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Artificial Intelligence
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Biotechnology and Synthetic Biology
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Cryptography and Computer Security
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Energy Technologies
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Neuroscience
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Quantum Technologies
Quantum Technologies
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Robotics
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semiconductors
Semiconductors
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Space

KEY TAKEAWAYS

•  Materials science is a foundational technology that underlies advances in many other fields, including robotics, space, energy, and synthetic biology.

•  The field will exploit artificial intelligence as another promising tool to predict new materials with new properties and to identify novel uses for known materials.

•  Future progress in materials science requires new funding mechanisms and access to additional computational power to more effectively transition from innovation to implementation.

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Overview

From semiconductors in computer chips to plastics in everyday objects, materials are everywhere. Knowing how to synthesize and process them, as well as understanding their structure and properties, has helped shape the world around us. Materials science contributes to the development of stronger, lighter materials that improve devices as varied as battery electrodes, medical implants, automobiles, and spacecraft.

Broadly speaking, materials science and engineering research focuses on four major activities: (1) studying the structure of materials to understand how they are composed and organized from atomic to macroscopic scales, (2) verifying the properties of materials, such as their conductivity, strength, and elasticity, (3) analyzing and benchmarking how materials perform in specific situations, and (4) assessing how materials can be fabricated and manufactured.

 

KEY DEVELOPMENTS

  • Flexible electronics involves the creation of electrical devices that can bend, stretch, and deform without compromising their performance. Such electronics can be used as wearable, skin-like devices. For instance, a “smart bandage” with integrated sensors to monitor wound conditions and provide electrical stimulation can reduce the time needed to heal chronic wounds by 25 percent. 
  • Additive manufacturing, or 3-D printing, is one of the most promising advances in materials processing over the past fifteen years. The technology comes in different forms. For instance, a method known as continuous liquid interface production uses directed ultraviolet light to form structures from a polymer resin. 
  • Nanotechnology studies how properties of nanoscale materials—including their electronic, optical, magnetic, thermal, and mechanical properties— differ from the same materials in bulk form. 
  • Batteries can be improved through better materials that are safer, longerlasting, and more cost-effective than current materials. Obstacles to progress remain in achieving higher energy storage levels and faster charging speeds— as well as reducing manufacturing costs—while ensuring safety and reliability.
  • Electrocatalysis uses catalysts to speed up electrochemical reactions critical for water splitting, fuel cells, and carbon dioxide (CO₂) recycling. Nanomaterials are ideal electrocatalysts because of their large surface area per unit mass. Water splitting, which separates water into oxygen and hydrogen, enables hydrogen energy storage, while CO₂ electrocatalysis converts CO₂ into valuable fuels and chemicals. 
  • Electrochemistry examines relationships between electrical energy and chemical reactions. Electrochemical devices can generate electrical energy through a spontaneous chemical reaction (such as that which occurs in a battery) or use electrical energy to drive a chemical reaction (e.g., electrocatalysis to produce hydrogen). One electrochemistry application is the detection of biological molecules through electrical signals generated by a reaction between a biological component, such as an enzyme or antibody, and the molecule being detected. Highly sensitive, portable, and inexpensive, such sensors are ideal for medical diagnostics, environmental monitoring, and pathogen detection. 
  • Machine learning (ML) can address a fundamental challenge of materials science as a discipline: reviewing the vast number of materials and possible material combinations, as well as reducing the time and cost involved in their synthesis and characterization—which are the general processes through which materials’ structure and properties are ascertained through spectroscopic, microscopic, and other methods. 

    ML can leverage experimental and computational data on the properties of materials to identify patterns in existing data and make generalized predictions about new materials. ML results provide a time-saving starting point for further exploration, although laboratory work is still needed to validate ML informed solutions. Another application of the approach involves examining scientific literature to uncover hidden relationships that could reveal latent knowledge about materials and point to new research directions.

 

Over the Horizon

Enhancing the Human Body Through Materials Science Advances in materials science are transforming human body repair and enhancement. High-performance materials like carbon fiber and shape memory alloys enable natural prosthetic movements. Biocompatible polymers support soft bioelectronic interfaces for neuroprosthetics, restoring motor and sensory functions via nervous system connections. Brain–machine interfaces use flexible electrodes with graphene and nanowires to decode neural signals, aiding communication and robotic control of prostheses. Deep-brain devices modulate neural activity for conditions like Parkinson’s, expanding human physical and cognitive capabilities.

Metamaterials Metamaterials are artificially engineered materials with structures smaller than light or sound wavelengths, enabling unique control over electromagnetic or acoustic waves. They enable applications like invisibility cloaks, superlenses, advanced antennas, seismic protection, and sound insulation. Advances in fabrication have made them commercially viable, with future uses expected in telecommunications, biomedicine, and energy, including 6G antennas, wireless power for implants, and hardware for quantum computing.

POLICY ISSUES

Research Infrastructure 

Today’s materials research infrastructure does not adequately support the transition from research to real-word applications at scale. Such transitions generally require construction of a small-scale pilot project to demonstrate the feasibility of potential large-scale manufacturing. However, at this stage, the work is too mature to qualify for funding as basic research but not mature enough to be commercialized by actual companies. New funding vehicles are needed to bridge this gap between bench-scale research and company-level investment. 

Regulation and Environmental Issues 

As with other areas of technology, materials science faces concerns about balancing the need to ensure public safety with the imperative to innovate quickly. Nanoparticles raise particular concern because their small size may enable them to pass through various biological borders, such as cell membranes. Multiple US government agencies currently oversee the regulation of and infrastructure for nanomaterials research. 

The Minerals Supply Chain 

Sourcing critical minerals like lithium, cobalt, and rare-earth elements involves a complex global network dominated by countries like China and the Democratic Republic of the Congo, which raises associated ethical and geopolitical concerns. To strengthen and secure supply chains, the United States must diversify sources, invest in recycling and alternative materials, strengthen domestic processing, and build international partnerships. 

Foreign Collaboration and Competition 

Historically, the US has led the world in nanotechnology, but the gap between it and China has narrowed. As great-power competition intensifies, many researchers are concerned that fundamental research could become subject to export controls, deterring international collaborations. There is an urgent need for clarification of these policies, particularly those delineating fundamental research and export-controlled research. 

Infrastructure for ML-Assisted Materials Science 

The US benefits from having some of the world’s largest supercomputing resources, which are essential for ML and for developing extensive databases. However, better access to computing power—and data—is needed to generate and analyze data effectively.

Report Preview: Materials Science

Faculty Council Advisor

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Zhenan Bao
Author
Zhenan Bao

Zhenan Bao is the K. K. Lee Professor in Chemical Engineering and Professor, by courtesy, of chemistry and materials science and engineering at Stanford University. She has close to seven hundred referred publications and more than eighty US patents. Her current research focuses on organic electronics, including skin-inspired materials, dynamic energy storage, and recyclable, re-processable materials. She received her PhD in chemistry from the University of Chicago.

View Bio
zhenan-bao_profilephoto.jpg
Zhenan Bao

Zhenan Bao is the K. K. Lee Professor in Chemical Engineering and Professor, by courtesy, of chemistry and materials science and engineering at Stanford University. She has close to seven hundred referred publications and more than eighty US patents. Her current research focuses on organic electronics, including skin-inspired materials, dynamic energy storage, and recyclable, re-processable materials. She received her PhD in chemistry from the University of Chicago.

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