-old male Arbor Acres chicks were divided into four groups with eight replicates of ten birds each, based on a 2×2 factorial arrangement (basal diet or 5g/kg PAL-supplemented diet) and inoculation (bacterial culture medium or APEC). PAL increased body weight gain (BWG) prior to APEC challenge (P < 0.05). However, APEC caused losses in BWG, feed intake (FI), and feed efficiency, along with increased relative hepatic weight, hepatic pathology scores, and hepatic-cell apoptosis rate (P < 0.05). Compared to normal birds, APEC increased interleukin (IL)-1β, interferon-γ (IFN-γ), tumor necrosis factor-α (TNF-α), malondialdehyde (MDA), and nitric oxide (NO) levels, as well as lysozyme (LZM) and myeloperoxidase (MPO) activities, while decreasing total antioxidant capacity (T-AOC) and IL-10 levels, and total superoxide dismutase (T-SOD) and catalase (CAT) activities in both serum and liver, APEC also raised alanine aminotransferase (ALT) and aspartate aminotransferase (AST) activities, but reduced total protein (TP), albumin (ALB), immunoglobulin (Ig) A, IgG, and IgM levels in serum (P < 0.05). Moreover, APEC increased hepatic mRNA level of IL-1β, IFN-γ, TNF-α, nuclear factor kappa B, and inducible nitric oxide synthase (iNOS), while inhibited mRNA level of IL-10 (P < 0.05). In contrast, PAL increased BWG and FI, alleviated hepatic-cell apoptosis rate during the challenge period (P < 0.05). An incorporation of PAL reduced triglyceride and NO contents, ALT and AST activities, while increasing TP, ALB, IL-10, IgG, and IgM levels in serum, enhancing serum T-SOD and CAT activities, elevating hepatic T-AOC and CAT activities, inhibiting hepatic MDA accumulation, and reducing IL-1β levels and LZM activity in both liver and serum (P < 0.05). An interactive effect was found for hepatic TNF-α and iNOS mRNA expression, in which PAL inhibited their mRNA expression in APEC-challenged birds (P < 0.05). Overall, PAL addition partially mitigated the negative impact of APEC challenge on growth performance and liver function of broiler chicks at an early age.

Autoregressive distributed lag-based dynamic uniformity modeling and monitoring approaches for superconductor manufacturing

ABSTRACT High-temperature superconductors (HTS), known for their high efficiency and low energy loss, have found profound applications across various fields, driving the demand for long, uniformly performing tapes. However, ensuring uniform performance over extended lengths of HTS tapes, often characterized by the consistency of critical current, remains challenging due to fluctuations in growth conditions during manufacturing. To elucidate the mechanisms underlying variations in tape uniformity and enable real-time monitoring of associated parameters, we propose an Autoregressive Distributed Lag (ADL)-based Dynamic Uniformity Modeling and Monitoring (ADUM2) approach. This method integrates uniformity measurement, the identification of critical process parameters and real-time monitoring within the manufacturing process. The ADUM2 approach is applied to the advanced metal organic chemical vapor deposition (A-MOCVD) process, a pilot-scale method for superconductor manufacturing. Our model demonstrates superior performance compared to benchmark methods, accounting for over 80% of the total variance in the data and identifying 13 key process parameters influencing the uniformity of HTS tapes. This study offers significant insights into the high-temperature superconductor manufacturing process and holds the potential to facilitate the production of cost-effective, uniformly performing long superconducting tapes in the future.

Performance of a BeO-based dosimetry system for proton and electron beam dose measurements

This study aims to evaluate the performance of the BeO-based myOSLchip system (RadPro International GmbH, Remscheid, Germany) for dosimetry of proton and electron radiotherapy beams. Although beryllium oxide (BeO) has been recognised as a promising material for luminescence dosimetry in radiotherapy, this research extends beyond material properties and examines the entire BeO-based dosimetry system, including the detector, holder, and readout components.Packages of myOSLchip detectors were irradiated either in a (70−230) MeV proton beam or in a 16 MeV electron beam. The readouts were carried out using the portable myOSLchip reader. In the electron beam, tests on the precision, dose response up to 100 Gy and dose-rate effects of the system were carried out. In the proton beam, the system was tested for its dose response (up to 10 Gy), fading, and linear energy transfer (LET) response.For proton irradiations, the myOSLchip BeO OSLDs exhibited stability within 2 % over 135 days, as well as a linear dose response in the tested range, (0.1−10) Gy. The efficiency showed a reduction for proton beams with LET values (for water) above 0.6 keV/μm, with up to 40 % loss in efficiency at 4 keV/μm. For the electron irradiations, they showed a linear dose–response up to 20 Gy and dose-rate independence, with a constant response at least up to 2.99×105 Gy s−1. Using individual chip sensitivity correction, the precision for a single chip was around 3.5% (standard deviation of the data of all chips) and for a package comprising four chips was 1.7% (standard deviation of the mean of the four chips).These findings suggest the myOSLchip system’s potential as a reliable alternative to existing dosimetry systems in clinical applications.

Towards bespoke gas permeability by functionally graded structures in laser-based powder bed fusion of metals

Permeable, media transporting, components are an integral part in numerous technical applications. In gas turbines combustors, for example, gaseous oxidizer and fuel are transported separately into the burner, where they are injected and mixed, and subsequently combusted. The mixture homogeneity strongly affects the combustion performance and emissions formation and is, amongst other, determined by the spatial distribution of fuel injection ports. In this context, porous media provide the limiting case for a spatial distribution of media-injecting pores, yet is typically associated with a high pressure drop that yields a loss in efficiency. In this study, possibilities of achieving gas permeability in additively manufactured porous structures are investigated. The objective is to selectively functionalize the permeable layers for gaseous media supply with low pressure loss and, when needed, enable a targeted mixing of different gas streams. For this purpose, a laser-based powder bed fusion process (PBF-LB/M) was used in this study. It offers the opportunity to manufacture varying porosities inside complex monolithic metal parts. To produce the porous structures and to achieve gas permeability, the effect of scan rotation angle, hatch distance, build-up direction and length of the porous specimen is investigated. Due to the high temperatures present in combustion systems, the present work utilizes Inconel 718 material. The AM gas permeable specimen are experimentally characterized by means of surface topography, micro X-ray computed tomography (µXRCT) as well as flow and pressure loss test. The results show, that the AM process parameter provide effective control parameters to adjust the permeability. The strongest effect originates from the hatch distance for a given build-up direction. Depending on the scan rotation, the flow transitions from a turbulent pipe flow to a Darcy flow as present in conventional porous media. A structured alignment and connectivity of pores can be realized as evident in the µXRCT results, surface topography and the flow measurements. Residual powder, powder adhering to the pore walls and stochastic closure of pores or channels lead to deviations and need to be considered when designing respective parts. Nonetheless, the results further show that a directional dependence of the permeability and the build-up direction can be realized and controlled. Consequently, when considering the AM build-strategy in the design of components, this directed permeability can be functionalized in the generation of gas transporting and gas mixing layers separately by adjusting the AM processing parameter.

Effect of streamlining prior authorization processes for systemic cancer treatments on efficiency and financial losses.

412 Background: Prior authorizations (PAs) for systemic cancer treatments are a barrier to timely quality cancer care delivery. The high administrative burden to complete peer to peer’s (P2P) and appeals leads to care delays and revenue losses. At our tertiary academic cancer center, in partnership with our cancer registry and Epic teams, we shifted the clerical work required for PAs from clinicians to certified tumor registrars (CTRs) to increase authorization efficiency and decrease financial losses from denials. Methods: Clinicians place the treatment plan order which goes to the CTR work queue. We leveraged the Epic staging smart form to consolidate and auto-populate common elements needed for PA. The CTRs then complete and validate the form prior to the authorization specialists obtaining the PA. We compared the pre (1/2022-9/2022) and post-implementation (11/2022-4/2024) periods on our primary outcomes: average monthly number of PAs pending review (including P2P, appeals and authorizations requiring clarifying clinical documentation), average monthly denial rate and average time spent on PAs by the authorization specialists. We compared the financial losses from denied PAs from calendar year 2022 to 2023. Analyses were conducted using descriptive statistics. Results: There was a 1.4% reduction in the average monthly number of PA’s pending review (350 vs 345). The average monthly authorized rate was steady from the beginning of the intervention (94%) to present time (95%). The average monthly denial rate was 2.9% at the beginning of the intervention and 0.9% at present time. There was a consistent decrease in the average time a PA was spent in pending review status: 118 hours in 2022, 102 hours in 2023 and 79 hours in quarter 1 of 2024. Despite the overall increase in volume of authorizations submitted, there was an overall cost savings of $27,392,894 from 2022 ($49,964,703) to 2023 ($22,571,809) from the decrease in denials. In 2022, 6.2% of total approved charges were denied and this decreased to 2.7% in 2023. Conclusions: By leveraging the EHR and optimizing existing non-clinical staff workflows, we maintained sustained average authorized and denial rates despite overall volume going up due to improved authorization efficiency and reduced financial losses due to denials. Additionally, there were overall cost savings for the institution due to the decreased percent of denials of total approved charges. Future work will include further refinement of treatment and disease specific optimizations.

B-fields and Dust in Interstellar Filaments Using Dust Polarization (BALLAD-POL). II. Testing the Radiative Torque Paradigm in Musca and OMC-1

Polarization of starlight and thermal dust emission caused by aligned dust grains is a valuable tool to characterize magnetic fields (B-fields) and constrain dust properties. However, the grain alignment physics is not fully understood. To test the radiative torque (RAT) paradigm, including RAT alignment (RAT-A) and disruption (RAT-D), we use dust polarization observed by Planck and Stratosphere Observatory for Infrared Astronomy/High-resolution Airborne Wideband Camera Plus toward two filaments, Musca and OMC-1, with contrasting physical conditions. Musca, a quiescent filament, is ideal for testing RAT-A, while OMC-1, an active star-forming region OMC-1, is most suitable for testing RAT-D. We found that polarization fraction, P, decreases with increasing polarization angle dispersion function, S , and increasing column density, N(H2), consistent with RAT-A. However, P increases with increasing dust temperature, T d, but decreases when T d reaches a certain high value. We compute the polarization fraction for the ideal models with B-fields in the plane of sky based on the RAT paradigm, accounting for the depolarization effect by B-field tangling. We then compare the realistic polarization model with observations. For Musca with well-ordered B-fields, our numerical model successfully reproduces the decline of P toward the filament spine (aka polarization hole), having higher N(H2) and lower T d, indicating the loss of grain alignment efficiency due to RAT-A. For OMC-1, with stronger B-field variations and higher temperatures, our model can reproduce the observed P–T d and P−N(H2) relations only if the B-field tangling and RAT-D effect are incorporated. Our results provide more robust observational evidence for the RAT paradigm, particularly the recently discovered RAT-D.

Homogeneous reactive distillation: The influence of pressure drop on separation and reaction kinetics

This study investigates the Total Annual Cost (TAC) optimization of a reactive distillation (RD) process for methyl acetate (MA) production as a function of tray pressure drop, focusing on the trade-off between chemical reaction kinetics and separation efficiency. The analysis examines how variations in column diameter and weir height influence the TAC across different liquid hold-ups with and without incorporating a tray pressure drop in the simulations. Results indicate that for larger liquid hold-ups, the decrease in separation efficiency predominates over kinetic advantages, leading to higher energy costs when pressure drop is considered. Despite the loss in separation efficiency with a high weir height, a pressure drop-incorporated column design featuring a high weir height and small diameter is shown to achieve lower TAC due to the comparatively lower installed costs. A reduction of tray liquid hold-up of more than 50 % is found for the optimal column design in the considered case study when the tray pressure drop is considered. A sensitivity analysis towards a hypothetical infinite fast reaction is conducted to illustrate how the energy costs are affected by the kinetic rate of the chemical reaction.

Design of sustainable integrated energy systems for green ports – selection and sizing

Abstract Design of sustainable and integrated energy systems for marine port is a complex problem, involving multiple conflicting objectives like energy efficiency and minimum losses, cost-effectiveness, and avoiding excessive cycling and degradation. This paper addresses the sizing of integrated and sustainable port energy systems with renewable energy sources and energy storage systems based on two different methods. Both developed methods start by selecting design sets representing the gradual expansion of renewable sources and storage to the maximum size, limited by various constraints. Each design variant is evaluated based on the energy demands of the port, historical prices, and site energy production capacity. The first method, developed by ITK Engineering GmbH, uses a conventional deterministic forecasting approach with detailed annual data. The latter, developed by NTNU, employs several 24-hour data sets to capture annual energy dynamics. Key performance indicators for both methods are defined based on the total cost, with the benchmark cost obtained using the first (deterministic) method with 100% grid-supplied energy. Two virtual ports of different sizes (Port A and B) are established in two electric markets (1 and 2) for verification and benchmarking. The paper then discusses the influence of uncertainty in 24-hour data sets, used by the second (stochastic) method, for all cases.

Atomically dispersed Ru on flower-like In2O3 to boost CO2 hydrogenation to methanol

Metal-based catalysts are prevalent in the CO2 hydrogenation to methanol owing to their remarkable catalytic activity. Herein, Ru/In2O3 catalysts with different morphologies obtained by doping Ru into In2O3 with irregular, rod-like, and flower-like morphologies are used for catalytic CO2 hydrogenation to methanol. Results indicate that the flower-like Ru/In2O3 (Ru/In2O3-F) exhibits higher catalytic performance than Ru/In2O3 with other morphologies, achieving a 12.9% CO2 conversion, 74.02% methanol selectivity, and 671.36 mgMeOH·h−1·gcat−1 methanol spatiotemporal yield. Furthermore, Ru/In2O3-F maintains its catalytic stability over 200 h at 5 MPa and 290 °C. The promotional effect mainly stems from the fact that electronic structure of Ru can be effectively adjusted by modulating the morphology of In2O3. The strong interaction between atomically dispersed Ru and In2O3-F enhances the structural stability of Ru, inhibiting the agglomeration of the catalyst during the reaction process. Furthermore, density-functional theory calculations reveal that highly dispersed Ru atoms not only perform efficient and rapid electronic gain and loss processes, facilitating the catalytic activation of H2 into H intermediates. It also enables the generated reactive H to rapidly overflow to the surrounding In sites to participate in CO2 reduction. These findings provide a theoretical basis for the development of high-performance catalysts for CO2 hydrogenation.

Reusable metal-free mesoporous carbon-catalyzed reductive N-formylation of nitroarenes and quinolines

The high-value transformation of nitrogen-containing compounds through a facile, cost-effective, and eco-friendly one-pot strategy holds significant importance. However, this process typically involves the use of metal catalysts and is limited by low activity as well as the requirement of high temperature and pressure. Herein, we describe a general and efficient metal-free N-doped mesoporous carbon material using well-defined ligand 1,10-phenanthroline as the precursor and silica colloid as the hard template. Formic acid is both a reducing agent and a formylation reagent, and structurally distinct mono- or multi-substituted nitroarenes and quinolines can be selectively N-formylation in a one-pot method. The catalyst can be easily recovered without observable loss of efficiency for ten consecutive uses. The control experiments and density functional theory (DFT) calculations indicate that formic acid mainly obtains active hydrogen in the form of O–H bond cleavage, which benefits from the strong adsorption and enhanced activity generated by the interaction between graphitic nitrogen species in the catalyst and formic acid. The excellent catalytic performance of the meso-phen-X catalyst is attributed to the synergistic effect of graphitic N and large specific surface area, providing a promising method for the development of non-metallic catalyst-modified carbon materials.