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3-D On-Chip Integration of GaN Power Devices on Power Delivery Network (PDN) With Direct Heat Spreading Layer Bonding for Heterogeneous 3-D (H3D) Stacked Systems
No full textHeterogeneous 3-D (H3D) stacked systems offer numerous advantages for high-performance computing (HPC) and artificial intelligence/machine learning (AI/ML) applications. However, implementing H3D systems requires a re-designed power delivery network (PDN) for efficient power delivery in 3-D stacked systems and thermal management solutions. To develop an efficient PDN for the H3D system, a 3-D integrated on-chip power device is recommended. In this work, we demonstrate an H3D-integrated GaN power device on the PDN of a CMOS chip with direct heat-spreading layer bonding. The GaN power devices were designed to integrate both E-mode and D-mode with L-G of 1.5 mu m and L-GD of 15 mu m, and achieve a R-ON of 22.3 Omega mm and V-BD of 137 V. These results surpass the limitation of silicon-based power devices. In addition, we experimentally demonstrated that direct heat spreading layer bonding effectively relaxed the thermal effect of H3D-integrated GaN power devices using a thermoreflectance microscopy (TRM) system for the first time. By introducing a heat spreading layer, the thermal resistance (R-TH) of the GaN power device was reduced by 48.8% compared to GaN power devices without a heat spreading layer. These findings mark a substantial advancement in PDN technology, setting the stage for vertically integrated active PDNs that support efficient power delivery and effective thermal management in H3D stacked systems.
Necessity, Essence, and Explanation
No full textI shall discuss some of the relations among metaphysical modality, essence, and explanation. Marion Godman, Antonella Mallozzi and David Papineau have recently argued that the essence of a kind consists in its super-explanatory property-a single property that is causally responsible for a multitude of commonalities shared by the instances of the kind. And they argue that this super-explanatory account of essence offers a principled account of aposteriori necessities concerning kinds. I shall examine their arguments and argue that they are fallacious. Along the way, a general problem will also emerge that applies to any account that tries to explicate the notion of essence in terms of an explanatory relation.
The effects of knowledge network characteristics on R&D alliance formation
No full textFirms' knowledge characteristics shape their research and development (R&D alliance activities). When denoting the characteristics, the alliance literature has exclusively focused on firms' internal knowledge characteristics, leaving structural properties of their knowledge relatively unexplored. Therefore, this study aims to investigate how firms' knowledge network characteristics are associated with the propensity to ally. By using 235,024 unique alliance dyads between U.S. semiconductor firms and their potential partners, we examine the effects of two knowledge network characteristics - degree centrality and structural holes - on alliance formation. We further examine the joint effects of the knowledge network characteristics. Our findings reveal the curvilinear relationship between degree centrality and the likelihood of alliance formation. We also find support for the positive joint effects on the likelihood of alliance formation. These findings provide implications for the varying propensity to ally associated with the knowledge network characteristics, i.e. structural positions of a firm's knowledge elements in the sector-level knowledge network.
Free interchange for better transit? Assessing the multi-dimensional impacts on metro to bus interchange behavior - insights from an explainable machine learning method
No full textThis study investigates the impact of a newly implemented public transport interchange discount policy in Suzhou, China, focusing on its effects on metro-to-bus interchange behaviors across various spatial and temporal dimensions. Utilizing two distinct datasets spanning periods before and after the policy's implementation, a comprehensive spatial-temporal analysis was conducted, covering weekdays, weekends, and holidays. A novel, real-time, distance-weighted methodology was developed to more accurately identify metro-to-bus interchange catchments, thereby refining the modeling scope. The study examines the interplay between land use, sociodemographic factors, and bus-related attributes-including a newly proposed operation-opportunity combined bus accessibility metric-using an explainable machine learning approach. Results indicate that the interchange discount policy has had an overall positive, though varied, impact on interchange behaviors, with the most pronounced effects observed during weekdays in central urban areas and at metro line bends. Specifically, 76.1 % of metro stations saw an increase in metro-to-bus interchange ratios on weekdays following the policy's implementation, with increases observed at 66.4 % and 67.3 % of stations during weekends and holidays, respectively. Overall, the interchange ratio increased by 12.49 %, with a 17.45 % increase on weekdays. The analysis also reveals that factors such as bus accessibility, bus-to-bus interchange, and population density exhibit different effects depending on the time of week, with non-linear patterns emerging. The policy's introduction shifted the impact thresholds for certain factors, initially triggering competition between bus and metro services but eventually leading to a synergistic rise in metro-to-bus transfers as bus-to-bus interchange ratios increased. Additionally, the policy altered the significance of population density, enhancing the attractiveness of multimodal interchange for users who previously favored other modes of transport.
Nonlinear shock isolation using the bottleneck phenomenon near a saddle-node ghost
No full textRecent shock-protection technologies have leveraged elastic instability in nonlinear bistable mechanisms. These innovations include a bistable shock isolator (BSI), which uses a zero- frequency singularity to delay and mitigate force transmission. However, a well-escape accompanying the singularity of the BSI has a critical drawback as the well-escape alters the initial conditions, which precludes repetitive applications of the singularity for subsequent shock loading. To address this issue, we propose a transitional shock isolator (TSI; from asymmetric bistability to asymmetric monostability) designed to possess a saddle-node ghost (TSI-snG) remnant after the saddle-node bifurcation. A symmetry-breaking parameter is introduced into the shock isolator model and designed such that the initial conditions for every shock loading are maintained at one fixed point, and the other two fixed points are mutually annihilated. After the annihilation, the TSI-snG ensures that the payload - oscillating mass exposed to shock loading - reliably returns to the original position after every shock loading, which indicates that the limitation of the BSI is resolved. For engineering practicality, we also consider the inevitable fabrication errors by using an imperfection parameter, which is a perturbation of the symmetry-breaking parameter. We demonstrate that TSI-snG with imperfections exhibits a bottleneck near the ghost and exploits the bottleneck to delay and nullify the force-transmission pathway. Therefore, the TSI-snG produces similar benefits from the BSI (delay and mitigation of force transmission), while resolving the drawback of the BSI (well-escape). Parametric studies reveal the dynamics of the TSI model, and experimental verifications corroborate the benefits of the TSI-snG.
Enhanced Hydrate Growth Kinetics with Hydrate Seeds and Promoter under a Static Reaction System
No full textThis work provides fundamental insights into methane hydrate growth kinetics from cyclopentane (CP) hydrate seeds with a surface-active promoter of sodium dodecyl sulfate (SDS) or l-methionine under a static hydrate formation system. The gas consumption rate and the apparent rate constant were determined from the kinetic model during hydrate growth at 275 K and 7 MPa conditions. The quantity of preconstructed hydrate seeds and kinetic promoters was adjusted under a static reaction system. As CP hydrate seeds and SDS have a synergetic effect on promoting heterogeneous nucleation for hydrate growth, the initial apparent rate constant, calculated with initial gas consumption rates, indicating the number of nucleation sites where the hydrate growth occurs, increased with higher seed amounts at 200 and 500 ppm of SDS. However, increasing the seed amount at 1000 ppm of SDS does not improve the initial formation kinetics. l-methionine, one of the hydrophobic amino acids utilized as a kinetic hydrate promoter, did not significantly decrease the interfacial tension between CP and the aqueous phase. With l-methionine, the gas consumption rate did not increase significantly with higher CP amounts because of the limited conversion of CP liquid to hydrate seeds and the small number of nucleation sites. However, the overall methane storage capacity in the l-methionine system increased due to both a lowered initial rate and enhanced water-to-hydrate conversion. These findings provide insights into understanding the fundamental kinetics of hydrate growth and guidelines for optimizing hydrate formation processes to enhance methane storage.
Predicting the physiological effects of multiple drugs using electronic health record
No full textVarious computational models have been developed to understand the physiological effects of drug-drug interactions, which can contribute to more effective drug treatments. However, they mostly focus on interactions of only two drugs, and do not consider the patient information. To address this challenge, we use publicly available electronic health record (EHR), MIMIC-IV, to develop machine learning models that predict the physiological effects of two or more drugs. This study involves extensive preprocessing of laboratory measurement data, prescription data and patient data. The resulting machine learning models predict potential abnormalities across 20 selected measurement items (e.g., concentrations of metabolites and blood cells) in the form of a sentence. Analysis of the model predictions showed that age, specific active pharmaceutical ingredients, and male/female appeared to be the most influential features. The model development process showcased in this study can be extended to other measurement items for a target EHR.
Cross-Correlation Between Crystallinity and Optoelectronic Properties of Mixed-Perovskite Thin Films Through Multiple Time-Resolved Spectroscopy
No full textA power conversion efficiency (PCE) exceeding 25% is achievable using perovskite solar cells (PSCs), with compositional engineering as the most effective strategy for high-efficiency PSCs. However, the understanding of structural properties, charge-carrier dynamics, and photoelectric properties, crucial for solar cell performance, still remains insufficient to establish a correlation with device performance for improving the PCE and stability of PSCs. This study uncovers the crucial links between structural disorder, charge-carrier dynamics, and photoelectric properties of mixed-perovskite (FAPbI3)1-x(MAPbBr3)x thin films by investigating device performance for different mol%. Structural and morphological analyses reveal that the mixed perovskite-thin-film disorder exhibits composition dependence in the form of a checkmark trend, with a minimum near 0.8 mol%. Time-resolved transient absorption spectroscopy demonstrates that charge-carrier dynamics and optoelectronic properties exhibit a corresponding dependence on disorder. As the disorder of the perovskite thin film decreases, the trap density decreases, charge-carrier loss decreases during the thermalization process, and the carrier lifetime is prolonged. Optical pump-THz probe measurements show 20% effective mobility and a diffusion length of 34%. The device performance shows composition dependence and superior PCE is achieved at 0.8 mol%. This study highlights the significance of charge-carrier dynamics in optimizing mixed perovskite composition for enhanced PCE and stability of PSCs. This study comprehensively clarified the crucial correlation between crystalline disorder, charge-carrier dynamics in mixed perovskite, and solar cell performance. Incorporating a trace amount of MAPbBr3 additive effectively mitigates and reduces the structural disorder of FAPbI3, resulting in excellent charge-carrier dynamics and improved photoelectric properties. These enhanced material characteristics contribute to achieving the highest power conversion efficiency in solar cells. image
Shock-induced dispersion patterns of powder with diverse physical properties
No full textUnder the strong pressure pulse induced by a shock wave, powders exhibit specific instability and dispersion patterns that develop into jets over time. We experimentally investigate how the physical properties of particles affect the dispersion of powders in both the compaction and subsequent expansion phases. Our investigation uses a laboratory-scale Hele-Shaw cell device and nano-energetic materials to generate the pressure pulse. Depending on the initial radius of the powder, distinct jetting patterns are initiated by instability in either the inner or outer boundary of the powder. The degree of particle cohesion also influences the instability, and its relationship with the morphology of the finger structure at the inner boundary is quantitatively assessed. The permeability of the powder, which depends on particle size, is another important factor determining the instability of the powder layer during the compaction phase and its inward flow in the expansion phase. Based on the experimental results, a scaling analysis is performed to identify the characteristic time scale of temporal changes in the outer boundary of the powder. The findings presented in this paper offer novel insights for improved predictions of shock-induced particle dispersion in industrial processes.