Plastic modeling – Plamo http://plamo.info/ Sat, 03 Sep 2022 09:57:25 +0000 en-US hourly 1 https://wordpress.org/?v=5.9.3 https://plamo.info/wp-content/uploads/2021/06/icon-3-105x105.png Plastic modeling – Plamo http://plamo.info/ 32 32 Alarm bells ringing on Court Street in Binghamton for months https://plamo.info/alarm-bells-ringing-on-court-street-in-binghamton-for-months/ Fri, 02 Sep 2022 19:15:36 +0000 https://plamo.info/alarm-bells-ringing-on-court-street-in-binghamton-for-months/ The incessant beeping of what could be a fire alarm system can be heard in the heart of downtown Binghamton…and no one seems inclined to turn it off. The noise has been emanating from inside the closed Galaxy Brewing Company craft beer facility at 41 Court Street for several months. Many people who operate businesses […]]]>

The incessant beeping of what could be a fire alarm system can be heard in the heart of downtown Binghamton…and no one seems inclined to turn it off.

The noise has been emanating from inside the closed Galaxy Brewing Company craft beer facility at 41 Court Street for several months.

Many people who operate businesses nearby have become accustomed to the incessant beeps.

The old Galaxy Brewing building on Court Street on September 2, 2022. Photo: Bob Joseph/WNBF News

The old Galaxy Brewing building on Court Street on September 2, 2022. (Photo: Bob Joseph/WNBF News)

A woman from the Currys of India restaurant next to Galaxy Brewing said “it’s always like that”. She indicated that she was not disturbed by the alarm.

A couple who often walk their dog past the closed business were intrigued by the continuous beeping of the alarm. They said they noticed it and wondered why nothing had been done about it. But a person who lives near the Galaxy Brewing site said he never heard the alarm.

A man shopping at a nearby store said he thought he had heard the alarm for almost a year.

Seth and Michael Weisel as Galaxy Brewing Company opened August 30, 2013. Photo: Roger Neel/WNBF News

Seth and Michael Weisel as Galaxy Brewing Company opened August 30, 2013. (Photo: Roger Neel/WNBF News)

Seth and Michael Weisel opened Galaxy Brewing in August 2013. The craft beer business also served food for several years, although the restaurant closed in December 2018.

The Weisels could not be reached for comment on the alarm situation and no one from the Binghamton Fire Department was available to discuss the matter.

Photo: Bob Joseph/WNBF News

Galaxy Brewing’s Andromeda IPA canned in February 2017. (Photo: Bob Joseph/WNBF News)

A proposal for a new Galaxy Brewing facility at the former EH Titchener complex on Clinton Street was presented to the planning commission in April 2019.

Galaxy Brewing canned its last beer in the summer of 2020 at the start of the Covid-19 pandemic.

Contact Bob Joseph, WNBF News reporter: bob@wnbf.com or (607) 545-2250. For the latest story development news and updates, follow @BinghamtonNow on Twitter.

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Industrial 3D Printing Market Expected to Hit $107.7 https://plamo.info/industrial-3d-printing-market-expected-to-hit-107-7/ Mon, 29 Aug 2022 10:00:00 +0000 https://plamo.info/industrial-3d-printing-market-expected-to-hit-107-7/ Portland, OR, Aug. 29, 2022 (GLOBE NEWSWIRE) — According to the report released by Allied Market Research, the industrial 3D printing market generated $15 billion in 2021 and is expected to reach $107.7 billion by 2031, growing at a CAGR of 21.9% from 2022 to 2031. The report provides an in-depth study of major investment […]]]>

Portland, OR, Aug. 29, 2022 (GLOBE NEWSWIRE) — According to the report released by Allied Market Research, the industrial 3D printing market generated $15 billion in 2021 and is expected to reach $107.7 billion by 2031, growing at a CAGR of 21.9% from 2022 to 2031. The report provides an in-depth study of major investment pockets, trends market dynamics, regional landscape, major segments, value chain and competitive scenario. The report is a vital source of information for new entrants, major market players, stakeholders and investors in strategizing for the future and taking action to strengthen their position in the market.

Download a free sample report (Get a detailed analysis in PDF – 398 pages): https://www.alliedmarketresearch.com/request-sample/17517

Report coverage and details:

Report cover Details
Forecast period 2022–2031
Year of reference 2021
Market size in 2021 $15 billion
Market size in 2031 $107.7 billion
CAGR 21.9%
Number of pages in the report 398
Segments Covered Component, technology, end user and region.
Drivers Growing demand for product customization to gain competitiveness
Rapid increase in the adoption of multiple materials for printing
Opportunities Increase in applications from multiple industries
Improved manufacturing processes
holds back High cost related to 3D printing
Requirement of qualified professionals

COVID-19 scenario:

  • The pandemic has negatively impacted the market due to strict lockdown regulations and prolonged lockdown in several businesses. The lockdown disrupted the supply chain and labor shortages hampered the manufacturing of 3D printing materials.
  • Major market players in the industry have experienced a huge downturn due to the shortage of skilled workers to develop 3D printing solutions.

The report offers a detailed segmentation of the global industrial 3D printing market on the basis of component, technology, end-user, and region. The report provides an analysis of each segment and sub-segment using tables and figures. This analysis helps market players, investors, and new entrants determine which sub-segments should be leveraged to achieve growth in the coming years.

Interested in getting the data? Find out here: https://www.alliedmarketresearch.com/purchase-enquiry/17517

Based on components, the hardware segment accounted for the highest share in 2021, contributing more than two-thirds of the total share, and is expected to maintain its leading status during the forecast period. Moreover, the segment is expected to show the highest CAGR of 22.1% from 2022 to 2031.

Based on the technology, the stereolithography (SLA) segment held the largest share in 2021, accounting for over a quarter of the market, and is expected to maintain its revenue dominance by 2031. However, deposition modeling of fusion (FDM ) the segment is believed to reflect the highest CAGR of 23.9% during the forecast period.

On the basis of end-user, the manufacturing segment dominated the market in 2021, contributing almost three quarters of the market, and is expected to maintain its dominance throughout the forecast period. However, the aerospace and defense segment would show the highest CAGR of 22.6% during the forecast period.

According to region, the North American market accounted for the highest share in 2021, contributing nearly half of the total market share. However, the LAMEA market is expected to show the fastest CAGR of 24.1% during the forecast period.

Get a detailed COVID-19 impact analysis on the Industrial 3D printing market: https://www.alliedmarketresearch.com/request-for-customization/17517?reqfor=covid

Key players of the global industrial 3D printing market analyzed in the research include 3D Systems, Autodesk Inc., Arcam Ab (General Electric), Envisiontec Inc., Canon Inc., ExOne Company, Eos GmbH., General Electric Company, GE Additive, HOGANAS AB, HP Inc., Materialise, OPTOMEC INC., Organovo Holdings Inc., Protolabs, SLM Solutions, Stratasys Ltd. and Voxeljet AG.

The report analyzes these key players in the global industrial 3D printing market. These players have adopted various strategies such as expansion, new product launches, partnerships and others to increase their market penetration and strengthen their position in the industry. The report is helpful in determining the business performance, operating segments, product portfolio, and developments of each market player.

Main benefits for stakeholders:

  • This report provides quantitative analysis of market segments, current trends, estimates and dynamics of Industrial 3D Printing Market analysis from 2021 to 2031 to identify the Industrial 3D Printing market opportunity .
  • Market research is offered with information related to key drivers, restraints, and opportunities.
  • Porter’s Five Forces analysis highlights the ability of buyers and suppliers to enable stakeholders to make profit-driven business decisions and strengthen their supplier-buyer network.
  • An in-depth analysis of the industrial 3D printing market outlook helps determine the existing market opportunities.
  • Major countries in each region are mapped according to their revenue contribution in the global market.
  • The positioning of market players facilitates benchmarking and provides a clear understanding of the current position of market players.
  • The report includes analysis of regional and global Industrial 3D Printing market trends, key players, market segments, application areas, Industrial 3D Printing market forecasts and growth strategies of the market.

Key segments of the industrial 3D printing market:
By Component:

By technology:

  • Stereolithography (SLA)
  • Selective Laser Sintering (SLS)
  • Electron Beam Melting (EBM)
  • Fused Deposition Modeling (FDM)
  • Manufacture of rolled objects (LOM)
  • Others

Per end user:

  • Manufacturing
  • Aeronautics and Defense
  • Others

By region:

  • North America (United States, Canada and Mexico)
  • Europe (UK, Germany, France, Italy, Spain, Russia, Netherlands, Belgium, Poland and Rest of Europe)
  • Asia Pacific (China, Japan, India, South Korea, Australia, Malaysia, Thailand, Philippines, Indonesia and Rest of Asia Pacific)
  • LAMEA (Latin America, Middle East and Africa)

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“We have also published a few syndicated market studies in the same area that you may be interested in. Below are the titles of the reports for your reference, considering the impact of COVID-19 on this market, which will help you to assess the impact of the pandemic on the short and long-term growth trends of this market”.

Reports on trends in the semiconductor and electronics industry (book now with 10% discount + COVID-19 scenario):

3D printing market By technology (stereolithography [SLA]Selective Laser Sintering [SLS]electron beam melting [EBM]Modeling of molten deposits [FDM]Manufacture of laminated objects [LOM]Others), Application (Consumer Electronics, Industrial, Aerospace, Automotive, Healthcare, Defense, Education & Research, and Others): Global Opportunities Analysis and Industry Forecast, 2020-2030

3D printing market in emerging economies – China, India, UAE, Brazil, South Africa (Components and Applications) Opportunities and Forecast, 2013-2020

Personal 3D printer market By type (hardware, software and services), material (plastic, metal, ceramics, resins and others), technology (molten wire deposition modeling [FDM]Stereolithography [SLA]Digital light processing [DLP]Continuous production of liquid interface [CLIP]Selective Laser Sintering [SLS]Stratification by selective deposition, Multi-jet fusion, Polyjet, Selective laser fusion [SLM]and others), form (filament, powder, and liquids), additive manufacturing process (material extrusion, powder bed fusion, light-curing, material jetting, and sheet lamination), and application (education, entertainment, photography, architecture, fashion and Jewelry, and Others): Global Opportunities Analysis and Industry Forecast, 2021-2030

3D technology market By Product (3D Printing, 3D Glasses, 3D Display, 3D Imaging, 3D Camera, and 3D Scanner), Application (Media & Entertainment, Automotive, Industrial, Healthcare, Military & Defense, and Others): Global Opportunity Analysis and Market Forecast industry, 2021-2030

About Us:

Allied Market Research (AMR) is a full-service market research and business consulting wing of Allied Analytics LLP based in Portland, Oregon. Allied Market Research provides global corporations as well as small and medium enterprises with unrivaled quality of “market research reports” and “Business Intelligence solutions”. AMR has a focused vision to provide business insights and advice to help its clients make strategic business decisions and achieve sustainable growth in their respective market area.

We maintain professional relationships with various companies which helps us to extract market data which helps us to generate accurate research data tables and confirm the utmost accuracy of our market predictions. Allied Market Research CEO Pawan Kumar helps inspire and encourage everyone associated with the company to maintain high quality data and help clients in every way possible to achieve success. All data presented in the reports we publish are drawn from primary interviews with senior managers of large companies in the relevant field. Our secondary data sourcing methodology includes extensive online and offline research and discussions with knowledgeable industry professionals and analysts.


Contact:

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Researchers discuss recycling 3D printed nylon composites https://plamo.info/researchers-discuss-recycling-3d-printed-nylon-composites/ Wed, 24 Aug 2022 14:30:00 +0000 https://plamo.info/researchers-discuss-recycling-3d-printed-nylon-composites/ A new article in the journal Sustainability explored the recycling of 3D printed nylon composites with the aim of improving the sustainability of the additive manufacturing industry. The research was conducted by scientists from the United Arab Emirates University in the United Arab Emirates. Study: Characterization and sustainability potential of recycling 3D printed nylon composite […]]]>

A new article in the journal Sustainability explored the recycling of 3D printed nylon composites with the aim of improving the sustainability of the additive manufacturing industry. The research was conducted by scientists from the United Arab Emirates University in the United Arab Emirates.

Study: Characterization and sustainability potential of recycling 3D printed nylon composite waste. Image Credit: Joaquin Corbalan P/Shutterstock.com

The scale of plastic and polymer composite waste

According to some reports, by 2050 there could be more plastic waste in the ocean than fish. The critical problem of large quantities of polymer and composite material waste entering the natural environment has crystallized industry and government action to limit the ecological damage it causes.

Block diagram of the material preparation process.

Block diagram of the material preparation process. Image credit: Al-Mazrouei, N et al., Sustainability

The National Geographic Society has estimated that there are currently 5.25 trillion pieces of plastic debris in the ocean, ranging from whole products to microplastic fragments. Microplastics pose a particular problem because they can be consumed by marine organisms and enter the food chain, causing damage to human and animal health. Plastic waste finds its way from the surface to the depths of the ocean.

3D printing and waste

The field of additive manufacturing has provided innovative solutions to many industries due to the design freedom and cost-effectiveness of 3D printing technologies. One of the characteristics of 3D printing is the reduction of waste compared to traditional manufacturing techniques. Products are built layer by layer from raw materials.

While waste is greatly reduced when 3D printing, there are still critical issues with waste in the industry that impact its overall sustainability. Products, especially composite filaments that are produced by commercial fusion deposition modeling techniques, are an additional source of plastic waste that complicates environmental remediation efforts.

Waste can be generated during additive manufacturing processes due to issues such as poor filament quality, hardware failures, slicing errors, and print bed adhesion issues. Recycling waste can be a complicated process, for example in the case of composites incorporating glass fibers and carbon fibers due to the toxic heavy metals produced during manufacture.

Tensile testing machine.

Tensile testing machine. Image credit: Al-Mazrouei, N et al., Sustainability

Recent studies have focused on combining different synthetic fibers and polymers to improve the properties of composites made by 3D printing methods, such as carbon fibers, glass fibers, and nylon fibers. Specific material challenges are associated with each reinforcing fiber, with different effects on the properties of the final product observed by researchers.

Challenges with dimensional quality control and consistency of material properties lead to problems recycling 3D printed polymer composite waste. However, the recycling of certain waste is possible but limited. In the case of materials incorporating carbon fiber, 30% of the waste can be recycled. Prototyping parts produced using FDM techniques can be recycled and reused.

The research

Recognizing the inherent difficulties in manufacturing 3D printed polymer composites and the recyclability and reuse of waste produced during processing, the authors produced recycled blended polymer composites.

The researchers mixed 3D-printed composite waste, carbon-fiber reinforced nylon, and glass-fiber reinforced nylon. This approach produced recycled composite sheets of CFGF/nylon materials. Filaments from 3D printing waste were used, offering a solution to improve the circularity of these materials. The composites were produced using different mix compositions.

To produce the composite sheets, the authors used a process that combines compression molding and a dual-extruder machine. The thermal and mechanical properties of the composite sheets produced were evaluated. Mechanical properties such as modulus of elasticity, toughness, tensile strength and ductility of composite materials were evaluated. FTIR and thermogravimetric analysis were used in the study.

Study results

The article demonstrated the relevance of recycled 3D printing waste for the manufacture of new functional products. Analysis of composite sheets incorporating different blends of carbon fiber, glass fiber, and nylon fiber reinforced materials revealed several important properties of each material.

Comparison of toughness of composites.

Comparison of toughness of composites. Image credit: Al-Mazrouei, N et al., Sustainability

The highest toughness and ductility were observed in pure glass fiber/nylon reinforced polymer composites. Although this was the highest result observed, the authors also found that adding 20% ​​by weight of fiberglass/nylon to carbon fiber/nylon composites increased their tensile strength. Increasing fiberglass/nylon from 50 to 60 wt% improved the elastic modulus, but at 80 wt% it decreased.

Thermal analysis revealed that pure carbon fiber/nylon composites possess a high degradation temperature compared to pure fiberglass/nylon composites. In addition, the incorporation of fibreglass/nylon decreases the degradation temperature of the composite.

In summary

The recyclability of 3D printing waste is currently a key area of ​​research in the industry. Being able to recycle and reuse polymers and composite materials will improve the sustainability and circularity of additive manufacturing and therefore the many industries that are increasingly using 3D printing methods.

The team behind the paper said the results of their study could be used in research into the recycling of many 3D-printed filament waste, providing several innovative opportunities for future research.

Further reading

Al-Mazrouei, N et al. (2022) Characterization and sustainability potential of recycling 3D printed nylon composite waste Sustainability 14(17) 10458 [online] mdpi.com. Available at: https://www.mdpi.com/2071-1050/14/17/10458

Disclaimer: The views expressed herein are those of the author expressed privately and do not necessarily represent the views of AZoM.com Limited T/A AZoNetwork, the owner and operator of this website. This disclaimer forms part of the terms of use of this website.

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New Jersey arts and entertainment news, features and event insights. https://plamo.info/new-jersey-arts-and-entertainment-news-features-and-event-insights/ Thu, 18 Aug 2022 19:09:40 +0000 https://plamo.info/new-jersey-arts-and-entertainment-news-features-and-event-insights/ NEW | FEATURES | PREVIEWS | EVENTS originally published: 08/18/2022 (LINCROFT, NJ) — Two Brookdale Community College Engineering the students created a prosthetic hand to qualify as a designer for e-NABLE, a national organization of volunteers who make free upper limb prostheses for people in need, especially children. Professor of Engineering and Technology Lisa Hailey […]]]>
NEW | FEATURES | PREVIEWS | EVENTS



originally published: 08/18/2022

(LINCROFT, NJ) — Two Brookdale Community College Engineering the students created a prosthetic hand to qualify as a designer for e-NABLE, a national organization of volunteers who make free upper limb prostheses for people in need, especially children.

Professor of Engineering and Technology Lisa Hailey introduced the 3D printer to his students at the beginning of the semester. She offered to help them with any special projects they wanted to do. At the end of the semester, two students approached her. Both graduated in May from Brookdale’s chemical engineering program. Anjeli Santillan, who received the STEM Outstanding Student Award, will continue her studies in biomedical. Mason Brown continues his studies in chemical engineering and both transfer to the New Jersey Institute of Technology (NJIT) with which Brookdale has an articulation agreement.

3D printing is a method of creating a three-dimensional object layer by layer using a computer-generated design. The students used an extrusion-based 3D printing technology called Fused Deposition Modeling (FDM). Like a hot glue gun, plastic filaments (spools of plastic) run across the top, layers of plastic melting and building up to create a 3D part.

The students printed the hand in a few parts, including the palm, knuckles, and fingers.

“The process was awesome, because I got to work with one of my favorite teachers on a project that I had wanted to do since high school,” Santillan said. to pursue biomedical engineering.”

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e-NABLE is a global movement of volunteers using 3D printers to create free 3D printed hands and arms for those in need of upper limb assist devices. To qualify to become an ENABLE volunteer, students will present the hand they have created by video to prove that it is of excellent quality. Then they are listed as being able to make that hand. So potentially their names will be on a list, and if a child lives in Monmouth County and needs a helping hand, they can call on Santillan or Brown to create one for the child.

“As volunteer creators of e-NABLE, Mason and mine’s goal is to send working hands to children for free,” Santillan said. “With NJIT’s Makerspace, we hope to continue this volunteer work while we are at school. We also look forward to joining the Prosthetics Club, where we will design and assemble animal prostheses.”

“I hope Anjeli and Mason’s work will inspire other students at Brookdale,” Professor Hailey said.

Brookdale offers five major areas of study in its engineering program, chemical, civil, electrical, industrial, and mechanical.

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Xometry (NASDAQ:XMTR) PT raised to $65.00 https://plamo.info/xometry-nasdaqxmtr-pt-raised-to-65-00/ Sat, 13 Aug 2022 08:42:46 +0000 https://plamo.info/xometry-nasdaqxmtr-pt-raised-to-65-00/ Xometry (NASDAQ: XMTR – Get a rating) had its price target raised by CL King from $55.00 to $65.00 in a note issued to investors on Thursday, Fly reports. The brokerage currently has a “buy” rating on the stock. CL King’s target price indicates a potential upside of 32.52% from the company’s previous close. Several […]]]>

Xometry (NASDAQ: XMTRGet a rating) had its price target raised by CL King from $55.00 to $65.00 in a note issued to investors on Thursday, Fly reports. The brokerage currently has a “buy” rating on the stock. CL King’s target price indicates a potential upside of 32.52% from the company’s previous close.

Several other research analysts also weighed in on XMTR. Loop Capital lowered its target price on Xometry from $50.00 to $46.00 and set a “buy” rating on the stock in a research report on Tuesday, July 19. Goldman Sachs Group raised its target price on Xometry from $44.00 to $64.00 and gave the stock a “buy” rating in a research report on Thursday. Finally, Royal Bank of Canada raised its target price on Xometry from $46.00 to $60.00 and gave the stock an “outperform” rating in a research report on Thursday.

Xometry stock down 3.3%

NASDAQ: XMTR opened at $49.05 on Thursday. The company has a market capitalization of $2.17 billion, a price-earnings ratio of -29.91 and a beta of 0.38. Xometry has a 1 year minimum of $26.61 and a 1 year maximum of $76.53. The company has a current ratio of 7.86, a quick ratio of 7.82 and a debt ratio of 0.68. The company’s fifty-day moving average price is $36.88 and its 200-day moving average price is $38.20.

Xometry (NASDAQ: XMTRGet a rating) last released its quarterly results on Wednesday, May 11. The company reported ($0.35) earnings per share for the quarter, beating the consensus estimate of ($0.44) by $0.09. Xometry had a negative return on equity of 16.04% and a negative net margin of 24.80%. The company posted revenue of $83.67 million for the quarter, versus analyst estimates of $81.02 million. On average, sell-side analysts expect Xometry to post -1.02 earnings per share for the current fiscal year.

Insider Trading at Xometry

In other news, CEO Randolph Altschuler sold 22,715 shares of the company in a trade dated Wednesday, June 8. The stock was sold at an average price of $35.03, for a total transaction of $795,706.45. Following the completion of the sale, the CEO now owns 101,582 shares of the company, valued at approximately $3,558,417.46. The transaction was disclosed in a document filed with the SEC, accessible via this hyperlink. In other news, CEO Randolph Altschuler sold 22,715 shares of the company in a trade dated Wednesday, June 8. The stock was sold at an average price of $35.03, for a total transaction of $795,706.45. Following the completion of the sale, the CEO now owns 101,582 shares of the company, valued at approximately $3,558,417.46. The transaction was disclosed in a document filed with the SEC, accessible via this hyperlink. Additionally, manager George Hornig sold 10,000 shares in a trade that took place on Friday, June 3. The shares were sold at an average price of $32.95, for a total value of $329,500.00. Following the sale, the director now owns 124,851 shares of the company, valued at approximately $4,113,840.45. Disclosure of this sale can be found here. During the last quarter, insiders sold 144,715 shares of the company worth $5,062,576.

Xometry Institutional Trading

Hedge funds have recently increased or reduced their stakes in the company. Advisors Asset Management Inc. acquired a new stake in Xometry during Q1 worth approximately $33,000. Ensign Peak Advisors Inc purchased a new stake in Xometry stock in Q1 worth approximately $61,000. Zurcher Kantonalbank Zurich Cantonalbank purchased a new equity stake in Xometry in Q1 for a value of approximately $67,000. Ameritas Investment Partners Inc. increased its position in Xometry shares by 209.7% in Q1. Ameritas Investment Partners Inc. now owns 1,914 shares of the company worth $70,000 after acquiring an additional 1,296 shares during the period. Finally, SeaCrest Wealth Management LLC purchased a new equity stake in Xometry in Q2 worth approximately $91,000. Institutional investors hold 77.31% of the company’s shares.

Xometry company profile

(Get a rating)

Xometry, Inc operates a marketplace that allows buyers to source parts and assemblies manufactured in the United States and overseas. It provides CNC machining, milling and turning services; sheet, laser, water jet and plasma cutting services; and sheet metal forming services. The company also offers 3D printing services, such as digital carbon light synthesis, fusion deposition modeling, HP multi-jet fusion, PolyJet, selective laser sintering, stereolithography, printing service 3D metal, direct metal laser sintering and metal binder jetting; and injection molding services, including plastic injection, overmolding, insert and prototype molding, as well as deck and production tooling.

Further reading

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Integration of triboelectric sensing and machine learning https://plamo.info/integration-of-triboelectric-sensing-and-machine-learning/ Mon, 08 Aug 2022 17:19:00 +0000 https://plamo.info/integration-of-triboelectric-sensing-and-machine-learning/ Robotic or automated manufacturing helps streamline workflow and advance manufacturing processes, allowing companies to stay globally competitive. One of the key factors in these processes is quality control which often requires validating or verifying the materials used in the processes. Image Credit: Shutterstock.com/ Willyam Bradberry Now researchers from the Institute of Nanoenergy and Nanosystems in […]]]>

Robotic or automated manufacturing helps streamline workflow and advance manufacturing processes, allowing companies to stay globally competitive. One of the key factors in these processes is quality control which often requires validating or verifying the materials used in the processes.

Image Credit: Shutterstock.com/ Willyam Bradberry

Now researchers from the Institute of Nanoenergy and Nanosystems in Beijing have developed a ‘smart finger’ that can identify materials using ‘triboelectric’ sensors that test its ability to gain or losing electrons, as well as determining other characteristics such as its roughness, without risk of causing damage. Published in the journal Scientists progressthe team describes how they developed the triboelectric smart finger.

In principle, as each material has different abilities to gain or lose electrons, a unique triboelectric fingerprint output will be generated when the triboelectric sensor is in contact with the measured object.

Dan Luo, CAS Center for Excellence in Nanoscience, Beijing Institute of Nanoenergy and Nanosystems

Machine learning and quantification of material parameters

Humans rely on haptic feedback as an essential sensory function when in direct contact or communication with the surrounding environment.

Tactile perception comes from the response of subcutaneous tactile corpuscles to different environmental stimuli and from the brain’s recognition of afferent signals via nerve fibers.

Dan Luo, CAS Center for Excellence in Nanoscience, Beijing Institute of Nanoenergy and Nanosystems

In general, quantifying material parameters precisely at the psychological level of tactile perception can be a challenge when it comes to identifying the texture and roughness of a material. The smart finger developed by the researchers also uses machine learning to help improve triboelectric tactile perception in the mechanism and help human users of such systems.

Additionally, the team said they developed a smart finger that surpassed human tactile perception, enabling accurate identification of material type and roughness through the integration of triboelectric sensing and machine learning.

They claim the smart finger has at least 90% accuracy when sensing the material surface, suggesting the technology has potential use in automating robotic manufacturing tasks, including sorting materials. materials and quality control assessments.

Develop a smart finger

In recent years, various efforts have been made to design sensors or devices capable of identifying materials based on various strategies, such as computer vision, thermal conductivity, ultrasound, etc. As a result, computer systems and robots are becoming increasingly good at interacting with the world around them, but they will also need a sense of touch before they can reach their full potential.

When tested on a variety of samples, such as plastic, wood, silicon and glass, the smart finger demonstrated an average accuracy of 96.8% and an accuracy of at least 90% for all materials.

The system incorporates machine learning-based data analysis with four small square sensors, each made of a different plastic polymer that has been specifically chosen for its electrically conductive properties. The sensors are housed in a housing that looks like a finger, hence the name “smart finger”.

When the sensors come into contact with an object’s surface, the electrons in each square begin to interact with the surface in a different way, which the team was then able to measure.

Each of the sensors is connected to a processor and an organic light-emitting diode (OLED) display, which highlights the type of material being assessed. Indeed, the researchers were able to quantify tactile psychological parameters using the triboelectric effect, which could define a new paradigm in modeling human tactile perception.

Actual and future scenarios

In a real scenario, the processor could be directly integrated into a manufacturing control mechanism. The smart fingers could then perform quality checks and determine if the products are up to manufacturing standards.

Beyond the industrial/manufacturing setting, smart fingers could also be used in prosthetics as robotic limbs with a sense of touch to improve manipulation techniques and manipulation of objects.

The team also aims to introduce other sensors into the system, including pressure, temperature and humidity sensors, to help improve touch simulation.

In the future, artificial intelligence chips will be integrated into smart fingers to make them “smarter” and give them the ability to process data independently of the computer.

Dan Luo, CAS Center for Excellence in Nanoscience, Beijing Institute of Nanoenergy and Nanosystems

References and further reading

Qu, X. and Liu, Z., et al., (2022) Smart finger with artificial tactile perception for material identification based on triboelectric sensing. Scientists progress, [online] 8(31). Available at: https://www.science.org/doi/10.1126/sciadv.abq2521

Disclaimer: The views expressed herein are those of the author expressed privately and do not necessarily represent the views of AZoM.com Limited T/A AZoNetwork, the owner and operator of this website. This disclaimer forms part of the terms of use of this website.

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Trial of Cinpanemab in early Parkinson’s disease https://plamo.info/trial-of-cinpanemab-in-early-parkinsons-disease/ Wed, 03 Aug 2022 21:04:17 +0000 https://plamo.info/trial-of-cinpanemab-in-early-parkinsons-disease/ Summary Background Aggregated α-synuclein plays an important role in the pathogenesis of Parkinson’s disease. Cinpanemab, a human-derived monoclonal antibody that binds to α-synuclein, is being evaluated as a modifying treatment for Parkinson’s disease. Methods Download a PDF of the research summary. In a 52-week, double-blind, multicenter, phase 2 trial, we randomly assigned, in a 2:1:2:2 […]]]>

Summary

Background

Aggregated α-synuclein plays an important role in the pathogenesis of Parkinson’s disease. Cinpanemab, a human-derived monoclonal antibody that binds to α-synuclein, is being evaluated as a modifying treatment for Parkinson’s disease.

Methods

Download a PDF of the research summary.

In a 52-week, double-blind, multicenter, phase 2 trial, we randomly assigned, in a 2:1:2:2 ratio, participants with early-stage Parkinson’s disease to receive intravenous infusions of placebo (control) or cinpanemab at a dose of 250 mg, 1250 mg, or 3500 mg every 4 weeks, followed by a blind extension period of the active treatment dose up to 112 weeks . The primary endpoints were changes from baseline in the Movement Disorder Society-sponsored review of the Unified Parkinson’s Disease Rating Scale (MDS-UPDRS) total score (range 0 to 236, higher scores indicating poorer performance) at weeks 52 and 72 Secondary endpoints included MDS-UPDRS subscale scores and striatal binding assessed on dopamine transporter single-photon emission computed tomography (DaT -SPECT).

Results

Of the 357 participants enrolled, 100 were assigned to the control group, 55 to the cinpanemab 250 mg group, 102 to the 1250 mg group and 100 to the 3500 mg group. The trial was stopped after the week 72 interim analysis due to lack of efficacy. The change at week 52 in the MDS-UPDRS score was 10.8 points in the control group, 10.5 points in the 250 mg group, 11.3 points in the 1250 mg group and 10.9 points in the the 3500 mg group (adjusted mean difference vs control, −0.3 points [95% confidence interval {CI}, −4.9 to 4.3], P=0.90; 0.5 points [95% CI, −3.3 to 4.3], P=0.80; and 0.1 points [95% CI, −3.8 to 4.0], P = 0.97, respectively). The adjusted mean difference at 72 weeks between participants who received cinpanemab for 72 weeks and the pooled group of those who started cinpanemab at 52 weeks was −0.9 points (95% CI, −5.6 to 3.8) for the 250 mg dose, 0.6 points (95% CI, -3.3 to 4.4) for the 1250 mg dose and -0.8 points (95% CI, – 4.6 to 3.0) for the 3500 mg dose. The results for the secondary endpoints were similar to those for the primary endpoints. DaT-SPECT imaging at week 52 showed no difference between the control group and any cinpanemab group. The most common adverse events with cinpanemab were headache, nasopharyngitis and falls.

conclusion

In participants with early-stage Parkinson’s disease, the effects of cinpanemab on clinical measures of disease progression and changes in DaT-SPECT imaging did not differ from those of placebo over a 52-week period . (Funded by Biogen; SPARK ClinicalTrials.gov number, NCT03318523.)

Digital object thumbnailQUICK SUMMARY OF THE VIDEO
Cinpanemab in early Parkinson’s disease
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Machine Learning Aided Metamaterial Based Reconfigurable Antenna for Low Cost Portable Electronic Devices https://plamo.info/machine-learning-aided-metamaterial-based-reconfigurable-antenna-for-low-cost-portable-electronic-devices/ Tue, 19 Jul 2022 18:55:17 +0000 https://plamo.info/machine-learning-aided-metamaterial-based-reconfigurable-antenna-for-low-cost-portable-electronic-devices/ This section briefly describes the need to use regression models during the simulation process and explains how regression models can be used to reduce time and resource requirements by 80% while simulating design efficiency. the antenna. Need for regression methods Researchers use regression analysis to find the value of the dependent parameter(s) using the value(s) […]]]>

This section briefly describes the need to use regression models during the simulation process and explains how regression models can be used to reduce time and resource requirements by 80% while simulating design efficiency. the antenna.

Need for regression methods

Researchers use regression analysis to find the value of the dependent parameter(s) using the value(s) of the independent parameter(s)38,39,40,41. When simulating an antenna design, frequency is an independent parameter, while reflectance value is a dependent parameter. Simulating the experimental design requires a significant amount of time and resources. Increasing the complexity of experimental design requires more time and resources. When simulating the efficiency of an antenna, it must be evaluated for a wide variety of frequency values. As the range of tests expands, the demand for simulation resources also increases. As a result, the cost of modeling and experimentation increases. ML-based regression analysis methodologies can be used to solve this problem by following the following three steps.

Step 1: Simulate the antenna design using a higher step value for the frequency.

2nd step: Train the machine learning-based regression model using simulated data.

Step 3: Predict intermediate frequency reflectance values ​​using the trained regression model.

With an increase in the frequency step size value, simulation time and resource requirements are reduced. R Square score (R2S), Mean Absolute Percentage Error (MAPE), Mean Squared Error (MSE), and Adjusted R-Score Squared (AR2S) are commonly used criteria to quantify the prediction accuracy of the trained regression model. The formulas for calculating these metrics are shown in the equations. (5–8).

$$MSE= frac{1}{N}sum_{i=1}^{N}{({Actual,Target,Value}_{i}-{Predicted,Target,Value}_{ i})}^{2}$$

(5)

$$MAPE=frac{1}{n}sum_{i=1}^{n}leftlfloorfrac{{Actual,Target,Value}_{i}-{Expected,Target ,Value}_{i})}{{Actual,Target,Value}_{i}}rightrfloor *100$$

(6)

$${R}^{2}S= 1- frac{sum_{i=1}^{N}{({Predicted,Target,Value}_{i}-{Actual,Target, Value}_{i})}^{2}}{sum_{i=1}^{N}{({Actual,Target}_{i}- Average, Target,Value )}^{2 }}$$

(seven)

$$A{R}^{2}S= 1-left[frac{left(1-{R}^{2}right)*(N-1)}{N-K-1}right]$$

(8)

Here, “N” is a number of data points used to test the regression model and “K” is a number of independent parameters used to predict the value of the target parameter.

Regression analysis using Supplemental Tree Regression Model (ExTRM)

A binary recursive partitioning algorithm is used to build the regression tree. Each recursive step is used to find a data point in the independent parameter, where dividing the data set into two halves minimizes the root mean square error in the regression analysis. To improve the accuracy of its predictions, the regression tree may need to be pruned or adjusted.

Extremely random tree regression (additional tree)

This algorithm creates a collection of ‘M’ number of unpruned regression trees RT1…RTM. Unlike the regression tree, this technique picks the cutpoint at random and grows all the regression trees using the training dataset. As indicated in Eq. (9), the output of all regression trees is blended using an arithmetic mean.

$$Forecast,Value= sum_{j=1}^{M}{RT}_{j}(x)$$

(9)

Here x is the value of an independent parameter.

Design of Experiment for Reflectance Value Prediction Using ExTRM

The experiments are performed using data obtained by simulating the antenna design presented in Sect. 2. TS-60, TS-70, TS-80 and TS-90 are four test cases (TS) which are used to verify how much simulation time and resource requirements can be reduced using an analysis approach of regression. In the TS-P test case, (100-P)% simulated data points are selected using a uniform random selection strategy to train the ExTRM, while the P % simulated data points remaining are used to quantify the prediction accuracy of the formed ExTRM. The number of data points used to train and quantify the ExTRM during various test scenarios is detailed in Supplementary Table ST2.

Experimental results for prediction using ExTRM

100 regression trees are used to create ExTRMs for experimentation. AR2The S of the ExTRMs obtained for various inner square length values ​​during the TS-80 test case is shown in Fig. 6a.

Figure 6

(a) AR2S of the ExTRMs obtained for values ​​matched with the length of the interior square (LIS) during the test scenario (TS-80) (b) MAPE of the ExTRMs for different LIS values ​​during the test case (TS-80) (vs) AR2S of ExTRM obtained for values ​​matched with LIS during the test scenario (TS-90) (D) MAPE of the ExTRMs for different LIS values ​​during the test scenario (TS-90).

The MAPE of the ExTRMs for various inner square length values ​​during the TS-80 test case is shown using a comparative bar graph in Figure 6b. When ExTRMs are trained using first-degree polynomial (PF) features, an AR2S greater than 0.95 is obtained for all values ​​of interior square length, as shown in Figure 6a. Additionally, the MAPE of the ExTRMs is less than 0.5% for all inner square length values ​​when the model is trained using first-degree PFs, except for the inner square length of 11 mm, as shown in Fig. 6b. It’s about 1.0% in this situation.

Figure 7a–d shows scatterplots of predicted vs. simulated reflectance values ​​for 15 mm inner square length during test scenarios TS-60, TS-70, TS-80, and TS- 90, respectively. Even though only 20% of the simulated data is used to predict the reflectance value for the remaining 80% of frequencies, the ExTRM can predict these values ​​with high accuracy, as shown in Figure 7c. The same cannot be said for the TS-90 test case. Fig. additional. (S3 to S7) show scatter plots for inner square lengths of 10 to 14 mm in uniform 1 nm increments, respectively. As a result, we can conclude that using ExTRM during antenna design simulation for various interior square length values ​​can reduce simulation requirements by 80%.

Picture 7
number 7

Scatterplot of predicted value of reflectance versus simulated value of reflectance for (a) Inner Square Length (LIS) = 15mm during TS-60 (b) LIS = 15 mm during TS-70 (vs) LIS = 15 mm during TS-80 (D) LIS = 15 mm during TS-90 (e) Length of outer square (L0S) = 24 mm during TS-60 (F) L0S = 24 mm during TS-70 (g) L0S = 24 mm during TS-80 (h) L0S = 24 mm during TS-90.

AR2The S of the ExTRMs obtained for various inner square length values ​​during the TS-90 test case is shown in Fig. 6c. The MAPE of the ExTRMs for various inner square length values ​​during the TS-90 test case is shown using a comparative bar graph in Figure 6d. When ExTRMs are trained using first/second/third degree PFs, an AR2An S value greater than 0.9 cannot be obtained for all values ​​of inner square length, as shown in Figure 6c. Moreover, the MAPE of the ExTRM is significantly greater than 1.0% for some values ​​of the length of the inner square, as shown in Fig. 6d. As a result, we can conclude that using ExTRM during antenna design simulation for different inner square length values ​​cannot reduce the simulation requirements by 90%.

AR2The S of the ExTRMs obtained for various outer square length values ​​during the TS-80 test case is shown in Fig. 8a. The MAPE of the ExTRMs for various outer square length values ​​during the TS-80 test case is shown using a comparative bar graph in Figure 8b. When ExTRMs are formed using first-degree PFs, an AR2S greater than 0.99 is obtained for all values ​​of the length of the outer square, as shown in Figure 8a. Moreover, the MAPE of the ExTRM is less than 0.47% for all values ​​of the length of the outer square, as shown in Figure 8b.

Figure 8
figure 8

(a) AR2S of the ExTRMs obtained for values ​​matched with the length of the outer square (LOS) during the test scenario (TS-80) (b) MAPE of the ExTRMs for different values ​​of LOS during the test scenario (TS-80) (vs) AR2S of ExTRM obtained for different values ​​of LOS during the test scenario (TS-90) (b) MAPE of the ExTRMs for different LOS values ​​during the test scenario (TS-90).

Figure 7e–h shows scatter plots of predicted vs. simulated reflectance values ​​for 24 mm outer square length during test scenarios TS-60, TS-70, TS-80, and TS- 90, respectively. Even though only 20% of the simulated data is used to predict the reflectance value for the remaining 80% frequencies, the ExTRM can predict these values ​​with high accuracy, as shown in Figure 7g. The same cannot be said for the TS-90 test case. Fig. additional. (S8–S16) show scatter plots for the remaining lengths of the outer square. As a result, we can conclude that using ExTRM during antenna design simulation for various values ​​of outer square length can reduce simulation requirements by 80%.

AR2The S of the ExTRMs obtained for various outer square length values ​​during the TS-90 test case is shown in Fig. 8c. The MAPE of the ExTRMs for various outer square length values ​​during the TS-90 test case is shown using a comparative bar graph in Figure 8d. When ExTRMs are formed using second-degree PFs, an AR2S greater than 0.94 can be obtained for all values ​​of interior square length, as shown in Fig. 8c. However, the MAPE of the ExTRM is greater than 1.0% for some values ​​of the outer square length, as shown in Fig. 8d. Therefore, we can conclude that using ExTRM during antenna design simulation for different values ​​of outer square length cannot reduce the simulation requirements by 90%.

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Project Drawdown’s latest update adds 11 new ways to stop global warming https://plamo.info/project-drawdowns-latest-update-adds-11-new-ways-to-stop-global-warming/ Mon, 04 Jul 2022 19:44:03 +0000 https://plamo.info/project-drawdowns-latest-update-adds-11-new-ways-to-stop-global-warming/

It was 2017 when Project Drawdown first published its comprehensive guide to reducing greenhouse gas emissions so that average global temperatures don’t rise enough to make our beautiful planet uninhabitable for humans. 3 years later, Project drawupdated its initial plan to incorporate lessons learned since the publication of its first report. The Last update from Project draw group adds 11 new ways to responsibly address the global climate crisis.

The power of planning

A popular expression goes, “If you don’t plan, you have a plan to fail.” In other words, if you want to get somewhere, you need a guide to help you get where you want to go. It all starts with setting a goal. When we go on vacation, we don’t just get in the car and drive around aimlessly. We first choose a destination, such as Poughkeepsie, Peoria or Pocatello. That’s the point. Then we come up with a plan to achieve the goal – what route to take, what to pack and where to stay along the way. That’s the plan. With a goal and a plan, anything is possible.

Project draw has one goal: to prevent the Earth from getting so hot that humans can no longer survive. He has also developed detailed plans to achieve this goal in a practical and affordable way. He defines “drawdown” as the future time when levels of greenhouse gases in the atmosphere stop rising and begin to steadily decline, thereby halting catastrophic climate change. Its mission is to provide humanity with the solutions needed to achieve drawdown quickly, safely, efficiently and equitably.

“All solutions are based on a thorough analysis of the scientific literature and sophisticated modeling and share six key characteristics that set them apart from other sets of climate change mitigation strategies,” says Project Drawdown. “They 1) are currently available, 2) are gaining momentum, 3) are financially viable, 4) are capable of reducing greenhouse gas concentrations in the Earth’s atmosphere, 5) have a net positive impact, and 6) are quantifiable under different scenarios.”

11 new solutions

Here are the 11 new solutions proposed by the Project draw crew.

  • Algae cultivation — Seaweed farming is one of the most sustainable types of aquaculture. The expansion of algae cultivation improves carbon sequestration and stimulates the production of biomass that can be used for biofuels, bioplastics, livestock feed and human consumption.
  • Protection and restoration of macroalgae — Macroalgal forests are among the most productive ecosystems on the planet. Protecting and restoring these habitats improves carbon sequestration in the deep sea.
  • Improved fisheries — Improving fisheries involves reforming and improving the management of wild fisheries to reduce excessive effort, overcapitalization and overfishing. This can reduce fuel consumption and replenish fish populations.
  • Improved aquaculture — Aquaculture is one of the fastest growing animal feed sectors. Since some aquaculture systems are very energy intensive, ensuring that some on-site energy consumption is based on renewable resources would reduce greenhouse gas emissions.
  • Seabed protection — Large amounts of carbon stored in seabed sediments may be released by bottom trawling. Banning bottom trawling and creating marine protected areas can protect this important carbon sink.
  • Improving livestock feed — Optimizing livestock feeding strategies can reduce methane emissions produced in the digestive system of ruminants. Nutrient-enriched diets of high-quality forages, additives and supplements aim to improve animal health and productivity.
  • Improved manure management — Livestock manure produces methane, a powerful greenhouse gas. Advanced manure management technologies and practices can reduce the negative climate impact of livestock production.
  • Management of methane leaks — Methane, a potent greenhouse gas, is emitted during the production and transportation of oil and natural gas. Managing methane emissions can reduce greenhouse gases in the atmosphere.
  • Recycled metals — Metals are extracted from non-renewable ores. Recycled metals capitalize on materials already mined, allowing goods to be produced more efficiently, reducing the need to extract new resources, and reducing energy and water consumption.
  • Recycled plastics — Recycling plastics requires less energy than producing new materials, saves landfill space, reduces environmental pollution and decreases demand for fossil fuel-based raw materials.
  • Reduced plastics — The production of plastic has increased enormously over the past century, mainly for short-term use. Reducing the amount of plastic used in non-durable goods can significantly reduce greenhouse gas emissions and plastic waste.

Expense Vs. Investment

Keeping the Earth habitable will cost a lot of money. But every dollar spent is not wasted, as a former orange-skinned president liked to claim. What if a dollar spent today earned $3 tomorrow? It’s called an investment – a concept foreign to Republicans. In their world, the billions spent building the interstate highway systems was a classic example of Big Government wasting taxpayers’ money. In fact, these highways have led to a burst of economic activity that has helped make America’s economy the envy of the world.

Building factories costs a lot of money, but they create jobs and wealth far beyond their initial investment. What if spending money today could not only slow global warming, but also create more economic opportunity for millions of people? What if expenses incurred to save our planet could be recouped many times over? The Project draw the team says it’s not only possible, but virtually guaranteed.

His analysis is divided into two scenarios. The first outlines plans to prevent average global temperatures from rising more than 2°C above pre-industrial levels. The second focuses on the more difficult goal of keeping global warming below 1.5°C. Here are the conclusions of the last report.

  • An initial investment of $15.6 trillion (Scenario 1) would avoid or sequester more than 1,000 gigatonnes of greenhouse gases equivalent carbon dioxide between 2020 and 2050 and save nearly $98 trillion in total operating costs over the lifetime of the solution.
  • Scaling up investment to $23.6 trillion (Scenario 2) would avoid or sequester over 1,600 gigatons of gas and save over $140 trillion in lifetime costs.

Economists like to talk about “multiplier effects”. If a dollar invested creates 3 dollars in return, the multiplier effect is 3. If that same dollar brings in 10 dollars, the multiplier effect is 10. In the first scenario proposed by Project Drawdown, the multiplier effect is greater than 6. In the second scenario, it’s just under 6. If someone offered you a chance to increase your net worth by a factor of 6, most people would be thrilled. Couple that rate of return with the ability to keep Earth habitable for future humans and we’ve structured a win-win situation.

Takeaway meals

“In summary, we have confirmed that practices and technologies implemented to reduce greenhouse gas emissions will more than pay off in lifetime savings,” says Project Drawdown’s latest report. “In addition, many solutions have additional benefits for reducing poverty, increasing equity, and protecting endangered animals and ecosystems. Solving the climate crisis is therefore both a measure that saves lives and saves money for future generations.

It is the power to set a goal and make realistic plans to achieve that goal. We desperately need leaders who embrace such thoughtful and practical solutions. Wherever you are and whatever you do, make it a point to vote your conscience this year and every year. Remember that if the people lead, their leaders will follow.

Be sure to check near 100 proposals The Drawdown project aims to tame the rise in global average temperatures. There’s something for everyone, and every solution is backed by detailed, in-depth research. This is the information you need to make rational and informed decisions when choosing your political leaders.

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]]> Introducing the Microsoft Climate Research Initiative https://plamo.info/introducing-the-microsoft-climate-research-initiative/ Wed, 29 Jun 2022 16:00:00 +0000 https://plamo.info/introducing-the-microsoft-climate-research-initiative/ Addressing and mitigating the effects of climate change requires a collective effort, leveraging our strengths in industry, government, academia and civil society. As we continue to explore the role of technology in advancing the art of the possible, we are launching the Microsoft Climate Research Initiative (MCRI). This community of multidisciplinary researchers works together to […]]]>

Addressing and mitigating the effects of climate change requires a collective effort, leveraging our strengths in industry, government, academia and civil society. As we continue to explore the role of technology in advancing the art of the possible, we are launching the Microsoft Climate Research Initiative (MCRI). This community of multidisciplinary researchers works together to accelerate cutting-edge research and transformative innovation in climate science and technology.

MCRI enables us to bring Microsoft’s research skills and computational capabilities to deep and ongoing collaboration with domain experts. For the launch of this initiative, we are focusing on three critical areas of climate research where advances in computing can drive key science transformations: overcoming constraints to decarbonization, reducing uncertainties in carbon accounting, and assessing risks. climate in more detail.

Through these collaborative research projects, we hope to develop and maintain a highly engaged research ecosystem comprising a diversity of perspectives. Researchers will offer cross-disciplinary and diverse expertise, particularly in areas beyond traditional computing, such as environmental science, chemistry, and various engineering disciplines. All results of this initiative should be made public and freely accessible to spur even broader research and progress on these important climate issues.

“As researchers, we are excited to work together on projects specifically selected for their potential impact on global climate challenges. With the compute capabilities of Microsoft and the domain expertise of our people, our complementary strengths can accelerate progress in incredible ways.

– Karin Strauss, Microsoft

Microsoft researchers will work with collaborators around the world to co-investigate priority climate-related topics and bring innovative, world-class research to influential journals and venues.

First phase collaborations

Carbon accounting

Real-time monitoring of carbon control progress from CO2 and air pollutant observations with a physically informed transformer-based neural network

Jia Xing, Tsinghua University; Siwei Li, Wuhan University; Shuxin Zheng, Chang Liu, Shun Zheng, and Wei Cao, Microsoft

Understanding the evolution of CO2 emissions from CO measurement2 concentrations such as those produced by satellites is very useful for monitoring the progress of carbon reduction actions in real time. Current CO2 observations are relatively limited: methods based on numerical models have very low computational efficiency. The proposed study aims to develop a novel method that combines atmospheric numerical modeling and machine learning to infer CO2 emitted by satellite observations and data from ground surveillance sensors.

AI-powered Near Real-Time Global Carbon Budget (ANGCB)

Zhu Liu, Tsinghua University; Biqing Zhu and Philippe Ciais, LSCE; Steven J. Davis, UC Irvine; Wei Cao and Jiang Bian, Microsoft

Mitigation of climate change will depend on a carbon emissions trajectory that successfully achieves carbon neutrality by 2050. To this end, an assessment of the global carbon budget is essential. The AI-based, near real-time ANGCB (Global Carbon Budget) project aims to provide the world’s first carbon budget assessment based on artificial intelligence (AI) and other data science technologies.

Carbon Reduction and Removal

Computational discovery of new metal-organic frameworks for carbon capture

Jeffrey Long, University of Berkeley; Xiang Fu, Jake Smith, Bichlien Nguyen, Karin Strauss, Tian Xie, Daniel Zuegner and Chi Chen, Microsoft

Eliminate CO2 environment should be an integral part of keeping the temperature increase below 1.5°C. However, today it is an inefficient and expensive business. This project will apply generative machine learning to the design of novel metal-organic frameworks (MOFs) to optimize low-cost CO removal.2 air and other dilute gas streams.

An assessment of liquid metal catalyzed CO2 Reduction

Michael D. Dickey, State of North Carolina; Kourosh Kalantar-Zadeh, University of New South Wales; Kali Frost, Bichlien Nguyen, Karin Strauss, and Jake Smith, Microsoft

CO2 The reduction process can be used to convert captured carbon into a storable form as well as to manufacture sustainable fuels and materials with lower environmental impacts. This project will evaluate liquid metal-based reduction processes, identifying benefits, pinch points and opportunities for improvement needed to achieve industry-relevant scales. It will lay the groundwork for improving catalysts and addressing scaling bottlenecks.

Computational design and characterization of organic electrolytes for flow battery and carbon capture applications

David Kwabi, Anne McNeil and Bryan Goldsmith, University of Michigan; Bichlien Nguyen, Karin Strauss, Jake Smith, Ziheng Lu, Yingce Xia and Kali Frost, Microsoft

Energy storage is essential to enable 100% zero-carbon electricity generation. This work will use generative machine learning models and quantum mechanical modeling to drive the discovery and optimization of a new class of organic molecules for energy-efficient electrochemical energy storage and carbon capture.

Prediction of the properties of recyclable polymers

Aniruddh Vashisth, University of Washington; Bichlien Nguyen, Karin Strauss, Jake Smith, Kali Frost, Shuxin Zheng and Ziheng Lu, Microsoft

Despite encouraging progress in recycling, many plastic polymers often end up being single-use materials. The plastics that make up printed circuit boards (PCBs), ubiquitous in all modern devices, are among the most difficult to recycle. Vitrimers, a new class of polymers that can be recycled multiple times without significant change in material properties, present a promising alternative. This project will take advantage of advances in machine learning to select vitrimer formulations that withstand the demands imposed by their use in PCBs.

Accelerated discovery of green cement materials

Eleftheria Roumeli, University of Washington; Kristen Severson, Yuan-Jyue Chen, Bichlien Nguyen and Jake Smith, Microsoft

The concrete industry is a major contributor to greenhouse gas emissions, the majority of which can be attributed to cement. The discovery of alternative cements is a promising way to reduce the environmental impacts of industry. This project will use machine learning methods to accelerate the optimization of the mechanical properties of “green” cements that meet application quality constraints while minimizing the carbon footprint.

Environmental resilience

Causal inference to understand the impact of humanitarian interventions on food security in Africa

Gustau Camps-Valls, University of Valencia; Ted Shepherd, University of Reading; Alberto Arribas Herranz, Emre Kiciman and Lester Mackey, Microsoft

The Causal4Africa project will study the problem of food security in Africa from a new perspective of causal inference. The project will illustrate the utility of causal discovery and effect estimation from observational data through intervention analysis. Ambitiously, it will enhance the usefulness of causal ML approaches for climate risk assessment by enabling the interpretation and assessment of the likelihood and potential consequences of specific interventions.

Improving sub-seasonal forecasts with machine learning

Judah Cohen, Verisk; Dara Entekhabi and Sonja Totz, MIT; Lester Mackey, Alberto Arribas Herranz and Bora Ozaltun, Microsoft

Water and fire managers rely on subseasonal forecasts two to six weeks in advance to allocate water, manage wildfires, and prepare for droughts and other extreme weather events. However, skillful predictions for the sub-seasonal pattern are lacking due to a complex reliance on local weather patterns, global climate variables, and the chaotic nature of weather patterns. To address this need, this project will use machine learning to adaptively correct biases in traditional physics-based forecasts and adaptively combine forecasts from disparate models.


Get progress updates and new resources to accelerate sustainability science research >

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