Heterogeneous Integration Research Articles

A soft multimodal optoelectronic array interface for multiparametric mapping of heart function in vivo.

Multiparametric investigation of cardiac physiology is crucial for the diagnosis and therapy of heart disease. However, no method exists to simultaneously map multiple parameters that govern cardiac (patho)physiology from beating hearts in vivo. Here, we present a cardiac sensing platform that addresses this challenge, functioning with a wireless interface. Advanced fabrication and assembling strategies enable the heterogeneous integration of transparent microelectrodes, light-emitting diodes, photodiodes, and optical filters into a multilayer array structure on soft substrates. The microelectrodes exhibit superior electrochemical performance for measuring electrical potentials and excellent transparency for co-localized fluorescence measurement. The device shows excellent biocompatibility and records the fluorescence of calcium reporter with performance comparable to imaging cameras. Multiparametric in vivo mapping of electrical excitation, calcium dynamics, and their combined effects on cardiac excitation-contraction coupling is demonstrated during normal rhythm, arrhythmia, and treatment. This technology offers potential widespread use in cardiac research to support scientific discoveries and advance clinical life-saving diagnostics and therapies.

High-Q silicon two-dimensional photonic crystal slot nanocavities with asymmetric low-index claddings

Photonic crystal nanocavities with high quality (Q) factors find extensive application in silicon (Si)-integrated photonics owing to their highly selective wavelength filtering, optical buffering, and enhanced nonlinear optical effects in the telecommunication band. High-Q Si photonic nanocavities with asymmetric claddings offer mechanical stability, high functionalities from heterogeneous materials, and vertical integration of optoelectronic devices. However, achieving a high Q factor in an asymmetric structure remains challenging because of the TE–TM coupling loss in the Si slab. To suppress the TE–TM coupling, we designed a high-Q two-dimensional (2D) Si photonic crystal slot cavity by significantly reducing the electric field components in the slab, leveraging a large dielectric discontinuity between Si and the low-index slot. We fabricated 2D Si photonic crystal slot nanocavities with asymmetric claddings consisting of a lower cladding of thermal oxide (nlc = nBOX = 1.45) and an upper cladding of infiltrated spin-on glass (nuc = nSOG = 1.3). The Q factor of this slot cavity is as high as 6.32 × 105, which is the highest Q value ever recorded among nanocavities with asymmetric claddings. Our results are useful for heterogeneous integration of Si photonic crystal nanocavities with various functionalities such as active and nonlinear optical materials, which are unattainable in conventional Si photonics.

Multicolor Emission in Indium-Doped Amorphous Boron Nitride Integrated on Silicon for Self-Biased and High-Speed Photodetection.

Boron nitride (BN), as an emergent wide-bandgap material, is gaining considerable attention as a solid-state deep ultraviolet source and quantum emitter from the ultraviolet to the near-infrared spectral ranges. However, studies of the defect structure of BN and efforts at scalable BN emitters in photonic devices are limited. Controlling the BN doping is of particular interest in view of the light emission of defects. Here, it is demonstrated for the first time that doping amorphous BN (a-BN) with indium (In) shows luminescence spectra tuning from blue to red light, and only 765 nm (1.63 eV) light is dominant when more In content is introduced. The visible light emission is found to be the transition between the defect center of InN (a substitutional In of nitrogen) and ONVB (a substitutional oxygen with an adjacent boron vacancy). While ONVB is identified experimentally in accordance with previous theoretical assumptions, and is optically accessible with a zero-phonon line (ZPL) of about 1.63 eV with increasing In proportion. Moreover, the heterogeneous integration of synthesized In-doped a-BN in silicon platforms is demonstrated by the realization of a 700-1000 nm broadband photodetector. These devices operate self-biased at room temperature and show a high photoresponsivity of ∼1.5 A/W (at 980 nm with -2 V bias), a quick response time of ∼90 μs, and a detectivity of 1.02 × 109 cm·Hz1/2/W. This work fundamentally contributes to establishing infrared detection by doping a-BN materials in heterojunctions with Si, at the forefront of infrared optoelectronics.

Artificial Intelligence in Diagnosis and Management of Nail Disorders: A Narrative Review.

Artificial intelligence (AI) is revolutionizing healthcare by enabling systems to perform tasks traditionally requiring human intelligence. In healthcare, AI encompasses various subfields, including machine learning, deep learning, natural language processing, and expert systems. In the specific domain of onychology, AI presents a promising avenue for diagnosing nail disorders, analyzing intricate patterns, and improving diagnostic accuracy. This review provides a comprehensive overview of the current applications of AI in onychology, focusing on its role in diagnosing onychomycosis, subungual melanoma, nail psoriasis, nail fold capillaroscopy, and nail involvement in systemic diseases. A literature review on AI in nail disorders was conducted via PubMed and Google Scholar, yielding relevant studies. AI algorithms, particularly deep convolutional neural networks (CNNs), have demonstrated high sensitivity and specificity in interpreting nail images, aiding differential diagnosis as well as enhancing the efficiency of diagnostic processes in a busy clinical setting. In studies evaluating onychomycosis, AI has shown the ability to distinguish between normal nails, fungal infections, and other differentials, including nail psoriasis, with a high accuracy. AI systems have proven effective in identifying subungual melanoma. For nail psoriasis, AI has been used to automate the scoring of disease severity, reducing the time and effort required. AI applications in nail fold capillaroscopy have aided the analysis of diagnosis and prognosis of connective tissue diseases. AI applications have also been extended to recognize nail manifestations of systemic diseases, by analyzing changes in nail morphology and coloration. AI also facilitates the management of nail disorders by offering tools for personalized treatment planning, remote care, treatment monitoring, and patient education. Despite these advancements, challenges such as data scarcity, image heterogeneity, interpretability issues, regulatory compliance, and poor workflow integration hinder the seamless adoption of AI in onychology practice. Ongoing research and collaboration between AI developers and nail experts is crucial to realize the full potential of AI in improving patient outcomes in onychology.

Micro‐/Nanohierarchical Surfaces for Enhanced Pool Boiling in Large‐Area Silicon Multichips

With the rising demand for data centers, the need for an efficient thermal management approach becomes increasingly critical. This study examines the enhancement in pool boiling heat transfer on a customized multichip module, designed to mimic artificial intelligence chip layouts for high‐performance computing. Experiments are conducted on smooth surfaces and hierarchical structures integrating micropillars and porous copper, specifically copper inverse opal (CuIO) and copper nanowire (NW). The results demonstrate significant enhancements in critical heat flux (CHF) and heat transfer coefficient (HTC) through these hierarchical structures. Notably, the NW‐CuIO‐integrated hierarchical structure exhibits the highest CHF (234 W cm−2), achieving a 166% enhancement over smooth silicon. The HTC enhancement is more pronounced for the CuIO‐integrated hierarchical structure; this structure achieves an HTC of 70.3 kW m−2 K−1, which represents a 166% improvement. The heater layout, engineered surfaces, and their synergistic effects are analyzed through visualization. The observed boiling inversion phenomena further underscore the importance of sequential activation of nucleation sites in improving boiling performance. This study provides valuable insights into the mechanisms governing the enhancement of boiling heat transfer and offers practical guidance for developing efficient thermal management solutions for data centers.

Visible-spectrum (405–505 nm) low-temperature-deposited deuterated (D) SiNx-SiOy waveguides

Deuterated silicon nitride (SiNx:D)–silicon oxide (SiOy:D) waveguides grown by low-temperature (300 °C) plasma-enhanced chemical vapor deposition (PECVD) operating in the violet (405 nm) to cyan (505 nm) visible spectrum are demonstrated. The waveguides exhibit low insertion losses ranging from 3.2 dB/cm (405 nm) to 0.8 dB/cm (505 nm). The performance of these waveguides is competitive to conventional SiNx waveguides that require significantly higher processing temperatures (≥800 °C). The low-temperature deposition and low loss of these waveguides enable advanced heterogeneous integration schemes for visible-spectrum photonic integrated circuits.

Heterogeneous Packaging Technologies for Chiplet and Memory Integration

To meet the High-Performance Computing (HPC) and Artificial Intelligence (AI) market demands of ever higher performance, lower power consumption, wider memory bandwidth with reduced latency, the interconnects connecting D2D in advanced packages are getting ever smaller with tighter bump pitch. Hybrid Copper Bonding (HCB), which can provide direct Cu-Cu connection, is replacing solder-based micro bump Thermal Compressive Bonding (TCB) for die stacking, when the bump pitch shrinks down to less than 20µm. While the interconnects are getting smaller and denser, the overall package size is getting bigger, because more chiplets and High Bandwidth Memory (HBM) need to be assembled on the same package to meet the high-performance requirements. Innovative memory integration solutions, for example memory to logic die 3D stacking, photonic HBM integration, and remote optical HBM connection, are being developed to tackle the issue alternatively. This paper presents a chiplet based heterogeneous integration platform, an advanced custom HBM option, and a menu of advanced packaging offering, which are recently built and delivered by Samsung. including Integrated Stack Capacitor (ISC), Custom HBM, Re-Distribution Layer (RDL) based Fan Out Wafer Level Packaging (FOWLP), Fan Out Panel level packaging (FOPLP), interposer and Si bridge based 2.5 D package architectures, such as I-CubeS, I-CubeR, and I-CubeE, as well as TCB and HCB based 3D IC packaging.

Process Considerations for Defluxing Ultra-Fine Pitch Die on CoWs

Heterogeneous integration stands as a pivotal strategy in the semiconductor technology realm. As process nodes relentlessly scale down from 16nm to 5nm and beyond, CMOS component speeds soar. This dynamic corresponds to incorporating twice the component count within the same space every 18-24 months. The evolution from CoS (Chip on Substrate) to CoW (Chip on Wafer) marks a significant advancement. CoW integrates chips onto an interposer, applies wafer-level molding, and culminates with a flip chip (FC) substrate connection. This technology offers a superior physical structure to accommodate extensive die and larger interposer dimensions. The technical paper titled ‘Defluxing of Copper Pillar Bumped Flip Chips,’ initially presented at IPC Apex 2022 and subsequently at IMAPS Device Packaging Conference 2023, discussed a comparative study. The study confirmed that the De-ionized water inline cleaning system faces consistent and effective cleaning challenges beneath low standoff components under copper pillar packages featuring 150μm pitch and a 30μm Cu pillar height when compared to low concentration alkaline cleaning agents. This follow-up study is a continuation of the initial effort, focusing on cleaning under next tier of ultra-fine pitch CoW devices with bump pitches under 25μm and bump counts surpassing 150K. The author adhered to the same low-concentration alkaline cleaning agent for testing, exploring the impact of wash temperatures and conveyor belt speed. The assessment employed analytical/functional tests, including Visual Inspection, FTIR with color mapping, and SEM/EDX analysis.

New Innovative Way to Verify Package Connectivity

The heterogeneous integration of multiple ICs in a single package along with high performance/bandwidth memory is critical for many high performance computing applications. Such designs result in complex connectivity with many hundreds of thousands of connections after everything has been heterogeneously integrated and packaged. Such designs make it extremely challenging to verify the correctness of the connections. The traditional way to verify the connections requires a lot of manpower and time and is either not exhaustive or too late in the process as its typically done after implementation is complete. This paper will introduce a new way to functionally verify the packaging connectivity using formal verification that can exhaustively verify all interconnections between the IC blocks. The flow is automatic for all steps from creating connectivity spec to verify packaging output connectivity. The automatic parallel algorithms on compute grid can verify huge numbers of connections in minutes even seconds. The script for the flow is simple and only takes a few minutes to setup. Once the script is ready, it can be reused for different packaging projects.

Achieving Large-Scale HBM Integration with Adaptive Pad Stacks on Molded Embedded Bridge Die Interposers

Chiplets and heterogeneous integration are now common vernacular in the semiconductor industry. One of the more pressing issues facing device designers and system architects in this new reality is the insatiable appetite for high-bandwidth memory tightly integrated with GPU, CPU and other chiplet processing devices. This ever-increasing drive for higher levels of integration is resulting in module sizes that now exceed the bounds of the industry’s current de-facto standard silicon interposer solutions. With module dimensions exceeding 50 mm on a side, the industry is transitioning to organic substrates or molded fan-out interposers with embedded bridge die. These embedded bridge technologies provide a practical roadmap for significant module size growth to 100mm per side and beyond. As module sizes continue to grow, the number of embedded bridge die similarly increase. An emerging device currently in design now exceeds 20 bridge die. During assembly of the molded interposer, manufacturing tolerances to achieve the true positions required for all the bridge die become incredibly challenging to achieve in a cost-effective high-volume process. Within this paper, an innovative solution, Adaptive Pad Stacks, will be presented which increases process tolerances by up to 10X versus the conventional approach. For example, the ± 1.5 µm true position required for 35 µm pitch bridge die interfaces can be achieved with a die attach specification allowing up to ± 25 µm. Adaptive Pad Stacks utilize Adaptive Patterning® and mask-less laser direct imaging photolithography to not only deliver high yield on large scale interposers, but also remove the historical challenge with reticle stitching.

Improved Yield Estimation for Heterogeneously Integrated Components

We show the use of a parallelized daisy “field” design for continuity and reliability testing for 2.5D integrated microelectronics. The use of daisy chains for continuity testing of flip-chip integrated microelectronics packaging is well-established, and statistical models are used to estimate the yield and reliability of the interconnects. However, single points of failure make up the basis for these statistical models. This can be a challenge for unknown yield distributions, as longer daisy chain structures provide an accurate probe for high-yielding processes but are of limited use for process development when the yield is lower. More, shorter-length chains are useful in troubleshooting lower-yield situations, at the expense of decreased statistical relevance and increased complexity of data collection due to the necessity of testing a large number of daisy chains. Additionally, information is lost due to a single failure in a daisy chain creating an open circuit that prevents any further failures in a daisy chain from being identified. The new 2D Daisy Field (2DDF) allows for continuous monitoring of emerging failures across a large grid of microbumps for thermocompression flip-chip bonding applications for a wide range of yield/failure rate distributions. The concept is based on failures causing DC resistance changes across a large population of connections, which do not need to be tested individually. The reduced testing complexity allows for continuous monitoring of the entire interconnect population through the resistance across a single pair of connections. Assuming that, at any given time, failures are occurring at single interconnect points (as is frequently the case for fatigue, stress voiding, electromigration-type failures) allows for the determination of the population failure rate in situ. We will present a procedure for eliminating degenerate failure distribution solutions for the resistance from physical principles to determine the unique failure distribution. The technique allows for continuous monitoring of the failure rate, providing yield as a function of an applied parameter: such as temperature, shear, or voltage. Clustering of failures with respect to these parameters provides insight into the onset and mechanisms of failure. Thus, the clear identification of process limits – thermal budgets, mechanical robustness, operating voltages, and so on – for optimizing fabrication can be performed with only a single experiment through the full range of values, rather than a time-consuming guess-and-check process for a number of discrete process parameters until the approximate yield is found. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA-0003525. SAND2023-11665A This research was developed with funding from the Defense Advanced Research Projects Agency (DARPA). The views, opinions and/or findings expressed are those of the author and should not be interpreted as representing the official views or policies of the Department of Defense or the U.S. Government. Distribution Statement ““A”” (Approved for Public Release, Distribution Unlimited). If you have any questions, please contact the Public Release Center.

Analysis of errors in junction temperature estimated by temperature-sensitive electrical parameter for parallel-connected SBDs

Abstract Multi-chip topology is widely adopted for large rated current power modules. Thermal management of multi-chip power modules has a significant impact on their long-term reliability. The transient thermal network model used for thermal management relies on the time response of junction temperature, which is estimated using temperature-sensitive electrical parameters (TSEPs) derived from the temperature dependency of I-V characteristics in power devices. However, the parallel connection of power devices complicates the junction temperature estimation because the sensing current is shared unevenly due to differences in the I-V characteristics of individual devices and the temperature gradient within the power module package. Consequently, the temperature estimated using a unified TSEP does not accurately represent the temperature difference among parallel-connected power devices. This paper investigates an error in the junction temperature estimated by using unified static TSEP for parallel-connected silicon carbide (SiC) Schottky barrier diodes (SBDs) as the power device. The results reveal that the unified TSEP underestimates the maximum temperature in multi-chip power modules. However, the semi-physical model of power devices enables us to estimate the junction temperature of each SiC SBD when we measure shared currents for each device.

Applications, Design Methods, and Challenges for Additive Manufacturing of Thermal Solutions for Heterogeneous Integration of Electronics

Abstract Heterogeneous integration of electronics is critical to the next wave of electronics applications ranging from extremely power dense energy conversion systems to advanced chiplet and co-packaged optics architectures for next-generation computing. Enhanced functionality and operation are essential goals in heterogeneous integration. In all applications, effective thermal management of both active and passive electronic devices is required to support these goals. Additive manufacturing opens new avenues for heterogeneous integration of electronics. This article thus provides a review of additive manufacturing methods and applications in the specific context of thermal solutions for heterogeneous integration of electronics. Three-dimensional printing methods, associated materials (e.g., metal, polymer, ceramic, and composite), and electronics package integration approaches, or conceptual fabrication workflows, are outlined for cold plates, heat sinks, fluid flow manifolds, and thermal interface materials plus composites for electronics. The current status of design optimization methods for additive manufacturing of thermal solutions for electronics is also covered. Future challenges and research directions are outlined to further stimulate the development of advanced manufacturing methods, novel design techniques, and unique electronics package integration capabilities for thermal solutions.

Liquid-infused nanostructured composite as a high-performance thermal interface material for effective cooling

Effective heat dissipation remains a grand challenge for energy-dense devices and systems. As heterogeneous integration becomes increasingly inevitable in electronics, thermal resistance at interfaces has emerged as a critical bottleneck for thermal management. However, existing thermal interface solutions are constrained by either high thermal resistance or poor reliability. We report a strategy to create printable, high-performance liquid-infused nanostructured composites, comprising a mechanically soft and thermally conductive double-sided Cu nanowire array scaffold infused with a customized thermal-bridge liquid that suppresses contact thermal resistance. The liquid infusion concept is versatile for a broad range of thermal interface applications. Remarkably, the liquid metal infused nanostructured composite exhibits an ultra-low thermal resistance <1 mm² K W-1 at interface, outperforming state-of-the-art thermal interface materials on chip-cooling. The high reliability of the nanostructured composites enables undegraded performance through extreme temperature cycling. We envision liquid-infused nanostructured composites as a universal thermal interface solution for cooling applications in data centers, GPU/CPU systems, solid-state lasers, and LEDs.

Enormous Out-of-Plane Charge Rectification and Conductance through Two-Dimensional Monolayers.

Heterogeneous integration of emerging two-dimensional (2D) materials with mature three-dimensional (3D) silicon-based semiconductor technology presents a promising approach for the future development of energy-efficient, function-rich nanoelectronic devices. In this study, we designed a mixed-dimensional junction structure in which a 2D monolayer (e.g., graphene, MoS2, and h-BN) is sandwiched between a metal (e.g., Ti, Au, and Pd) and a 3D semiconductor (e.g., p-Si) to investigate charge transport properties exclusively in an out-of-plane (OoP) direction. The role of 2D monolayers as either an OoP metal-to-semiconductor charge injection barrier or an OoP semiconductor-to-metal charge collection barrier was comparatively evaluated. Compared to monolayer graphene, monolayer MoS2 and h-BN effectively modulate OoP metal-to-semiconductor charge injection through a barrier tunneling effect. Their effective OoP resistance and resistivity were extracted using a resistors-in-series model. Intriguingly, when functioning as a semiconductor-to-metal charge collection barrier, all 2D monolayers become electronically "transparent" (close to zero resistance) when a high OoP voltage (greater than the built-in voltage) is applied. As a mixed-dimensional integrated diode, the Ti/MoS2/p-Si and Au/MoS2/p-Si configurations exhibit both high OoP rectification ratios (5.4 × 104) and conductance (1.3 × 105 S/m2). Our work demonstrates the tunable OoP charge transport characteristics at a 2D/3D interface, suggesting the opportunity for 2D/3D heterogeneous integration, even with sub-1 nm thick 2D monolayers, to enhance modern Si-based electronic devices.

Materials-Technology Co-Optimization (MTCO) for Inter-Die-Gap-Fill (IDGF) in Heterogeneous Integration of Chiplets

Materials-Technology Co-Optimization (MTCO) is used to engineer Plasma-Enhanced Chemical Vapor Deposition (PECVD) of dielectric material properties for the Inter-Die-Gap-Fill (IDGF) between bonded chiplets in 2D and 3D heterogeneous integration. Mechanical properties of the dielectric IDGF are accurately tuned to eliminate cracking due to external forces in the next planarization processes. Thermal properties of the dielectric IDGF are tuned to effectively reduce thermal stress and eliminate cracking through downstream anneal and deposition processes. We demonstrate a working process flow to evaluate mechanical and thermal cracking stability of the IDGF material for heterogenous integration development.

3.5D Packaging for Heterogeneous Integration

Exponential growth in the number of parameters used to train machine learning (ML) models for artificial intelligence (AI) training &amp; inference applications consequently requires extensive compute resources like CPUs, GPUs, and memory, all working in tandem at high bandwidth. Heterogeneous integration via chiplet architectures is also key to enabling economically feasible growth of power efficient computing, given the slowdown in Moore’s law. In this paper, we summarized the key advanced packaging technologies that directly enabled the heterogenous integration of multiple chiplets like CPUs, GPUs, active interposers, high bandwidth memory (HBMs) die and passive components in the largest, most complex, and high power (550 W+) AMD Instinct™ MI300 accelerator package built by AMD. Three key technologies are described: direct Cu-Cu hybrid bonding, 2.5D integration on large silicon interposer, and metal TIM-based cooling solution used in MI300. Package level reliability results are also presented.

Reliable Direct Bonded Heterogeneous Integration (DBHi) for AI Hardware

AI applications are becoming pervasive, they require computational performance to grow at an annual rate of 2.5x or a decadal rate of 1000x. The front runners to keep up this trend are System on Chip (SoC) and system in package (SiP)/Heterogenous Integration (HI). While SoC has advantages in functional performance, it is more expensive to design, fabricate and package. As we increase the functionality, the cost increases and so is the package size. HI offers the possibility to integrate a variety of computing elements intoa smaller space, controlling package size with a relatively less expensive design and fabrication. Integrating and tiling chiplets from differnts silicon technology nodes reqiuire high bandwidth interconnects to achieve this seemlessly. . To address this need, several solutions have emerged in the past years such as silicon interposer [1], high-density laminate [2], silicon bridge [3-4] chip-stacked packages and Fan-out packaging. Out of these options, Si bridge offers one of the fastest lateral communications between chips. In the test configuration proposed, Si bridge connects two chips, and these two chips are connected to the laminate as shown in Fig 1. There are different approaches to make this architecture. The first approach has a laminate with an embedded chip and 2 principal chips are bonded over the laminate (and bridge) at the same time. In another approach which is called DBHI, first a subassembly is made by bonding all the 3 chips (a Si bridge with 2 principal Si chips) and subsequently bonding this chip assembly to a laminate. In the latter approach the laminate comprises a cavity where the Si bridge will be loged at chip assembly whereas in the former approach a special laminate with embedded Si bridge is required. In last few years we have presented our work on DBHI with a thick bridge in cavity. In this current work we present simpler DBHI architecture which doesn’t need a cavity in the laminate. In this novel configuration which is presented in Fig 2 , a thinner Si bridge chip (60 µm thick) is used as opposed to thicker bridge (200 µm), while the principal chips are fitted with higher Copper pillar instead of solder C4’s. The Copper pillars create a standoff between principal chips and laminate. This clears sufficient height for the bridge chip to the surface of the laminate after the chip joining operation. DBHI now offers the possibility of assembling Si bridge to principal chips at very fine pitch interconnects (30-75 µm) with the help of uC4s on regular laminate configurations. To validate process yield, JEDEC standard thermal cycling Deep thermal cycling DTC (-40C to +125C) and ATC (0C to 100C) are performed. All stress cells saw JEDEC preconditioning before starting the actual stress. The results indicate that the novel DBHI configuration comfortably passes JEDEC criteria. Extended thermal cycling up to 2000 DTC is also performed to properly assess the thermomechanical properties of these laminates. Physical analysis for the post-reliability test samples for the uC4s and C4s are also discussed in this study. In this work, we present the effects and the advantages that came with thinning down the Si bridge and the removal of cavity for the bonding and their influence on the overall thermo-mechanical performance of the package. This configuration provides flexibility for signal routing in the laminate below the bridge and eliminates any additional processing of the laminate. DBHI is therefore further enhanced and well positioned to provide high-bandwidth and low-power communication required for AI workloads.

Die-First FOPLP Lithography Challenges Due To Die Shifting And A Solution Using Feedforward Adaptive Shot Technology

Artificial intelligence (AI) is beginning to have a broad effect on people’s lives. AI can be applied in a variety of ways to a variety of fields, including medicine, sales, finance and more. Market leaders like Intel, AMD, IBM, Microsoft, Meta and Google are using AI in various ways that may ultimately change the future of humankind. AI requires powerful, high-specification chips to speed up the time it takes to train AI models and reduce power consumption. To create AI packages, manufacturers use heterogeneous integration (HI) techniques. Fan-out panel-level packaging (FOPLP), which costs less than other packaging processes, is often employed. Although FOPLP has many advantages, it faces significant process challenges, such as die placement errors and substrate warpage. One of the key challenges is the trade-off between overlay, yield and throughput during the lithography processing steps. A user exposes multiple dies per exposure shot to increase throughput, but this can result in lower overlay yield because of so-called pick-and-place die placement errors. To overcome issues involving low yields, each die needs to be aligned. Doing this impacts throughput, so a compromise is needed. Finding a balancing between throughput and overlay is one of the biggest challenges of FOPLP. In this paper we will address the tradeoff between lithography throughput and overlay yield by demonstrating an integrated feedforward adaptive shot solution. This feedforward approach uses a third-party metrology system to measure reconstituted panel die location data and sends the data to the stepper via a network. With feedforward technology, the stepper uses smart adaptive shot technology to generate an optimized variable shot size layout. This layout ensures overlay yield is within specification and uses the minimum number of exposure steps. With feedforward adaptive shot technology, the user can maximize the throughput of the stepper and ensure proper overlay yield at the same time.

Hierarchy Reproduction: Multiphasic Strategies for Tendon/Ligament-Bone Junction Repair.

Tendon/ligament-bone junctions (T/LBJs) are susceptible to damage during exercise, resulting in anterior cruciate ligament rupture or rotator cuff tear; however, their intricate hierarchical structure hinders self-regeneration. Multiphasic strategies have been explored to fuel heterogeneous tissue regeneration and integration. This review summarizes current multiphasic approaches for rejuvenating functional gradients in T/LBJ healing. Synthetic, natural, and organism-derived materials are available for invivo validation. Both discrete and gradient layouts serve as sources of inspiration for organizing specific cues, based on the theories of biomaterial topology, biochemistry, mechanobiology, and insitu delivery therapy, which form interconnected network within the design. Novel engineering can be constructed by electrospinning, 3-dimensional printing, bioprinting, textiling, and other techniques. Despite these efforts being limited at present stage, multiphasic scaffolds show great potential for precise reproduction of native T/LBJs and offer promising solutions for clinical dilemmas.