Advanced Design Research Articles

Suppression of Initial Degradation via an Interfacial Charge-Induced Overshooting Effect in Solution-Processed Organic Light-Emitting Diodes.

As the chemical stability of organic materials in organic light-emitting diodes (OLEDs) greatly impacts devices' lifetime, a thoughtful and advanced design of materials and device structures is necessary. In our work, we have achieved lifetime enhancement at its initial stage for solution-processed OLEDs. This improvement was realized through the implementation of a double electron transporting layer (dETL) composed of 2-[4-(9,10-dinaphthalen-2-yl-anthracen-2-yl)-phenyl]-1-phenyl-1H-benzoimidazole (ET) and hydroxyquinolinolato-lithium (Liq). A giant surface potential was generated at the surface of a constituent electron transport layer (ETL) that contained a higher concentration of Liq with high polarity. This giant surface potential simultaneously promoted the injection of trapped/accumulated electrons through the interface within dETL and the injection of holes from the anode, generating more exciton recombination events and ultimately enhancing efficiency by 133.0% and lifetime LT95 (luminance dropped by 5%) by 300% with an overshooting effect. Additionally, the degradation at the emitting layer was mitigated by shifting the degradation zone to the dETL, which was evidenced by laser desorption/ionization-time-of-flight (LDI-TOF) mass spectroscopy.

Photo-ferroelectric perovskite interfaces for boosting VOC in efficient perovskite solar cells

Interface engineering is the core of device optimization, and this is particularly true for perovskite photovoltaics (PVs). The steady improvement in their performance has been largely driven by careful manipulation of interface chemistry to reduce unwanted recombination. Despite that, PVs devices still suffer from unavoidable open circuit voltage (VOC) losses. Here, we propose a different approach by creating a photo-ferroelectric perovskite interface. By engineering an ultrathin ferroelectric two-dimensional perovskite (2D) which sandwiches a perovskite bulk, we exploit the electric field generated by external polarization in the 2D layer to enhance charge separation and minimize interfacial recombination. As a result, we observe a net gain in the device VOC reaching 1.21 V, the highest value reported to date for highly efficient perovskite PVs, leading to a champion efficiency of 24%. Modeling depicts a coherent matching of the crystal and electronic structure at the interface, robust to defect states and molecular reorientation. The interface physics is finely tuned by the photoferroelectric field, representing a new tool for advanced perovskite device design.

Microenvironment Engineering of Heterogeneous Catalysts for Liquid-Phase Environmental Catalysis.

Environmental catalysis has emerged as a scientific frontier in mitigating water pollution and advancing circular chemistry and reaction microenvironment significantly influences the catalytic performance and efficiency. This review delves into microenvironment engineering within liquid-phase environmental catalysis, categorizing microenvironments into four scales: atom/molecule-level modulation, nano/microscale-confined structures, interface and surface regulation, and external field effects. Each category is analyzed for its unique characteristics and merits, emphasizing its potential to significantly enhance catalytic efficiency and selectivity. Following this overview, we introduced recent advancements in advanced material and system design to promote liquid-phase environmental catalysis (e.g., water purification, transformation to value-added products, and green synthesis), leveraging state-of-the-art microenvironment engineering technologies. These discussions showcase microenvironment engineering was applied in different reactions to fine-tune catalytic regimes and improve the efficiency from both thermodynamics and kinetics perspectives. Lastly, we discussed the challenges and future directions in microenvironment engineering. This review underscores the potential of microenvironment engineering in intelligent materials and system design to drive the development of more effective and sustainable catalytic solutions to environmental decontamination.

Car detection algorithm in urban based on YOLOv5

Car detection is essential to promote the development of intelligent technologies such as autonomous driving and car forward collision warning. To deal with low detection accuracy, poor real-time performance and robustness of existing object detection algorithms, a YOLOv5-based car detection algorithm is used. The advanced structure design of Backbone, Neck and Head in YOLOv5 demonstrates powerful feature extraction and multi-scale object detection capabilities. The detection results reveal that the algorithm is able to quickly recognize cars in images in different urban scenes, and the detection accuracy can reach more than 95%, which can satisfy the application demands for real-time car detection.

Multi-Fidelity Aeromechanical Design Framework for High Flow Speed Multistage Axial Compressors

Abstract The development of novel engine architectures is vital in achieving the aviation sector’s net-zero carbon emission target by 2050. With today’s digital decade providing support for an accelerated technology maturation, the challenge for turbomachinery design remains to significantly push the limits of current performance within an ambitious development lead time. In this context, it is essential to adopt a design framework where the predictive models or simulations employed target a sufficiently reliable performance assessment. These models must be tailored to the dynamics of evolving industrial design processes, and therefore continuously balance required design flexibility, robust evaluation, appropriate fidelity (i.e. the level of detail and accuracy they provide), and resulting evaluation time. This paper discusses a framework for designing axial compressors and its application to the aeromechanical optimisation of a high-speed compressor rotor. The design environment integrates geometry parametrisation, modular evaluation with different levels of fidelity for the aerodynamic and structural models, and surrogate-based optimisation (SBO) capabilities. It is shown how the combination of a modular sequencing of the different models and the acceleration enabled by high-performance computing (HPC) and machine learning allows for a more advanced preliminary design. A significant gain in isentropic efficiency is attained while satisfying all structural constraints. At the same time, it is demonstrated that the framework is compatible with the characteristics of the preliminary design phase: both in its ability to adapt to cycle and design changes as well as regarding the turnaround time of the optimisation itself.

Biomimetic multiscale structure with hierarchically entangled topologies of cellulose-based hydrogel sensors for human-computer interaction

The development of high-performance cellulose-based sensors with superior interfacial compatibility, flexibility, and strength has always been challenging. Drawing inspiration from the intricate multiscale hierarchy found in resilient natural materials, the incorporation of this structure into cellulose-based hydrogels using biomimetic strategies is anticipated to enhance their properties. Therefore, the cellulose/polyacrylamide (PAM) hybrid hydrogels are fabricated using the aqueous AlCl3/ZnCl2 system through an all-green one-pot method at room temperature, achieving efficient dissolution of cellulose at multiple scales and in-situ polymerization of polyacrylamide. The multiscale cellulose/PAM hydrogels achieve good interfacial compatibility, with the reinforcing mechanism being confirmed through a combination of experimental validation and atomic simulations. The findings underscore the key elements that drive the multiscale behavior of hydrogels, encompassing a range of factors such as multiple interfacial interactions, hierarchical molecular entanglements, and microskeleton reinforcement. The hydrogels exhibit satisfactory stretchability (412 %), compressive strength (1.2 MPa), conductivity (1.65 S m−1), and ultralong circulability (> 12,000 cycles), rendering them suitable for various scenarios of human-computer interaction. This work establishes a comprehensive interpretation of the strengthening mechanism in cellulose-based multiscale hierarchical structures, thereby providing novel insights for the advanced design strategies of other promising hierarchical materials.

Scaling Heat Transfer and Pressure Losses of Novel Additively Manufactured Rib Designs

Abstract Rib turbulators are a key cooling feature that enables increased heat transfer on the interior of gas turbine components. As metal additive manufacturing becomes available for developing turbine parts, it is becoming increasingly important to understand how the surface roughness intrinsic to this manufacturing method impacts the performance of rib turbulators. To explore what impact roughness has on rib turbulator performance, several relevant scale test coupons were manufactured on two different additive machines out of IN718. Additionally, several coupons were built at large scales to effectively reduce the relative roughness size impacts and determine scale effects. A range of different wavy broken rib designs, varying both rib wavelength and orientation within a channel were evaluated. Coupon geometry and surface roughness were characterized using both computed tomography scans and optical profilometry. Variations between the print methods were found to have limited impact on the surface roughness, but significant impact on the accuracy to meet the design intent with rib heights varying by 30%. Following characterization, coupons were flow tested and it was found that the ribs that more regularly disturbed the flow as a function of their geometry most significantly enhanced heat transfer and pressure drop. The performance index of the broken wavy ribs was similar to other advanced rib designs, such as broken or V shaped ribs, but augmentations to heat transfer and pressure drop were generally lower. The rib performance was compared as a function of relative roughness, and it was found that increases in relative roughness resulted in increased friction factor and heat transfer, especially at higher Reynolds numbers.

Learning from Designing a Board Game for Policy Thinking in Computer Science

Technology does not exist in a vacuum, but is influenced by society and at the same time shaping it. In order to educate future computer scientists to be able to assess and create technology in a conscious and responsible manner, we provide first-year Computer Science (CS) students with an introductory course on different ways of thinking about CS by offering them a transdisciplinary view of the field. As we continuously strive to use engaging teaching methods to foster long-lasting interest for the topics of the course, as well as enhancing students’ learning experiences, we have introduced a unique game-based learning pipeline: In a game design course, advanced CS students design non-digital games that address various topics from the introductory course. These games are later played by first-year CS students, who are reflecting on the content and their experience as a part of their course assignments. In order to learn from the first iteration of this process, we analyse one of the games created, in particular its design and the educational objectives intended by the game designers, including the students’ feedback. We found that the game was perceived to be good in achieving learning outcomes; however, it scored even higher in terms of being an interesting and entertaining game. Overall, we conclude that the game was successful in creating an engaging learning experience, demonstrating the potential for game-based learning with non-digital games. This case study also highlights the importance of creating a suitable environment for game-based learning approaches to enhance the educational effects and utilise individual strengths of educational games, providing inspiration and groundwork for future research.

Advanced design of indented-standing surface acoustic wave (i-SSAW) device for platelet-derived microparticle separation from whole blood

Isolating submicron microvesicles (MVs) from blood has become important for clinical diagnosis and researches. Advanced design of indented-standing surface acoustic wave (i-SSAW)-based device with a U-shaped microchannel is proposed for extracting platelet-derived microparticles (PDMPs) from whole blood. Unlike the previous acoustic devices, the cross-sectional shape of the microchannel was manipulated to enhance the device performance, rather than the patterned interdigitated transducers. Cross-sectional shape-dependent device performance was evaluated using rectangular channels with different heights and U-shaped channel with whole blood sample with 40 % hematocrit. Effect of the flow rates on acoustic migration of red blood cells (RBCs) was examined at 20 V fixed voltage. In addition, RBC and platelet removal was examined using different applied voltages for i-SSAW operation. Finally, high-purity (approximately 100 %) and high-recovery (approximately 55.6 %) platelet-poor plasma was separated from whole blood at 30 μL/min without platelet activation.

Study of the dynamic response of an offshore continuous beam bridge under nonlinear wave and scour

The study highlights the critical factors and findings regarding bridge damage susceptibility during typhoons and hurricanes, primarily due to extreme waves, scour, and storm surges. While existing research has extensively studied bridges' responses to either extreme waves or scour individually, their combined effects have not been sufficiently explored. Experiments were conducted on a scaled two-span bridge to examine its behavior under simultaneous wave and scour conditions. Results from these experiments indicate that as scour depth increases, there is a corresponding escalation in displacement of the bridge pier, acceleration of the bearing platform, and strain along the pile foundation. To further investigate these dynamics, fluid-structure interaction analysis was employed, revealing significant insights. Notably, the study found that wave height exerts a substantial influence on wave load. For instance, at a wave height of 6 m, the average peak horizontal wave load on bridge piers was 2.48 times higher than at 3 m wave height. Moreover, local scour was identified as a critical factor reducing the bearing capacity of pile foundations, thereby significantly impacting the bridge's dynamic response to nonlinear waves. Under identical wave conditions, varying scour depths (3 m, 6 m, 9 m, and 12 m) resulted in increases in peak lateral displacements at the pier top compared to non-scouring conditions. The study concludes by emphasizing the increasing risk posed to pile foundations with deeper scour depths, particularly under stronger wave conditions. Consequently, there is a crucial need to enhance the resilience of offshore bridges against these dual hazards through advanced design and protective measures.

Unraveling the mechanism of CH3CH2OH dehydrogenation on m-ZrO2(111) surface, Au13 cluster, and Au13 cluster/m-ZrO2(111) surface: A DFT and microkinetic modeling study

The dehydrogenation of CH3CH2OH to produce CH3CHO and H2 is crucial for generating valuable chemicals. This study uses density functional theory (DFT) and microkinetic modeling to elucidate the reaction pathways on the m-ZrO2 (111) surface, Au13 cluster, and Au13 cluster/m-ZrO2(111) surface. Dehydrogenation on both the m-ZrO2(111) surface and Au13 cluster occurs via two key steps. The first step involves the cleavage of the OH bond in CH3CH2OH, forming a CH3CH2O moiety and an OH bond with the lattice oxygen on m-ZrO2 (111) surface or with a low-coordination Au atom in the Au13 cluster, respectively; while the formation of H2 takes place in the second step; however, the results microkinetic modeling render low values for the corresponding rate constants for this reaction path. Although the Au13cluster/m-ZrO2(111) surface introduces an additional step, where the H atom migrates from the m-ZrO2 (111) surface to the Au13 cluster, we shown that the relative energy of the three transition states is similar, the activation barriers are lower, and the rate constants are favorable for the dehydrogenation of CH3CH2OH. These results demonstrate the potential of the Au13 cluster supported on m-ZrO2(111) for efficient and selective CH3CHO and H2 production, providing valuable insights for advanced catalytic system design.

A novel technique to detect and mitigate harmonic during islanding in grid connected PV system

The integration of photovoltaic (PV) systems into the power grid has become increasingly prevalent, providing sustainable and renewable energy solutions. However, the occurrence of islanding events, where a portion of the PV system operates independently from the main grid, presents challenges in maintaining power quality. This research paper investigates the harmonic distortions during islanding in grid-connected PV systems and proposes effective mitigation strategies. The study employs advanced simulation tools to analyse the dynamic behavior of the PV system during islanding scenarios, focusing on the occurrence and characteristics of harmonics. A detailed investigation into the root causes of harmonic distortions is conducted, considering factors such as grid fluctuations, inverter operation, and system impedance. Based on the findings, this paper introduces novel harmonic mitigation techniques tailored for islanding conditions. These techniques encompass advanced control algorithms, filter designs, and modulation strategies to suppress harmonics and enhance the overall system performance during islanded operation. Comparative assessments of different mitigation approaches are presented, evaluating their effectiveness in minimizing harmonic distortions and maintaining grid code compliance. The research contributes valuable insights to the field of grid-connected PV systems, offering a comprehensive understanding of harmonic issues during islanding events and proposing innovative solutions for their mitigation. The outcomes of this study are crucial for advancing the reliability, stability, and power quality of PV systems that are connected to the grid, which makes it possible for green energy sources to be added to the grid without any problems.

Innovative Machine Learning Strategies for DDoS Detection: A Review

This is a broad survey that investigates the use of machine learning (ML) methods for detecting distributed denial of service (DDoS) attacks. Traditional intrusion detection systems face difficulties in application-layer DDoS attacks because they target legal web traffic forms using standard transmission control protocol connections. This paper reviews different ML methods used in recent studies to tackle these issues. These studies use various data sets, such as UNSW-np-15, CICDDoS2019, and the novel dataset LATAM-DDoS-Internet of Things., which prove the efficacy of the proposed models in terms of accuracy and performance metrics. The second group of studies shows more advanced designs, such as protocol-based deep intrusion detection and autoencoder-multi-layer perceptron. These use deep learning to find features and group attacks. All of these approaches present favorable outcomes when it comes to distinguishing normal, DoS, and DDoS traffic with a high level of accuracy. Furthermore, the review discusses works that emphasize the early detection of noise-robust models and distributed frameworks. Different techniques, such as snake optimizer with ensemble learning, metastability theory, and spark-based anomaly detection, highlight the trend of predicting DDoS attacks, whereas hyperband-tuned deep neural networks and evolutionary support vector machine models show higher accuracy in cloud systems as well as software-defined networking environments. Hence, this review gives a general observation of how DDoS attacks develop on their way and proves that ML techniques help to strengthen network security.

Analyzing the Indirect Effects of Lightning on Unmanned Aerial Vehicle Navigation Receivers

To investigate the interference effects of lightning on unmanned aerial vehicle (UAV) navigation receivers, an analytical approach for the evaluation of indirect lightning effects is suggested. The blocking mechanism of lightning pulses on the receiver is analyzed using the vector method. A behavioral-level simulation model of the receiver’s radio frequency (RF) front-end is constructed, and a lightning pulse injection simulation is performed based on the advanced design system (ADS). The simulation results indicate that lightning pulses induce blocking interference on the RF front-end of the navigation receiver, reducing its sensitivity and dynamic range. This interference is attributed to gain compression and degradation of the noise figure in the low-noise amplifier (LNA). To further validate the simulation results, a pin injection test is carried out to examine the influence of lightning pulses with different peak voltages on receiver sensitivity. The test results indicate a notable reduction in the receiver sensitivity when the lightning pulse peak reaches 250 V. The sensitivity trends across various test panels are consistent, and the damage thresholds are similar. These findings confirm the accuracy of the simulation results.

Band Structure Engineering in 2D Metal-Organic Frameworks.

The design of 2D metal-organic frameworks (2D MOFs) takes advantage of the combination of the diverse electronic properties of simple organic ligands with different transition metal (TM) centers. The strong directional nature of the coordinative bonds is the basis for the structural stability and the periodic arrangement of the TM cores in these architectures. Here, direct and clear evidence that 2D MOFs exhibit intriguing energy-dispersive electronic bands with a hybrid character and distinct magnetic properties in the metal cores, resulting from the interactions between the TM electronic levels and the organic ligand π-molecular orbitals, is reported. Importantly, a method to effectively tune both the electronic structure of 2D MOFs and the magnetic properties of the metal cores by exploiting the electronic structure of distinct TMs is presented. Consequently, the ionization potential characteristic of selected TMs, particularly the relative energy position and symmetry of the 3d states, can be used to strategically engineer bands within specific metal-organic frameworks. These findings not only provide a rationale for band structure engineering in 2D MOFs but also offer promising opportunities for advanced material design.

Hydrothermal behaviour of hybrid nanofluid flow in two types of shell and helical coil tube heat exchangers with a new design. Numerical approach

High-efficiency thermal energy systems are very important in meeting the growing demand for thermal energy. As a result, several heat transfer improvements have been proposed. Some promising methods include flow heat transfer in shell and spiral tube exchangers.In a shell-and-coil heat exchanger, utilizing a meticulously designed coil instead of a basic one significantly boosts heat transfer and overall thermal efficiency. This is due to the enhanced fluid dynamics and increased turbulence facilitated by the advanced coil design, making it ideal for space-constrained applications. Moreover, the helical configuration helps minimize fouling and maintenance, and may also provide self-cleaning benefits. Consequently, helical coils are highly regarded in industrial contexts for their superior performance, maintenance ease, and design adaptability.This study conducts a numerical evaluation of the heat transfer and fluid flow properties of two distinct shell-and-coil heat exchangers with specialized designs. The fluids analyzed include water-based hybrid nanofluids, specifically Water/MgO-TiO2and Ag-HEG/water, with results compared to those obtained using pure water. The investigation spans Reynolds numbers from 500 to 2000 and is divided into two segments.The first segment examines the influence of spiral coil geometry and fluid type on the heat exchanger's endothermic performance, utilizing nanoparticle volume concentrations of φ1 = φ2 = 0.3. In the second segment, the optimal geometric and fluid model is chosen based on the findings from the first part. Following this, the impact of various hybrid nanofluids on thermal performance is assessed, comparing fluids with volume concentrations of φ1 = φ2 = 0.3 to pure water (φ1 = φ2 = 0).The findings reveal that Case [A], featuring a unique geometry with Water/Ag_HEG, achieves the highest thermal performance across all examined Reynolds numbers. At the lowest Reynolds number, the thermal efficiency improvements for Case [A], Case [B], and Case [C] were 137 %, 113 %, and 56 %, respectively, compared to the baseline. Additionally, the second part of the study demonstrates that at the lowest Reynolds number, the thermal efficiencies of Water/MgO-TiO2 and Water/Ag_HEG nanohybrid fluids increased by 76 % and 49 %, respectively.

Improvement of Capacitive Accelerometers: Integrating Modeling, Electrode Design, Signal Processing, and Material Selection

This work offers a thorough method for integrating advanced modeling, electrode design, signal processing, and material selection techniques to maximize the performance of capacitive accelerometers. Key performance measures, including noise reduction, sensitivity, and range, can be systematically analyzed and simulated to forecast how design decisions would affect the overall behavior of the sensor. Advanced electrode designs greatly increase capacitance, which results in more precise and trustworthy sensor readings. These designs include optimizing the shape and using high-permittivity materials. Furthermore, to guarantee that the accelerometer’s output precisely represents actual motion even in noisy surroundings, noise reduction strategies including filtering and digital signal processing methods are essential. Additionally, calibration is emphasized as a critical step in preserving measurement accuracy over time and accounting for environmental changes and sensor drift. The choice of material, with an emphasis on thermally stable and high-permittivity materials, is crucial in determining the capacitance, sensitivity, and durability of the sensor. The study offers a paradigm for the creation of capacitive accelerometers that perform better across a variety of applications by striking a balance between these variables.

Revisiting the catalytic activity of single horseradish peroxidase clusters through electrochemical collision technique: Effect of electrolyte and substrate

Horseradish peroxidase (HRP) is a versatile biosensing label and signal reporter owing to its broad-spectrum catalytic ability. In present work, we characterized HRP's catalytic performance with various substrates using electrochemical collision technique and analyzed the associated electron transfer processes. Different electrolyte solutions greatly affected enzyme dispersibility and zeta potential, thereby impacting HRP collision dynamics in single H2O2 substrate system. The maximum turnover number (kcat) for single HRP molecules was calculated to be 3.611 ± 0.149 × 103 s−1 in 0.85 % NaCl and 2.967 ± 0.286 × 103 s−1 in 0.1 M PBS solution, reflecting differences in cluster size induced by the electrolyte conditions. More severe agglomeration of HRP molecules was observed in double-substrate systems, where the hydrophilic mediator (K4Fe(CN)6) and lipophilic mediator (ABTS) served as electron donors and signal reporters. The calculated kcat value of single HRP molecules in ABTS-H2O2 was 7.6 times higher than that in K4Fe(CN)6–H2O2. This difference is attributed to mediators' solubility, lipophilicity, and HRP's affinity for different substrates, with HRP demonstrated stronger affinity for ABTS-H2O2 substrates, which realized more efficient electron transfer and compensated for the low diffusion coefficient of ABTS. This work provides a comprehensive analysis of the effects of electrolytes and substrates on HRP collision and catalytic behavior, offering valuable insights for the advanced design of HRP-based biosensors and diagnostic platforms.

Advanced design of target-driven self-powered sensor assisted by cascade catalytic strategy

In this work, a self-powered microsensor platform based on enzyme biofuel cells (EBFCs) was developed for intelligent monitoring of disease markers miRNA-451. The cascade catalysis system constructed by using the strategy of enzyme-like ZIF-8 nanocapsule incorporation with biological enzymes, which could simultaneously take into account the specificity of biological enzymes and the high activity of nano-enzymes, significantly promoted the electron transfer between glucose and the bio-anode surface, and improved the sensitivity and stability of the sensing system. Meanwhile, the target-triggered hybridisation chain reaction (HCR) amplification strategy to achieve exponential signal amplification based on accurate recognition, and jointly improve the detection sensitivity. As expected, the micro-sensor platform has a wide linear range of 0.5-1.0 fmol/L with a low limit of detection (LOD) of 0.13 fmol/L (S/N=3) and exhibits excellent selectivity, reproducibility and stability in interference assays under optimal detection conditions. The designed self-powered system is simple to construct, easy to transport and the data transmission mode is intelligent and controllable, which is expected to be used in basic biochemical research, clinical diagnosis and environmental monitoring.

Assessing the impacts of air-sealing on the sizing, operation, and economic feasibility of ground-source heat pumps for electrifying single-family houses in the US

According to recent studies and reports, in single-family houses (SFHs), air-sealing can significantly lower the thermal loads for space heating and cooling. Thus, air-sealing in SFHs could reduce the required size and cost of ground source heat pump (GSHP) systems for electrifying SFHs. This study investigated the costs and benefits of integrating air-sealing with GSHPs for retrofitting existing SFHs when compared with air-source heat pumps. A whole building energy simulation tool integrated with an advanced design tool for modeling ground heat exchangers was used to calculate changes in required GSHP capacity, total borehole length, and building energy consumption with and without air-sealing in SFHs in 16 US climatic regions. The results from this study showed that reducing outdoor air infiltration from 0.8 air changes per hour (ACH) to the minimum ventilation requirement (0.35 ACH) can significantly reduce borehole length (up to 55%), GSHP capacity (up to 48%), and total heating electricity reduction, especially in cold climates (up to 44%). The results also showed that for airtight homes (0.03 ACH infiltration) with a direct outdoor air system, the minimum required borehole length, GSHP capacity, and total heating electricity consumption can be reduced up to 70%, 68%, and 67%, respectively, when compared with SFHs with 0.8 ACH infiltration. Moreover, the life cycle cost analysis showed that air-sealing in conjunction with a GSHP is more profitable than replacing the existing system with an air-source heat pump, even without any incentives for most climatic regions in the US (except for some hot regions).