|
Forecast Period
|
2025-2029
|
|
Market Size (2023)
|
USD 127.98 Million
|
|
Market Size (2029)
|
USD 256.80 Million
|
|
CAGR (2024-2029)
|
12.48%
|
|
Fastest Growing Segment
|
Chemicals
|
|
Largest Market
|
North America
|
Market Overview
Global Material
Informatics Market was valued at USD 127.98 Million in 2023 and is anticipated
to project impressive growth in the forecast period with a CAGR of 12.48%
through 2029. The Global Material
Informatics Market is experiencing rapid growth, driven by the increasing
demand for advanced materials across various industries, such as aerospace,
automotive, healthcare, and electronics. Material informatics leverages data
science, machine learning, and artificial intelligence to accelerate the
discovery, development, and deployment of new materials. This interdisciplinary
field integrates materials science with informatics to analyze and predict
material properties, leading to more efficient and cost-effective production
processes. One of the primary factors propelling the market is the rising need
for innovative materials that offer superior performance, sustainability, and
reduced environmental impact. As industries seek to develop lightweight,
stronger, and more durable materials, the adoption of material informatics is
becoming essential.
Key players in
the market are investing heavily in research and development to harness the
potential of big data and computational tools for materials innovation.
Companies are also forming strategic partnerships with academic institutions
and technology providers to stay at the forefront of advancements in this
field. Government initiatives and funding aimed at promoting
advanced manufacturing technologies are bolstering market growth. For instance,
various national laboratories and research organizations are collaborating to
create extensive materials databases that can be accessed by industries for
accelerated innovation.
Key Market Drivers
Technological
Advancements in Data Science and AI
The integration of data science, machine
learning (ML), and artificial intelligence (AI) into materials science is
revolutionizing the field, driving unprecedented advancements and efficiency.
Traditionally, the discovery and development of new materials relied heavily on
experimental trials and a trial-and-error approach, which were both
time-consuming and costly. However, with the advent of advanced computational
techniques, this paradigm is shifting towards a more data-driven and predictive
methodology.
AI and ML algorithms have the capability
to analyze vast amounts of data swiftly, identifying patterns and correlations
that are often imperceptible to human researchers. These technologies can
process and interpret complex datasets derived from various sources, including
experimental results, theoretical calculations, and historical data. By doing
so, they can predict material properties, such as strength, conductivity, and
thermal stability, with high accuracy. This predictive power is crucial in screening
potential materials before they undergo expensive and time-consuming
experimental validation.
One of the most transformative
applications of AI and ML in materials science is molecular-level simulation
and modeling. Researchers can create detailed virtual models of materials,
allowing them to simulate and observe behaviors under different conditions.
This capability enables the exploration of a wide range of material
compositions and structures, accelerating the discovery of optimal materials
for specific applications. For instance, in the pharmaceutical industry, such
simulations can predict how new compounds interact with biological systems,
speeding up the drug discovery process.
The computational approach provided by
data science and AI drastically reduces the time required for material
discovery and development. Traditional experimental methods can take years or
even decades to bring new materials to market. In contrast, AI-driven methods
can reduce this timeframe to months or even weeks. The cost
savings are substantial, as fewer resources are spent on physical experiments.
This efficiency not only accelerates innovation but also makes the development
of advanced materials more economically viable.
Rise
in Sustainability and Environmental Concerns
The growing awareness of environmental
issues and the pressing need for sustainable practices are significantly
influencing the materials science field. Industries across the globe are
increasingly prioritizing eco-friendly materials with lower carbon footprints
to address climate change and resource depletion. This shift towards
sustainability is driven by both regulatory pressures and consumer demand for
greener products. Material informatics plays a crucial role in the discovery
and development of sustainable materials. By leveraging data science, machine
learning (ML), and artificial intelligence (AI), researchers can analyze
extensive datasets to identify materials with desirable environmental
properties. This approach enables the exploration of a broader range of
materials, including those that might have been overlooked using traditional
methods. The ability to predict and optimize material properties through
computational models accelerates the identification of sustainable
alternatives.
One of the key benefits of material
informatics is its ability to optimize materials for specific environmental
criteria. Researchers can model the lifecycle impacts of materials, including
their energy consumption, greenhouse gas emissions, and recyclability. This
comprehensive analysis helps in developing materials that not only meet
performance requirements but also minimize environmental harm. For example, in
the packaging industry, material informatics can lead to the creation of
biodegradable plastics or materials with reduced dependency on fossil fuels.
Material informatics supports industries
in complying with stringent environmental regulations and achieving
sustainability goals. Governments and regulatory bodies are increasingly
imposing limits on emissions, waste, and the use of hazardous substances. By
using material informatics, companies can ensure that their materials and
products adhere to these regulations, avoiding potential fines and reputational
damage. Adopting sustainable materials enhances corporate
responsibility and aligns with the growing consumer preference for
environmentally conscious brands. The push towards greener technologies is
heavily reliant on the development of sustainable materials. Material
informatics not only facilitates this development but also promotes innovation
in various sectors, such as renewable energy, electric vehicles, and green
building materials. For instance, the advancement of high-performance batteries
for electric vehicles depends on discovering materials that are both efficient
and sustainable. Similarly, the construction industry benefits from new
materials that reduce energy consumption and carbon emissions.
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Key Market Challenges
Data
Quality and Availability
One of the primary challenges in the
material informatics market is the quality and availability of data. Material
informatics relies heavily on large datasets to train machine learning (ML)
algorithms and drive AI models. However, obtaining high-quality, comprehensive
data can be difficult. Data from different sources often vary in format,
completeness, and accuracy, making it challenging to integrate and analyze
effectively. Proprietary data held by private companies is often
inaccessible, limiting the scope of available information.
Incomplete or low-quality data can lead
to inaccurate predictions and unreliable models, undermining the benefits of
material informatics. For example, inconsistencies in experimental conditions,
measurement techniques, or data recording practices can result in datasets that
are difficult to reconcile. This fragmentation not only hampers the training of
robust ML models but also reduces the overall confidence in the predictive
capabilities of these models. Addressing this issue requires standardized data
collection methods and improved data sharing practices across the industry.
Standardization can ensure that data is collected uniformly, making it easier
to combine and compare datasets from different sources. This could involve
developing industry-wide protocols for data recording and reporting, as well as
creating common formats for data storage and exchange.
Enhanced collaboration between academia,
industry, and government can facilitate better data integration and quality.
Collaborative efforts can lead to the creation of comprehensive, high-quality
databases that are accessible to all stakeholders. For instance, public-private
partnerships can help bridge the gap between proprietary data and publicly
available information, enriching the datasets available for material
informatics.
Interdisciplinary
Skill Gaps
Material informatics represents a
convergence of multiple disciplines, including materials science, data science,
and computational modeling. However, the demand for professionals with
expertise in all these areas far outstrips the current supply, leading to
significant interdisciplinary skill gaps in the workforce. Traditionally,
materials scientists focused on experimental techniques for synthesizing and
characterizing materials, while computational scientists primarily worked on
data analysis and modeling. Bridging the gap between these disciplines requires
individuals with a deep understanding of both material science concepts and
advanced data analytics techniques.
The shortage of professionals with
interdisciplinary skills poses several challenges to the effective
implementation and utilization of material informatics technologies. Without
adequate expertise, organizations may struggle to develop accurate predictive
models or effectively interpret data insights. This can result in suboptimal
material design and development processes, limiting the potential for
innovation and advancement in the field.Addressing the interdisciplinary skill
gap requires targeted educational and training programs that equip
professionals with the necessary knowledge and expertise. Universities and
training institutions can develop interdisciplinary curricula that integrate
materials science, data science, and computational modeling courses. Industry-academic partnerships can provide hands-on training
opportunities and real-world experience to aspiring material informatics
professionals.
Key Market Trends
Emergence
of Cloud-Based Platforms
The advent of cloud-based platforms and
software solutions is profoundly transforming the material informatics
landscape, enabling unprecedented efficiencies and capabilities. These
platforms integrate seamlessly into existing workflows, enhancing the overall
productivity and collaborative potential of research and development teams. By
facilitating real-time data sharing, collaboration, and more accurate
simulations, cloud-based solutions are revolutionizing how materials are
discovered, developed, and optimized.
Cloud-based platforms allow for the
smooth integration of material informatics into the workflows of research and
development teams. This integration is crucial for enabling real-time data
sharing and collaboration among geographically dispersed teams. Researchers can
access and contribute to a centralized database, ensuring that data is
consistently updated and available to all stakeholders. This real-time
collaboration accelerates the pace of innovation, as insights and discoveries
can be rapidly shared and built upon. One of the most significant advantages of
cloud-based solutions is their scalability. Researchers and engineers can scale
their computational resources up or down based on the complexity and demands of
their projects. This flexibility eliminates the need for extensive on-premises
infrastructure, which can be costly and difficult to maintain. Cloud platforms
provide access to high-performance computing resources, enabling the execution
of complex simulations and analyses that would otherwise be impractical. This
scalability ensures that material informatics can be applied to a wide range of
projects, from small-scale studies to large-scale industrial applications.
Cloud-based platforms democratize access
to advanced computational tools, making them available to a broader range of
users, including small and medium-sized enterprises (SMEs) and academic
institutions. This accessibility reduces barriers to entry and fosters a more
inclusive innovation ecosystem. The pay-as-you-go model of cloud
services is cost-efficient, allowing organizations to manage their budgets more
effectively by only paying for the resources they use. This cost efficiency is
particularly beneficial for startups and research institutions with limited
funding.
The ease of access and enhanced computational
power provided by cloud-based platforms are driving the adoption of material
informatics across various industries. Sectors such as aerospace, automotive,
healthcare, and electronics are leveraging these platforms to accelerate the
development of advanced materials. For instance, the aerospace industry uses
cloud-based simulations to design lightweight yet durable materials for
aircraft, while the healthcare sector explores new biomaterials for medical
applications. The broad applicability of cloud-based material informatics
underscores its transformative potential across multiple fields.
Increasing
Demand for Advanced Materials
Industries such as aerospace,
automotive, electronics, and healthcare are continuously seeking advanced
materials that provide superior performance, durability, and sustainability.
These advanced materials are crucial for driving innovation and maintaining
competitive advantage in increasingly demanding markets. Material informatics
is pivotal in addressing these needs by facilitating the rapid development of
materials with specific, optimized properties. In the aerospace industry, there
is a constant demand for materials that are lightweight yet incredibly strong
and heat-resistant. Such materials are essential for improving fuel efficiency,
reducing emissions, and enhancing the overall performance and safety of
aircraft. Material informatics helps researchers discover and optimize alloys
and composites that meet these stringent requirements. By leveraging data
science and AI, the aerospace industry can develop materials that withstand
extreme conditions while minimizing weight.
The automotive sector is also heavily
focused on advanced materials to enhance fuel efficiency and reduce vehicle
weight. Lightweight materials, such as advanced high-strength steels, aluminum
alloys, and carbon fiber composites, are critical for achieving these goals.
Material informatics accelerates the identification and development of such
materials by predicting their properties and performance through computational
models. This capability allows automotive manufacturers to innovate faster,
bringing more efficient and environmentally friendly vehicles to market.
In the electronics industry, the demand
for materials with high thermal conductivity and electrical insulation
properties is paramount. These materials are vital for the development of
smaller, faster, and more reliable electronic devices. Material informatics
enables the exploration of new materials that can dissipate heat effectively
while maintaining electrical insulation, thereby supporting the miniaturization
and performance enhancement of electronic components. The healthcare sector
seeks advanced materials for medical devices, implants, and drug delivery
systems that are biocompatible, durable, and capable of functioning in complex
biological environments. Material informatics aids in the discovery of
biomaterials that meet these criteria, facilitating innovations in medical
technology and improving patient outcomes. For instance, researchers can use
computational models to design materials for prosthetics that are both
lightweight and highly durable.
One of the primary advantages of
material informatics is its ability to accelerate the development and
customization of materials. Traditional methods of material discovery are often
slow and resource-intensive, involving extensive trial and error. In contrast,
material informatics uses advanced algorithms and data analysis to predict the
properties and performance of new materials quickly. This predictive capability
significantly reduces development time and costs, allowing industries to
respond swiftly to changing market demands and technological advancements.
Segmental Insights
Application Insights
Based on the Application, in 2023, the
Energy segment emerged as the dominant segment in the Global Material
Informatics Market. This dominance can be attributed to several factors driving
the demand for advanced materials and the adoption of material informatics
within the energy sector. The push towards renewable energy sources, such as
solar and wind power, has fueled the need for materials with enhanced
performance characteristics. Advanced materials are crucial for improving the
efficiency and durability of renewable energy technologies, such as
photovoltaic cells and wind turbine blades. Material informatics enables
researchers to discover and optimize materials that can withstand harsh
environmental conditions, leading to more reliable and cost-effective renewable
energy systems.
The transition towards electric vehicles
(EVs) has spurred innovation in battery technology. Lithium-ion batteries, the
primary energy storage technology used in EVs, require materials with high
energy density, fast charging capabilities, and long-term stability. Material
informatics facilitates the development of new battery materials by predicting
their electrochemical properties and optimizing their performance through
computational modeling. The quest for sustainable energy solutions has prompted
research into alternative energy sources, such as hydrogen fuel cells and
advanced nuclear reactors. These technologies rely on materials that can
efficiently catalyze chemical reactions, withstand high temperatures and
pressures, and minimize environmental impacts. Material informatics accelerates
the discovery of such materials by providing insights into their
structure-property relationships and guiding experimental efforts towards the
most promising candidates.
Material Type Insights
Based on the Material Type, in 2023, the
Chemicals segment emerged as the dominant segment in the Global Material
Informatics Market. The chemicals sector encompasses a wide range of
industries, including pharmaceuticals, cosmetics, agrochemicals, and specialty
chemicals. Each of these industries relies heavily on advanced materials to
develop innovative products with enhanced performance characteristics. Material
informatics enables researchers to discover and optimize materials that meet
specific requirements, such as chemical stability, solubility, and toxicity
profile, leading to the development of safer, more effective, and
environmentally friendly products.
The chemicals industry faces increasing
regulatory pressure to minimize environmental impact and reduce the use of
hazardous substances. Material informatics plays a crucial role in addressing
these challenges by facilitating the development of sustainable materials and
processes. Researchers can use computational modeling and data analytics to
design materials with lower carbon footprints, improved recyclability, and
reduced waste generation, aligning with global sustainability goals. The
chemicals sector is highly competitive, with companies constantly seeking to
differentiate their products through innovation. Material informatics provides
a competitive advantage by accelerating the pace of materials discovery and
development, enabling companies to bring new products to market faster and more
cost-effectively.
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Regional Insights
In 2023,
North America emerged as the dominant region in the Global Material Informatics
Market, holding the largest market share. North America boasts a strong
presence of key players and leading technology hubs in the field of material
informatics. The region is home to prominent companies, research institutions,
and universities that are at the forefront of developing advanced materials and
leveraging data-driven approaches for materials discovery and development.
These entities drive innovation and technological advancements in material
informatics, attracting investments and fostering a thriving ecosystem for
research and development.
North
America benefits from robust infrastructure and advanced technology adoption,
which provide a conducive environment for the growth of the material
informatics market. The region has access to high-performance computing
resources, data analytics platforms, and state-of-the-art laboratories,
enabling researchers and companies to conduct cutting-edge research and
experimentation in material science. North America has a diverse
industrial landscape with a high demand for advanced materials across various sectors,
including aerospace, automotive, electronics, healthcare, and energy. The
region's strong manufacturing base and emphasis on innovation drive the
adoption of material informatics technologies to improve product performance,
reduce costs, and enhance competitiveness in global markets.
Recent Developments
- In November 2023, Proterial, Ltd.
unveiled its proprietary Materials Informatics (MI) platform,
"D2Materi." D2Materi adopts a data-centric methodology to predict
materials properties and formulate novel materials. By analyzing accumulated
data, including unconventional datasets such as metallic materials, the
platform discerns correlations between materials' performance, composition, and
various factors like processes, regulations, and characteristics. This advanced
approach equips the platform to effectively address the challenge of designing
materials with efficiency.
Key Market Players
- AI Materia Inc.
- ALPINE ELECTRONICS, Inc.
- Citrine Informatics
- Dassault Systèmes S.E.
- Exabyte Inc.
- Hitachi High-Tech Corporation
- Kebotix, Inc.
- Materials.Zone Ltd.
- Materials Design, Inc.
- DataRobot, Inc.
|
By Application
|
By Material Type
|
By Technique
|
By Region
|
- Chemical and Pharmaceuticals
- Material Science
- Manufacturing
- Food Science
- Energy
- Others
|
|
- Digital Annealer
- Deep Tensor
- Statistical Analysis
- Genetic Algorithm
|
- North America
- Europe
- Asia Pacific
- South America
- Middle East & Africa
|
Report Scope:
In this report, the Global Material
Informatics Market has been segmented into the following categories, in
addition to the industry trends which have also been detailed below:
- Material
Informatics Market, By Application:
o Chemical and Pharmaceuticals
o Material Science
o Manufacturing
o Food Science
o Energy
o Others
- Material
Informatics Market, By Material Type:
o Elements
o Chemicals
o Others
- Material
Informatics Market, By Technique:
o Digital Annealer
o Deep Tensor
o Statistical Analysis
o Genetic Algorithm
- Material
Informatics Market, By Region:
o
North America
§ United
States
§ Canada
§ Mexico
o
Europe
§ France
§ United
Kingdom
§ Italy
§ Germany
§ Spain
o
Asia-Pacific
§ China
§ India
§ Japan
§ Australia
§ South
Korea
o
South America
§ Brazil
§ Argentina
§ Colombia
o
Middle East & Africa
§ South
Africa
§ Saudi
Arabia
§ UAE
Competitive Landscape
Company
Profiles: Detailed
analysis of the major companies present in the Global Material Informatics Market.
Available Customizations:
Global Material Informatics market report with the given market data,
TechSci Research offers customizations according to a company's specific needs.
The following customization options are available for the report:
Company Information
- Detailed analysis and profiling of additional market players (up to
five).
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soon. If you wish an early delivery of this report or want to confirm the date
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