Measuring temperature with neutrons

Researchers from Osaka University, National Institutes for Quantum Science and Technology, Hokkaido University, Japan Atomic Energy Agency, and Tokamak Energy developed a way to rapidly measure the temperature of electronic components inside a device using neutrons.

The technique, called ‘neutron resonance absorption’ (NRA), examines neutrons being absorbed by atomic nuclei at certain energy levels to determine the properties of the material. After being generated using high-intensity laser beans, the neutrons were then decelerated to a very low energy level before being passed through the sample, in this case plates of tantalum and silver. The temporal signal of the NRA was altered in a predictable manner when the sample material’s temperature was changed.

“This technology makes it possible to instantaneously and accurately measure temperature,” said Zechen Lan of Osaka University, in a statement. “As our method is non-destructive, it can be used to monitor devices like batteries and semiconductor devices.”

The technique can acquire temperature data in a window of 100 nanoseconds, and the measurement device itself is about a tenth of the size of similar equipment.

“Using lasers to generate and accelerate ions and neutrons is nothing new, but the techniques we’ve developed in this study represent an exciting advance,” added Akifumi Yogo of Osaka University, in a statement. “We expect that the high temporal resolution will allow electronics to be examined in greater detail, help us to understand normal operating conditions, and pinpoint abnormalities.” [1]

Mapping heat transfer

Researchers from the University of Rochester applied optical super-resolution fluorescence microscopy techniques used in biological imaging to map heat transfer in electronic devices using luminescent nanoparticles.

By applying highly doped upconverting nanoparticles to the surface of a device, the researchers were able to achieve super-high resolution thermometry at the nanoscale level from up to 10 millimeters away.

Rochester researchers demonstrated their super-high resolution thermometry techniques on an electrical heater structure that the team designed to produce sharp temperature gradients. (Credit: University of Rochester / J. Adam Fenster)

“The building blocks of our modern electronics are transistors with nanoscale features, so to understand which parts of overheating, the first step is to get a detailed temperature map,” said Andrea Pickel, an assistant professor from the University of Rochester’s Department of Mechanical Engineering, in a release. “But you need something with nanoscale resolution to do that.”

The researchers demonstrated the technique using an electrical heater structure designed to produce sharp temperature gradients. To improve the process, the team hopes to lower the laser power used and refine the methods for applying layers of nanoparticles to the devices. [2]

ML for predicting thermal properties

Researchers from MIT, Argonne National Laboratory, Harvard University, the University of South Carolina, Emory University, the University of California at Santa Barbara, and Oak Ridge National Laboratory propose a new machine learning framework that provides much faster prediction of phonon dispersion relations, an important measurement for determining the thermal properties of a material and how heat moves through semiconductors and insulators.

Heat-carrying phonons have an extremely wide frequency range, and the particles interact and travel at different speeds. “Phonons are the culprit for the thermal loss, yet obtaining their properties is notoriously challenging, either computationally or experimentally,” said Mingda Li, associate professor of nuclear science and engineering at MIT, in a release.

The researchers started with a graph neural network (GNN) that converts a material’s atomic structure into a crystal graph comprising multiple nodes, which represent atoms, connected by edges, which represent the interatomic bonding between atoms.

To make it suitable for predicting phonon dispersion relations, they created a virtual node graph neural network (VGNN) by adding a series of flexible virtual nodes to the fixed crystal structure to represent phonons. This enabled the VGNN to skip many complex calculations when estimating phonon dispersion relations, making it a more efficient method than a standard GNN.

Li noted that a VGNN could be used to calculate phonon dispersion relations for a few thousand materials in a few seconds with a personal computer. The technique could also be used to predict challenging optical and magnetic properties. [3]

References

[1] Lan, Z., Arikawa, Y., Mirfayzi, S.R. et al. Single-shot laser-driven neutron resonance spectroscopy for temperature profiling. Nat Commun 15, 5365 (2024). https://doi.org/10.1038/s41467-024-49142-y

[2] Ziyang Ye et al., Optical super-resolution nanothermometry via stimulated emission depletion imaging of upconverting nanoparticles. Sci. Adv. 10, eado6268 (2024) https://doi.org/10.1126/sciadv.ado6268

[3] Okabe, R., Chotrattanapituk, A., Boonkird, A. et al. Virtual node graph neural network for full phonon prediction. Nat Comput Sci 4, 522–531 (2024). https://doi.org/10.1038/s43588-024-00661-0

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In the relentless pursuit of performance and miniaturization, the semiconductor industry has increasingly turned to 3D integrated circuits (3D-ICs) as a cutting-edge solution. Stacking dies in a 3D assembly offers numerous benefits, including enhanced performance, reduced power consumption, and more efficient use of space. However, this advanced technology also introduces significant thermal dissipation challenges that can impact the electrical behavior, reliability, performance, and lifespan of the chips (figure 1). For automotive applications, where safety and reliability are paramount, managing these thermal effects is of utmost importance.

Fig. 1: Illustration of a 3D-IC with heat dissipation.

3D-ICs have become particularly attractive for safety-critical devices like automotive sensors. Advanced driver-assistance systems (ADAS) and autonomous vehicles (AVs) rely on these compact, high-performance chips to process vast amounts of sensor data in real time. Effective thermal management in these devices is a top priority to ensure that they function reliably under various operating conditions.

The thermal challenges of 3D-ICs in automotive applications

The stacked configuration of 3D-ICs inherently leads to complex thermal dynamics. In traditional 2D designs, heat dissipation occurs across a single plane, making it relatively straightforward to manage. However, in 3D-ICs, multiple active layers generate heat, creating significant thermal gradients and hotspots. These thermal issues can adversely affect device performance and reliability, which is particularly critical in automotive applications where components must operate reliably under extreme temperatures and harsh conditions.

These thermal effects in automotive 3D-ICs can impact the electrical behavior of the circuits, causing timing errors, increased leakage currents, and potential device failure. Therefore, accurate and comprehensive thermal analysis throughout the design flow is essential to ensure the reliability and performance of automotive ICs.

The importance of early and continuous thermal analysis

Traditionally, thermal analysis has been performed at the package and system levels, often as a separate process from IC design. However, with the advent of 3D-ICs, this approach is no longer sufficient.

To address the thermal challenges of 3D-ICs for automotive applications, it is crucial to incorporate die-level thermal analysis early in the design process and continue it throughout the design flow (figure 2). Early-stage thermal analysis can help identify potential hotspots and thermal bottlenecks before they become critical issues, enabling designers to make informed decisions about chiplet placement, power distribution, and cooling strategies. These early decisions reduce the risks of thermal-induced failures, improving the reliability of 3D automotive ICs.

Fig. 2: Die-level detailed thermal analysis using accurate package and boundary conditions should be fully integrated into the ASIC design flow to allow for fast thermal exploration.

Early package design, floorplanning and thermal feasibility analysis

During the initial package design and floorplanning stage, designers can use high-level power estimates and simplified models to perform thermal feasibility studies. These early analyses help identify configurations that are likely to cause thermal problems, allowing designers to rule out problematic designs before investing significant time and resources in detailed implementation.

Fig. 3: Thermal analysis as part of the package design, floorplanning and implementation flows.

For example, thermal analysis can reveal issues such as overlapping heat sources in stacked dies or insufficient cooling paths. By identifying these problems early, designers can explore alternative floorplans and adjust power distribution to mitigate thermal risks. This proactive approach reduces the likelihood of encountering critical thermal issues late in the design process, thereby shortening the overall design cycle.

Iterative thermal analysis throughout design refinement

As the design progresses and more detailed information becomes available, thermal analysis should be performed iteratively to refine the thermal model and verify that the design remains within acceptable thermal limits. At each stage of design refinement, additional details such as power maps, layout geometries and their material properties can be incorporated into the thermal model to improve accuracy.

This iterative approach lets designers continuously monitor and address thermal issues, ensuring that the design evolves in a thermally aware manner. By integrating thermal analysis with other design verification tasks, such as timing and power analysis, designers can achieve a holistic view of the design’s performance and reliability.

A robust thermal analysis tool should support various stages of the design process, providing value from initial concept to final signoff:

1. Early design planning: At the conceptual stage, designers can apply high-level power estimates to explore the thermal impact of different design options. This includes decisions related to 3D partitioning, die assembly, block and TSV floorplan, interface layer design, and package selection. By identifying potential thermal issues early, designers can make informed decisions that avoid costly redesigns later.
2. Detailed design and implementation: As designs become more detailed, thermal analysis should be used to verify that the design stays within its thermal budget. This involves analyzing the maturing package and die layout representations to account for their impact on thermally sensitive electrical circuits. Fine-grained power maps are crucial at this stage to capture hotspot effects accurately.
3. Design signoff: Before finalizing the design, it is essential to perform comprehensive thermal verification. This ensures that the design meets all thermal constraints and reliability requirements. Automated constraints checking and detailed reporting can expedite this process, providing designers with clear insights into any remaining thermal issues.
4. Connection to package-system analysis: Models from IC-level thermal analysis can be used in thermal analysis of the package and system. The integration lets designers build a streamlined flow through the entire development process of a 3D electronic product.

Tools and techniques for accurate thermal analysis

To effectively manage thermal challenges in automotive ICs, designers need advanced tools and techniques that can provide accurate and fast thermal analysis throughout the design flow. Modern thermal analysis tools are equipped with capabilities to handle the complexity of 3D-IC designs, from early feasibility studies to final signoff.

High-fidelity thermal models

Accurate thermal analysis requires high-fidelity thermal models that capture the intricate details of the 3D-IC assembly. These models should account for non-uniform material properties, fine-grained power distributions, and the thermal impact of through-silicon vias (TSVs) and other 3D features. Advanced tools can generate detailed thermal models based on the actual design geometries, providing a realistic representation of heat flow and temperature distribution.

For instance, tools like Calibre 3DThermal embeds an optimized custom 3D solver from Simcenter Flotherm to perform precise thermal analysis down to the nanometer scale. By leveraging detailed layer information and accurate boundary conditions, these tools can produce reliable thermal models that reflect the true thermal behavior of the design.

Automation and results viewing

Automation is a key feature of modern thermal analysis tools, enabling designers to perform complex analyses without requiring deep expertise in thermal engineering. An effective thermal analysis tool must offer advanced automation to facilitate use by non-experts. Key automation features include:

1. Optimized gridding: Automatically applying finer grids in critical areas of the model to ensure high resolution where needed, while using coarser grids elsewhere for efficiency.
2. Time step automation: In transient analysis, smaller time steps can be automatically generated during power transitions to capture key impacts accurately.
3. Equivalent thermal properties: Automatically reducing model complexity while maintaining accuracy by applying different bin sizes for critical (hotspot) vs non-critical regions when generating equivalent thermal properties.
4. Power map compression: Using adaptive bin sizes to compress very large power maps to improve tool performance.

5. Automated reporting: Generating summary reports that highlight key results for easy review and decision-making (figure 4).

Fig. 4: Ways to view thermal analysis results.

Automated thermal analysis tools can also integrate seamlessly with other design verification and implementation tools, providing a unified environment for managing thermal, electrical, and mechanical constraints. This integration ensures that thermal considerations are consistently addressed throughout the design flow, from initial feasibility analysis to final tape-out and even connecting with package-level analysis tools.

Real-world application

The practical benefits of integrated thermal analysis solutions are evident in real-world applications. For instance, a leading research organization, CEA, utilized an advanced thermal analysis tool from Siemens EDA to study the thermal performance of their 3DNoC demonstrator. The high-fidelity thermal model they developed showed a worst-case difference of just 3.75% and an average difference within 2% between simulation and measured data, demonstrating the accuracy and reliability of the tool (figure 5).

Fig. 5: Correlation of simulation versus measured results.

The path forward for automotive 3D-IC thermal management

As the automotive industry continues to embrace advanced technologies, the importance of accurate thermal analysis throughout the design flow of 3D-ICs cannot be overstated. By incorporating thermal analysis early in the design process and iteratively refining thermal models, designers can mitigate thermal risks, reduce design time, and enhance chip reliability.

Advanced thermal analysis tools that integrate seamlessly with the broader design environment are essential for achieving these goals. These tools enable designers to perform high-fidelity thermal analysis, automate complex tasks, and ensure that thermal considerations are addressed consistently from package design, through implementation to signoff.

By embracing these practices, designers can unlock the full potential of 3D-IC technology, delivering innovative, high-performance devices that meet the demands of today’s increasingly complex automotive applications.

For more information about die-level 3D-IC thermal analysis, read Conquer 3DIC thermal impacts with Calibre 3DThermal.

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