Close Menu
  • Home
  • AI Models
    • DeepSeek
    • xAI
    • OpenAI
    • Meta AI Llama
    • Google DeepMind
    • Amazon AWS AI
    • Microsoft AI
    • Anthropic (Claude)
    • NVIDIA AI
    • IBM WatsonX Granite 3.1
    • Adobe Sensi
    • Hugging Face
    • Alibaba Cloud (Qwen)
    • Baidu (ERNIE)
    • C3 AI
    • DataRobot
    • Mistral AI
    • Moonshot AI (Kimi)
    • Google Gemma
    • xAI
    • Stability AI
    • H20.ai
  • AI Research
    • Allen Institue for AI
    • arXiv AI
    • Berkeley AI Research
    • CMU AI
    • Google Research
    • Microsoft Research
    • Meta AI Research
    • OpenAI Research
    • Stanford HAI
    • MIT CSAIL
    • Harvard AI
  • AI Funding & Startups
    • AI Funding Database
    • CBInsights AI
    • Crunchbase AI
    • Data Robot Blog
    • TechCrunch AI
    • VentureBeat AI
    • The Information AI
    • Sifted AI
    • WIRED AI
    • Fortune AI
    • PitchBook
    • TechRepublic
    • SiliconANGLE – Big Data
    • MIT News
    • Data Robot Blog
  • Expert Insights & Videos
    • Google DeepMind
    • Lex Fridman
    • Matt Wolfe AI
    • Yannic Kilcher
    • Two Minute Papers
    • AI Explained
    • TheAIEdge
    • Matt Wolfe AI
    • The TechLead
    • Andrew Ng
    • OpenAI
  • Expert Blogs
    • François Chollet
    • Gary Marcus
    • IBM
    • Jack Clark
    • Jeremy Howard
    • Melanie Mitchell
    • Andrew Ng
    • Andrej Karpathy
    • Sebastian Ruder
    • Rachel Thomas
    • IBM
  • AI Policy & Ethics
    • ACLU AI
    • AI Now Institute
    • Center for AI Safety
    • EFF AI
    • European Commission AI
    • Partnership on AI
    • Stanford HAI Policy
    • Mozilla Foundation AI
    • Future of Life Institute
    • Center for AI Safety
    • World Economic Forum AI
  • AI Tools & Product Releases
    • AI Assistants
    • AI for Recruitment
    • AI Search
    • Coding Assistants
    • Customer Service AI
    • Image Generation
    • Video Generation
    • Writing Tools
    • AI for Recruitment
    • Voice/Audio Generation
  • Industry Applications
    • Finance AI
    • Healthcare AI
    • Legal AI
    • Manufacturing AI
    • Media & Entertainment
    • Transportation AI
    • Education AI
    • Retail AI
    • Agriculture AI
    • Energy AI
  • AI Art & Entertainment
    • AI Art News Blog
    • Artvy Blog » AI Art Blog
    • Weird Wonderful AI Art Blog
    • The Chainsaw » AI Art
    • Artvy Blog » AI Art Blog
What's Hot

OpenAI inks monumental $300 billion cloud deal with Oracle

Google DeepMind Uses AI to Detect Gravitational Waves, Featured in Science_Wen_waves_tubes

Floating Point Precision Optimization, AI Model Training Efficiency Soars!_The_brings_This

Facebook X (Twitter) Instagram
Advanced AI News
  • Home
  • AI Models
    • OpenAI (GPT-4 / GPT-4o)
    • Anthropic (Claude 3)
    • Google DeepMind (Gemini)
    • Meta (LLaMA)
    • Cohere (Command R)
    • Amazon (Titan)
    • IBM (Watsonx)
    • Inflection AI (Pi)
  • AI Research
    • Allen Institue for AI
    • arXiv AI
    • Berkeley AI Research
    • CMU AI
    • Google Research
    • Meta AI Research
    • Microsoft Research
    • OpenAI Research
    • Stanford HAI
    • MIT CSAIL
    • Harvard AI
  • AI Funding
    • AI Funding Database
    • CBInsights AI
    • Crunchbase AI
    • Data Robot Blog
    • TechCrunch AI
    • VentureBeat AI
    • The Information AI
    • Sifted AI
    • WIRED AI
    • Fortune AI
    • PitchBook
    • TechRepublic
    • SiliconANGLE – Big Data
    • MIT News
    • Data Robot Blog
  • AI Experts
    • Google DeepMind
    • Lex Fridman
    • Meta AI Llama
    • Yannic Kilcher
    • Two Minute Papers
    • AI Explained
    • TheAIEdge
    • The TechLead
    • Matt Wolfe AI
    • Andrew Ng
    • OpenAI
    • Expert Blogs
      • François Chollet
      • Gary Marcus
      • IBM
      • Jack Clark
      • Jeremy Howard
      • Melanie Mitchell
      • Andrew Ng
      • Andrej Karpathy
      • Sebastian Ruder
      • Rachel Thomas
      • IBM
  • AI Tools
    • AI Assistants
    • AI for Recruitment
    • AI Search
    • Coding Assistants
    • Customer Service AI
  • AI Policy
    • ACLU AI
    • AI Now Institute
    • Center for AI Safety
  • Business AI
    • Advanced AI News Features
    • Finance AI
    • Healthcare AI
    • Education AI
    • Energy AI
    • Legal AI
LinkedIn Instagram YouTube Threads X (Twitter)
Advanced AI News
MIT News

MIT Technology Could Slash Energy Use in Oil Refining by 90%

By Advanced AI EditorJune 7, 2025No Comments2 Mins Read
Share Facebook Twitter Pinterest Copy Link Telegram LinkedIn Tumblr Email
Share
Facebook Twitter LinkedIn Pinterest Email


Engineers at MIT have developed a new approach to crude oil fractionating that could slash the amount of energy needed for processing the crude into different fuels by as much as 90% in a breakthrough that could revolutionize fuel production.

MIT engineers have developed a membrane that can filter the components of crude oil based on their molecular size, eliminating the need for crude oil distillation, which is highly energy-intensive.

According to MIT, separating crude oil into products such as gasoline, diesel, and heating oil accounts for about 6% of the global carbon dioxide (CO2) emissions. Most of that energy goes into the heat needed to separate the components by their boiling point.

In a study published by the journal Science, the team at MIT revealed that it had developed a new filtration membrane that can efficiently separate heavy and light components from oil. The membrane is resistant to the swelling that tends to occur with other types of oil separation membranes.

According to MIT, the membrane is a thin film that can be manufactured using a technique that is already widely used in industrial processes, potentially allowing it to be scaled up for widespread use.

MIT engineers modified polymers that have been used in water desalination by changing the bonds and introducing monomers.

“This is a whole new way of envisioning a separation process. Instead of boiling mixtures to purify them, why not separate components based on shape and size? The key innovation is that the filters we developed can separate very small molecules at an atomistic length scale,” says Zachary P. Smith, an associate professor of chemical engineering at MIT and the senior author of the new study.

Conventional heat-driven processes for fractionating crude oil make up about 1% of global energy use, and it has been estimated that using membranes for crude oil separation could reduce the amount of energy needed by about 90%, MIT said.

By Tsvetana Paraskova for Oilprice.com

More Top Reads From Oilprice.com



Source link

Follow on Google News Follow on Flipboard
Share. Facebook Twitter Pinterest LinkedIn Tumblr Email Copy Link
Previous ArticleNebius Stock (NBIS) Surges 20% Following a $1B AI Funding Round
Next Article IBM’s cloud crisis deepens: 54 services disrupted in latest outage
Advanced AI Editor
  • Website

Related Posts

New MIT Tech Sees Underwater As if the Water Weren’t There

September 13, 2025

MIT investigating after swastikas, other messages discovered

September 12, 2025

The Download: America’s gun crisis, and how AI video models work

September 12, 2025
Leave A Reply

Latest Posts

Ohio Auction of Two Paintings Looted By Nazis Halted By Foundation

Lee Ufan Painting at Center of Bribery Investigation in Korea

Drought Reveals 40 Ancient Tombs in Northern Iraqi Reservoir

Artifacts Removed from Gaza Building Before Suspected Israeli Strike

Latest Posts

OpenAI inks monumental $300 billion cloud deal with Oracle

September 13, 2025

Google DeepMind Uses AI to Detect Gravitational Waves, Featured in Science_Wen_waves_tubes

September 13, 2025

Floating Point Precision Optimization, AI Model Training Efficiency Soars!_The_brings_This

September 13, 2025

Subscribe to News

Subscribe to our newsletter and never miss our latest news

Subscribe my Newsletter for New Posts & tips Let's stay updated!

Recent Posts

  • OpenAI inks monumental $300 billion cloud deal with Oracle
  • Google DeepMind Uses AI to Detect Gravitational Waves, Featured in Science_Wen_waves_tubes
  • Floating Point Precision Optimization, AI Model Training Efficiency Soars!_The_brings_This
  • Which AI Powerhouse Should You Buy Now?
  • QBTS in Focus Amid Quantum Launches, Competition With IBM, HON – September 10, 2025

Recent Comments

  1. natyajnie potolki_shKt on 10 best AI coding tools in 2025
  2. Brentcrelp on Marc Raibert: Boston Dynamics and the Future of Robotics | Lex Fridman Podcast #412
  3. Brentcrelp on Study: AI-Powered Research Prowess Now Outstrips Human Experts, Raising Bioweapon Risks
  4. binance on Prompt Stability Matters: Evaluating and Optimizing Auto-Generated Prompt in General-Purpose Systems
  5. HarryMoF on 1-800-CHAT-GPT—12 Days of OpenAI: Day 10

Welcome to Advanced AI News—your ultimate destination for the latest advancements, insights, and breakthroughs in artificial intelligence.

At Advanced AI News, we are passionate about keeping you informed on the cutting edge of AI technology, from groundbreaking research to emerging startups, expert insights, and real-world applications. Our mission is to deliver high-quality, up-to-date, and insightful content that empowers AI enthusiasts, professionals, and businesses to stay ahead in this fast-evolving field.

Subscribe to Updates

Subscribe to our newsletter and never miss our latest news

Subscribe my Newsletter for New Posts & tips Let's stay updated!

LinkedIn Instagram YouTube Threads X (Twitter)
  • Home
  • About Us
  • Advertise With Us
  • Contact Us
  • DMCA
  • Privacy Policy
  • Terms & Conditions
© 2025 advancedainews. Designed by advancedainews.

Type above and press Enter to search. Press Esc to cancel.