# CAREER: Monolithic 3D Oxide Semiconductor Nanoelectronics for Energy-Efficient Computing

> **NSF 01002627DB NSF RESEARCH & RELATED ACTIVIT** · University of Texas at Dallas (TX) · $501,234

## Abstract

We live in an era of unprecedented data explosion, where autonomous intelligent systems constantly generate and process enormous amounts of data in real-time. For example, today a single autonomous vehicle can generate nearly 40 terabytes of sensor data per hour, which is equivalent to streaming 6,000 Netflix movies simultaneously. Interpreting such massive data with artificial intelligence (AI) requires computing hardware that is both extremely fast and highly energy efficient while providing large storage capability. However, today’s computer chips face fundamental limitations. Most chips are built like a flat city, where different components responsible for computing, storage, and communication sit side by side. This arrangement forces large amounts of data to travel long distances between different parts of a system, consuming significant energy and slowing performance. One promising solution is to build computer chips more like a multi-story building, where different layers of electronics are stacked vertically. This three-dimensional (3D) design can dramatically shorten communication distances, enabling faster operation and lower energy consumption. Achieving this vision requires new types of electronic switches, called transistors, that can be manufactured at low temperatures so they can be safely built on top of existing circuits. This project studies a new class of materials that can enable such vertically stacked chips while maintaining high performance and extremely low energy consumption.

The goal of this CAREER proposal is to advance the science of amorphous oxide semiconductor (AOS) nanoelectronics and enable their use in 3D integrated systems. The research will investigate four fundamental aspects: (1) scaling limits of AOS transistors with stackable non-planar geometry, (2) vertical 3D integration, (3) fundamental understanding of AOS device physics including transport, reliability and thermal, and (4) AI-driven acceleration of AOS technology deve

## Key facts

- **NSF award ID:** 2541681
- **Awardee organization:** University of Texas at Dallas (TX)
- **SAM.gov UEI:** EJCVPNN1WFS5
- **PI:** Sourav Dutta
- **Primary program:** 01002627DB NSF RESEARCH & RELATED ACTIVIT
- **All programs:** Novel devices & vacuum electronics, CAREER-Faculty Erly Career Dev
- **Estimated total:** $501,234
- **Funds obligated:** $501,234
- **Transaction type:** Standard Grant
- **Period:** 05/01/2026 → 04/30/2031

## Primary source

NSF Award Search: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2541681

## Citation

> US National Science Foundation, Award 2541681, CAREER: Monolithic 3D Oxide Semiconductor Nanoelectronics for Energy-Efficient Computing. Retrieved via AI Analytics 2026-07-20 from https://api.ai-analytics.org/grant/nsf/2541681. Licensed CC0.

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