#ai in particle characterization

[mindblowingscience]

A McGill-led research team has developed the first real-time, on-site technology capable of detecting and deciphering nanoplastics from all other particles in water, a capacity akin to being able to find a needle in a haystack within milliseconds. The work, "Nanoplastics in water: Artificial intelligence-assisted 4D physicochemical characterization and rapid in situ detection," was published in Environmental Science & Technology. Microplastic pieces are between 1 micrometer and 5 millimeters, roughly equivalent to a grain of rice. Nanoplastics are far tinier—a single nanometer is just 0.000001 millimeters. For comparison, a human hair is approximately 80,000–100,000 nanometers wide.

Continue Reading.

[spacetimewithstuartgary]

New diagnostic tool will help LIGO hunt gravitational waves

Machine learning tool developed by UCR researchers will help answer fundamental questions about the universe.

Finding patterns and reducing noise in large, complex datasets generated by the gravitational wave-detecting LIGO facility just got easier, thanks to the work of scientists at the University of California, Riverside. 

The UCR researchers presented a paper at a recent IEEE big-data workshop, demonstrating a new, unsupervised machine learning approach to find new patterns in the auxiliary channel data of the Laser Interferometer Gravitational-Wave Observatory, or LIGO. The technology is also potentially applicable to large scale particle accelerator experiments and large complex industrial systems.

LIGO is a facility that detects gravitational waves — transient disturbances in the fabric of spacetime itself, generated by the acceleration of massive bodies. It was the first to detect such waves from merging black holes, confirming a key part of Einstein’s Theory of Relativity. LIGO has two widely-separated 4-km-long interferometers — in Hanford, Washington, and Livingston, Louisiana — that work together to detect gravitational waves by employing high-power laser beams. The discoveries these detectors make offer a new way to observe the universe and address questions about the nature of black holes, cosmology, and the densest states of matter in the universe.

Each of the two LIGO detectors records thousands of data streams, or channels, which make up the output of environmental sensors located at the detector sites. 

“The machine learning approach we developed in close collaboration with LIGO commissioners and stakeholders identifies patterns in data entirely on its own,” said Jonathan Richardson, an assistant professor of physics and astronomy who leads the UCR LIGO group. “We find that it recovers the environmental ‘states’ known to the operators at the LIGO detector sites extremely well, with no human input at all. This opens the door to a powerful new experimental tool we can use to help localize noise couplings and directly guide future improvements to the detectors.”

Richardson explained that the LIGO detectors are extremely sensitive to any type of external disturbance. Ground motion and any type of vibrational motion — from the wind to ocean waves striking the coast of Greenland or the Pacific — can affect the sensitivity of the experiment and the data quality, resulting in “glitches” or periods of increased noise bursts, he said. 

“Monitoring the environmental conditions is continuously done at the sites,” he said. “LIGO has more than 100,000 auxiliary channels with seismometers and accelerometers sensing the environment where the interferometers are located. The tool we developed can identify different environmental states of interest, such as earthquakes, microseisms, and anthropogenic noise, across a number of carefully selected and curated sensing channels.”

Vagelis Papalexakis, an associate professor of computer science and engineering who holds the Ross Family Chair in Computer Science, presented the team’s paper, titled “Multivariate Time Series Clustering for Environmental State Characterization of Ground-Based Gravitational-Wave Detectors,” at the IEEE's 5th International Workshop on Big Data & AI Tools, Models, and Use Cases for Innovative Scientific Discovery that took place last month in Washington, D.C.

“The way our machine learning approach works is that we take a model tasked with identifying patterns in a dataset and we let the model find patterns on its own,” Papalexakis said. “The tool was able to identify the same patterns that very closely correspond to the physically meaningful environmental states that are already known to human operators and commissioners at the LIGO sites.”

Papalexakis added that the team had worked with the LIGO Scientific Collaboration to secure the release of a very large dataset that pertains to the analysis reported in the research paper. This data release allows the research community to not only validate the team’s results but also develop new algorithms that seek to identify patterns in the data.

“We have identified a fascinating link between external environmental noise and the presence of certain types of glitches that corrupt the quality of the data,” Papalexakis said. “This discovery has the potential to help eliminate or prevent the occurrence of such noise.”

The team organized and worked through all the LIGO channels for about a year. Richardson noted that the data release was a major undertaking. 

“Our team spearheaded this release on behalf of the whole LIGO Scientific Collaboration, which has about 3,200 members,” he said. “This is the first of these particular types of datasets and we think it’s going to have a large impact in the machine learning and the computer science community.”

Richardson explained that the tool the team developed can take information from signals from numerous heterogeneous sensors that are measuring different disturbances around the LIGO sites. The tool can distill the information into a single state, he said, that can then be used to search for time series associations of when noise problems occurred in the LIGO detectors and correlate them with the sites’ environmental states at those times.

“If you can identify the patterns, you can make physical changes to the detector — replace components, for example,” he said. “The hope is that our tool can shed light on physical noise coupling pathways that allow for actionable experimental changes to be made to the LIGO detectors. Our long-term goal is for this tool to be used to detect new associations and new forms of environmental states associated with unknown noise problems in the interferometers.”

Pooyan Goodarzi, a doctoral student working with Richardson and a coauthor on the paper, emphasized the importance of releasing the dataset publicly. 

“Typically, such data tend to be proprietary,” he said. “We managed, nonetheless, to release a large-scale dataset that we hope results in more interdisciplinary research in data science and machine learning.”

The team’s research was supported by a grant from the National Science Foundation awarded through a special program, Advancing Discovery with AI-Powered Tools, focused on applying artificial intelligence/machine learning to address problems in the physical sciences. 

[analystviewmarketinsights800]

EUV Pellicle Market : Size, Trends, and Growth Analysis 2032

EUV Pellicle Market: Protecting the Future of Semiconductor Lithography

The EUV Pellicle Market size was valued at US$ 590.43 Million in 2024 and is forecasted to grow at a robust CAGR of 14.90% from 2025 to 2032. EUV pellicles are becoming increasingly critical in the semiconductor manufacturing process as the industry pushes the boundaries of miniaturization and chip performance.

What is an EUV Pellicle?

An Extreme Ultraviolet (EUV) pellicle is an ultra-thin, highly transparent membrane film designed to protect photomasks during EUV lithography. Photomasks carry the intricate circuit patterns that need to be etched onto semiconductor wafers. Because EUV lithography uses light at a wavelength of 13.5 nm—much shorter than traditional lithography wavelengths—the precision required is extreme, and even microscopic particles can cause significant defects in the wafer patterns.

The EUV pellicle acts as a physical barrier, preventing dust, contaminants, and particles from settling on the photomask surface. It allows EUV light to pass through with minimal absorption or distortion while ensuring the photomask remains uncontaminated, thereby enhancing yield rates and reducing costly reworks.

Market Drivers

1. Shrinking Node Sizes and Advanced Semiconductor Fabrication As semiconductor manufacturers push towards smaller technology nodes (sub-7 nm and below), the precision requirements for lithography increase exponentially. EUV lithography is pivotal to these advancements, and the demand for reliable EUV pellicles to protect photomasks grows correspondingly.

2. Increasing Demand for High-Performance Electronics The rising adoption of AI, IoT, 5G, and automotive electronics necessitates chips with higher transistor densities and superior performance. This trend drives investments in advanced lithography solutions where EUV pellicles are indispensable.

3. Growing Semiconductor Industry Investment Significant capital investments by semiconductor fabrication plants (fabs) in the U.S., South Korea, Taiwan, and China are accelerating the adoption of EUV lithography equipment. Consequently, the demand for supporting components like pellicles is on the rise.

4. Need for Yield Improvement and Cost Reduction Photomask defects due to particle contamination can cause substantial production losses. EUV pellicles improve yields by minimizing contamination risks, helping fabs reduce scrap rates and overall manufacturing costs.

Technical Challenges and Innovations

Material Selection and Durability EUV pellicles must be ultra-thin yet mechanically robust, withstand high EUV light intensities without degradation, and maintain thermal and chemical stability during lithography. The choice of pellicle materials such as silicon-based membranes or specialized polymers is critical to achieving these performance metrics.

Transparency and Low Absorption Because EUV light has high energy, even slight absorption or reflection by the pellicle can affect lithography quality. Innovations in material engineering aim to enhance pellicle transparency above 90%, reducing light loss and pattern distortion.

Thermal Management EUV lithography exposes pellicles to high thermal loads. Effective heat dissipation techniques and materials with high thermal stability are under continuous development to prevent pellicle damage and maintain performance.

Market Segmentation

By Product Type:

Silicon-based Pellicles

Polymer-based Pellicles

Composite Pellicles

By End-Use:

Semiconductor Foundries

Chip Manufacturers

Research and Development Institutes

By Region:

Asia-Pacific

North America

Europe

Rest of the World

Asia-Pacific dominates due to the concentration of semiconductor manufacturing hubs in countries like Taiwan, South Korea, and China. North America and Europe maintain significant shares driven by technology innovation and fab expansions.

Competitive Landscape

The EUV pellicle market is characterized by a few leading players with advanced technological capabilities and strong R&D investments:

ASML Holding N.V. As the pioneer of EUV lithography systems, ASML plays a critical role in the pellicle market through strategic partnerships and in-house development. Its integration of pellicles in EUV scanners enhances lithography precision.

Mitsui Chemicals, Inc. Known for its innovation in high-performance materials, Mitsui Chemicals produces cutting-edge pellicle films designed for enhanced durability and transparency in EUV applications.

Shin-Etsu Chemical Co., Ltd. Shin-Etsu specializes in advanced semiconductor materials and offers pellicle products engineered for high thermal stability and low EUV absorption.

FUJIFILM Holdings Corporation With a strong presence in thin-film technology, FUJIFILM manufactures pellicles with superior mechanical strength and chemical resistance.

Toppan Inc. Toppan’s expertise in photomask production complements its development of pellicle solutions aimed at minimizing contamination and improving semiconductor yield.

SÜSS MicroTec SE A key player in lithography equipment and photomask technologies, SÜSS MicroTec provides specialized pellicle handling and integration systems.

Industry Outlook

The EUV pellicle market is set to benefit from the global semiconductor industry's unrelenting focus on miniaturization and yield optimization. As fabs increase EUV scanner deployment, demand for pellicles will scale accordingly. Advances in materials science and thermal management will continue to unlock pellicle performance improvements, expanding their adoption.

Moreover, government initiatives worldwide to boost semiconductor self-reliance and chip manufacturing capacity are expected to create new growth opportunities for pellicle manufacturers. Collaborations between pellicle suppliers, lithography system makers, and semiconductor manufacturers are fostering innovation cycles that will push EUV lithography capabilities further.

Browse more Report:

Biostimulants Market

Multilayer Printed Circuit Board Market

Wafer Cases Market

Multimedia Chipsets Market

IoT Microcontroller Market

[drmikewatts]

Soft Computing, Volume 29, Issue 7, April 2025

1) Operators on complemented lattices

Author(s): Ivan Chajda, Helmut Länger

Pages: 3115 - 3123

2) Quasi-L-algebras

Author(s): Omid Zahiri, Xiao Long Xin

Pages: 3125 - 3137

3) Concept lattices of Ci-connected contexts and the characterization theorem

Author(s): Zhenhua Jia, Lankun Guo, Qingguo Li

Pages: 3139 - 3149

4) Numerical treatment of blood nanofluid flow in micro-vessels considering inclined magnetic field, hall and radiation effects

Author(s): M. Yasin, S. Hina, R. Naz

Pages: 3151 - 3164

5) A scalable method for extracting features using a complex network from SNP sequences and clustering using the scalable Max of Min algorithm

Author(s): Achint Kumar Kansal, Aruna Tiwari, Preeti Jha

Pages: 3165 - 3188

6) The influence of food bloggers toward consumer’s attitude in restaurant selection: a multi-objective metaheuristic approach

Author(s): Harinandan Tunga, Surjendu Pal, Romualdas Bausys

Pages: 3189 - 3215

7) Optimization of the rectangle area inside a concave polygon using PSO and Tabu Search

Author(s): Gautam Siddharth Kashyap, Karan Malik, Alexander E. I. Brownlee

Pages: 3217 - 3239

8) Adaptive iterated local search algorithm for dynamic patient admission scheduling problems

Author(s): Ayad Turky, Nasser R. Sabar, Panos Liatsis

Pages: 3241 - 3251

9) A bi-level programming model for optimal EV charging scheduling and operation in residential communities

Author(s): Gang Zhu, Yan Gao, Hao Sun

Pages: 3253 - 3272

10) A hybrid of particle swarm optimization and fuzzy system for modeling direct current microgrids to improve stability

Author(s): Hoda Naderi, Neda Ghaderi, Mohammad Abedini

Pages: 3273 - 3288

11) Performance and managerial ability analysis in banking sector: a fuzzy data envelopment analysis approach

Author(s): Alireza Amirteimoori, Tofigh Allahviranloo

Pages: 3289 - 3305

12) Enhancing coordinated target tracking: innovative particle filters with meta-heuristic integration and advanced model validation

Author(s): Nitish Das, Nilima Kulkarni

Pages: 3307 - 3338

13) Pyranet: a novel architectural approach to reduce the effect of unbalanced classes and analysis on leukemia dataset

Author(s): Nikhil Sharma, Rajanbir Singh Ghumaan, K. V. Arya

Pages: 3339 - 3347

14) FTBAC: fuzzy trust based access control for healthcare cross-domain environment

Author(s): Sujoy Roy, Alok Kumar, Udai Pratap Rao

Pages: 3349 - 3366

15) Home energy system: optimal design via risk-averse stochastic programming

Author(s): Patrizia Beraldi, Antonio Violi, Gianluca Carrozzino

Pages: 3367 - 3381

16) Single-stage multi-objective optimization for robust QFT controller and prefilter synthesis in process control systems

Author(s): Nitish Katal, Shiv Narayan

Pages: 3383 - 3414

17) A comparative performance of different Type-1 tournament based metaheuristic algorithms in solving engineering beam design optimization problems and structural engineering design problems

Author(s): Goutam Mandal, Nirmal Kumar, Asoke Kumar Bhunia

Pages: 3415 - 3442

18) Ligand-based and structure-based approaches for the identification of potential SARS-CoV-2 3CLpro inhibitors

Author(s): Achouak Madani, Othmane Benkortbi, Naomie Salim

Pages: 3443 - 3468

19) GWO based energy-efficient workflow scheduling for heterogeneous computing systems

Author(s): Karishma, Harendra Kumar

Pages: 3469 - 3508

20) Solving convex multi-objective optimization problems using a projection neural network framework

Author(s): Mohammadreza Jahangiri, Alireza Nazemi

Pages: 3509 - 3532

21) Organising unstructured data using Double Net Self-Organising Map (DNSOM) model

Author(s): Cheng Chun You, Seng Poh Lim, Seng Chee Lim

Pages: 3533 - 3554

22) Supply chain performance prediction model for make-to-order system using artificial neural network

Author(s): Sujan Piya, Mahmoud Mokhtar

Pages: 3555 - 3569

23) Shadow learner system: implementation of CNN with explainable AI model for bone radiology image classification

Author(s): Yaoyang Wu, Simon Fong, Liansheng Liu

Pages: 3571 - 3588

24) A cross-scale Gaussian wavelet model with decomposition cross-consistency for TAO multifocal region semi-supervised segmentation

Author(s): Haipeng Zhu, Hong He, Xuefei Song

Pages: 3589 - 3602

25) A multi-scale deep neural networks for early fault diagnosis in rolling ball bearings

Author(s): Rajeev Kumar, R. S. Anand

Pages: 3603 - 36

26) Impact of artificial intelligence and blockchain on supply chain resilience under influence of change management

Author(s): Eduard Gabriel Ceptureanu, Giovanna Ferraro, Alina Matei

Pages: 3617 - 3625

27) Enhanced Protein Complex Detection Using Square Clustering Coefficient

Author(s): Parimah Mirzaee, Nasrollah Moghaddam Charkari, Mehdy Roayaei

Pages: 3627 - 3640

28) Forecasting leading economic indicators in the US from financial news using multi-task learning

Author(s): Josh Jia-Ching Ying, Chia-Chen Liu, Ji Zhang

Pages: 3641 - 3657

29) Reparable threshold Paillier encryption scheme for federated learning

Author(s): Yi Zhang, Kun Tian, Qun Xu

Pages: 3659 - 3664

30) Multicombinators as observable presheaves

Author(s): Rocco Gangle, Fernando Tohmé, Gianluca Caterina

Pages: 3665 - 3673

31) The force of few: boosting deviance detection in data scarcity scenarios through self-supervised learning and pattern-based encoding

Author(s): Francesco Folino, Gianluigi Folino, Luigi Pontieri

Pages: 3675 - 3690

32) 0–1 Linear programming under interval uncertainty

Author(s): Elif Garajová, Milan Hladík, Miroslav Rada

Pages: 3691 - 3704

33) Absolute value equations with interval uncertainty

Author(s): Milan Hladík, Lenka Ptáčková

Pages: 3705 - 3718

34) A novel multifactor type-2 fuzzy time series model based on improved fuzzy C-means algorithm and justifiable granularity for stock index forecasting

Author(s): Zengtai Gong, Jindong Feng

Pages: 3719 - 3732

35) Adaptive hyperparameter selection in kernel-based partition of unity methods by global optimization techniques

Author(s): Roberto Cavoretto, Alessandra De Rossi, Yaroslav D. Sergeyev

Pages: 3733 - 3748

[ferrotitanium2]

Latest Trends in Ferro Titanium Alloys and Lumps as Seen by Global Ferro Alloy Suppliers!

The steel and metallurgical industries continue to evolve at a rapid pace, and the materials that support them must keep up. Among these critical inputs, Ferro Titanium Alloys have emerged as essential additives in the production of high-quality steel. With rising global standards, new environmental regulations, and advanced production technologies, these alloys are seeing increased demand — especially in specialized steelmaking segments.

This article explores the latest trends in the use and production of ferro titanium materials, based on industry strategies and global market developments.

Customized Alloy Compositions for Precision Applications

Today’s steelmakers demand more than just bulk materials — they require precision and consistency. Ferro titanium alloys are being customized to match specific industrial applications, especially in high-performance sectors like automotive, shipbuilding, defense, and aerospace.

Customization trends include:

Specific titanium content (ranging from 10% to 30%) depending on the desired steel characteristics.

Low residual impurities, especially aluminium, silicon, and phosphorus.

Tight control of particle size for uniform distribution during the steelmaking process.

This shift toward tailored compositions has pushed producers to invest in advanced refining and blending facilities, improving both product consistency and customer satisfaction.

Rising Demand for Clean and High-Purity Inputs

In modern foundries and electric arc furnaces, the demand for Ferro Titanium Lumps with consistent quality and minimal contamination is growing steadily. These lumps are often preferred in processes like vacuum induction melting (VIM), where impurities must be minimized to maintain steel integrity.

High-purity lumps are now being characterized by:

Titanium content typically around 70–75%

Minimal carbon, sulphur, and oxygen

Carefully controlled size fractions (10–50 mm or as per client need)

Producers are adopting pre-screening, mechanical sizing, and vacuum packing techniques to ensure these quality standards are met. This level of refinement not only supports better metallurgical performance but also reduces waste and enhances energy efficiency.

Sustainability and Recycling of Raw Materials

Environmental responsibility has become a key driver across the metallurgical value chain. To meet rising sustainability expectations, many Ferro Alloy Suppliers are shifting toward greener production methods, including the use of recycled titanium scrap.

The use of secondary titanium sources provides:

Lower production costs

Reduced carbon emissions

Support for circular economy initiatives

Moreover, buyers are increasingly requesting documentation on carbon footprints, environmental certifications, and origin tracking — further pushing suppliers to build eco-friendly systems into their operations.

Digital Transformation Across the Supply Chain

As global competition increases, efficiency and transparency are more important than ever. Suppliers are turning to digital tools to streamline operations, enhance communication, and deliver better customer service.

Key digital trends include:

Live shipment tracking for better planning

Digital mill test certificates accessible through cloud portals

AI-based demand forecasting to manage inventory and raw material sourcing

Integrated ERP systems to coordinate production, sales, and logistics

This digital shift not only shortens lead times but also builds trust with buyers who value data-driven decision-making and real-time visibility.

Global Expansion and New Market Opportunities

In recent years, emerging economies in Asia, the Middle East, and Eastern Europe have become major consumers of titanium-based ferroalloys. Countries like India, Vietnam, and the UAE are ramping up steel production and infrastructure investments, leading to greater demand for high-performance alloys.

To serve these growing markets efficiently, suppliers are:

Establishing regional warehouses and processing hubs

Partnering with local distributors

Adapting products to region-specific requirements, such as packaging standards, delivery terms, and regulatory compliance

By providing localized service, this expansion approach not only expedites delivery times but also enhances the relationship between the provider and the client.

Standardization and Certifications

To support global competitiveness and client trust, standardization is becoming a must. Producers of ferro titanium materials are increasingly aligning their operations with international norms such as:

ISO 9001 (quality management)

REACH and RoHS (compliance for EU markets)

EN and ASTM specifications for alloy grading and composition

This focus on certified production helps ensure reliability, improves export capabilities, and opens doors to collaboration with multinational steelmakers.

Conclusion

The market for titanium-based additives in steel production is experiencing significant transformation, fueled by innovation, sustainability goals, and the need for precision. Suppliers today are stepping beyond traditional roles, becoming strategic partners that offer customized solutions to meet the evolving demands of modern steelmakers.

As the world moves toward cleaner, more efficient, and more reliable steel production, keeping pace with these trends is essential. Whether you're a manufacturer, foundry engineer, or procurement specialist, understanding the evolving ferro titanium landscape can give you a competitive edge in sourcing, performance, and cost-efficiency.

#FerroTitaniumAlloys, #FerroTitaniumLumps, #FerroAlloySuppliers,

[hagooooorr]

تنظيف خزانات وقود السفن

تنظيف خزانات وقود السفن

Crude Oil Storage Tank Cleaning: The Ultimate Technical Encyclopedia

I. Advanced Sludge Characterization & Analysis

1.1 Molecular Composition Profiling

High-Resolution Mass Spectrometry (HRMS)

Identifies >5,000 unique compounds in sludge

Key markers:

C30 hopanes (biodegradation indicators)

DBE 12 (highly condensed aromatics)

3D Micro-CT Scanning

Resolution: 5μm voxel size

Reveals pore structure and solids distribution

1.2 Rheological Behavior Modeling

Modified Herschel-Bulkley with Thixotropy

math

\tau = [\tau_y + K\dot{\gamma}^n] × (1 + λe^{-t/θ})

Where:

λ = 0.7 (thixotropic index)

θ = 120s (recovery time constant)

II. Cutting-Edge Cleaning Technologies

2.1 Autonomous Robotic Systems

Next-Gen Specifications:

Model    Pressure (bar)     Flow (L/min) AI Features API Class

CleanBot-X12      500 300 Real-time viscosity adjustment   653 IV

SludgeTerminator Pro 450 280 Self-learning path optimization       650 VI

2.2 Plasma Arc Cleaning 2.0

Triple-Torch System:

Primary torch: 12,000°C (organic removal)

Secondary torch: 8,000°C (metal decontamination)

Tertiary torch: 15,000°C (final sterilization)

III. Hyper-Optimized Operational Protocols

3.1 CFD-Optimized Cleaning

Multiphase Flow Simulation:

Eulerian-Lagrangian particle tracking

Optimal nozzle placement reduces cleaning time by 35%

3.2 Predictive Maintenance Integration

[fayrozzaa]

تنظيف خزانات وقود السفن

تنظيف خزانات وقود السفن

Crude Oil Storage Tank Cleaning: The Ultimate Technical Encyclopedia

I. Advanced Sludge Characterization & Analysis

1.1 Molecular Composition Profiling

High-Resolution Mass Spectrometry (HRMS)

Identifies >5,000 unique compounds in sludge

Key markers:

C30 hopanes (biodegradation indicators)

DBE 12 (highly condensed aromatics)

3D Micro-CT Scanning

Resolution: 5μm voxel size

Reveals pore structure and solids distribution

1.2 Rheological Behavior Modeling

Modified Herschel-Bulkley with Thixotropy

math

\tau = [\tau_y + K\dot{\gamma}^n] × (1 + λe^{-t/θ})

Where:

λ = 0.7 (thixotropic index)

θ = 120s (recovery time constant)

II. Cutting-Edge Cleaning Technologies

2.1 Autonomous Robotic Systems

Next-Gen Specifications:

Model    Pressure (bar)     Flow (L/min) AI Features API Class

CleanBot-X12      500 300 Real-time viscosity adjustment   653 IV

SludgeTerminator Pro 450 280 Self-learning path optimization       650 VI

2.2 Plasma Arc Cleaning 2.0

Triple-Torch System:

Primary torch: 12,000°C (organic removal)

Secondary torch: 8,000°C (metal decontamination)

Tertiary torch: 15,000°C (final sterilization)

III. Hyper-Optimized Operational Protocols

3.1 CFD-Optimized Cleaning

Multiphase Flow Simulation:

Eulerian-Lagrangian particle tracking

Optimal nozzle placement reduces cleaning time by 35%

3.2 Predictive Maintenance Integration

[safsff]

تنظيف خزانات وقود السفن

تنظيف خزانات وقود السفن

Crude Oil Storage Tank Cleaning: The Ultimate Technical Encyclopedia

I. Advanced Sludge Characterization & Analysis

1.1 Molecular Composition Profiling

High-Resolution Mass Spectrometry (HRMS)

Identifies >5,000 unique compounds in sludge

Key markers:

C30 hopanes (biodegradation indicators)

DBE 12 (highly condensed aromatics)

3D Micro-CT Scanning

Resolution: 5μm voxel size

Reveals pore structure and solids distribution

1.2 Rheological Behavior Modeling

Modified Herschel-Bulkley with Thixotropy

math

\tau = [\tau_y + K\dot{\gamma}^n] × (1 + λe^{-t/θ})

Where:

λ = 0.7 (thixotropic index)

θ = 120s (recovery time constant)

II. Cutting-Edge Cleaning Technologies

2.1 Autonomous Robotic Systems

Next-Gen Specifications:

Model    Pressure (bar)     Flow (L/min) AI Features API Class

CleanBot-X12      500 300 Real-time viscosity adjustment   653 IV

SludgeTerminator Pro 450 280 Self-learning path optimization       650 VI

2.2 Plasma Arc Cleaning 2.0

Triple-Torch System:

Primary torch: 12,000°C (organic removal)

Secondary torch: 8,000°C (metal decontamination)

Tertiary torch: 15,000°C (final sterilization)

III. Hyper-Optimized Operational Protocols

3.1 CFD-Optimized Cleaning

Multiphase Flow Simulation:

Eulerian-Lagrangian particle tracking

Optimal nozzle placement reduces cleaning time by 35%

3.2 Predictive Maintenance Integration

[aliiiitotoo]

تنظيف خزانات وقود السفن

تنظيف خزانات وقود السفن

Crude Oil Storage Tank Cleaning: The Ultimate Technical Encyclopedia

I. Advanced Sludge Characterization & Analysis

1.1 Molecular Composition Profiling

High-Resolution Mass Spectrometry (HRMS)

Identifies >5,000 unique compounds in sludge

Key markers:

C30 hopanes (biodegradation indicators)

DBE 12 (highly condensed aromatics)

3D Micro-CT Scanning

Resolution: 5μm voxel size

Reveals pore structure and solids distribution

1.2 Rheological Behavior Modeling

Modified Herschel-Bulkley with Thixotropy

math

\tau = [\tau_y + K\dot{\gamma}^n] × (1 + λe^{-t/θ})

Where:

λ = 0.7 (thixotropic index)

θ = 120s (recovery time constant)

II. Cutting-Edge Cleaning Technologies

2.1 Autonomous Robotic Systems

Next-Gen Specifications:

Model    Pressure (bar)     Flow (L/min) AI Features API Class

CleanBot-X12      500 300 Real-time viscosity adjustment   653 IV

SludgeTerminator Pro 450 280 Self-learning path optimization       650 VI

2.2 Plasma Arc Cleaning 2.0

Triple-Torch System:

Primary torch: 12,000°C (organic removal)

Secondary torch: 8,000°C (metal decontamination)

Tertiary torch: 15,000°C (final sterilization)

III. Hyper-Optimized Operational Protocols

3.1 CFD-Optimized Cleaning

Multiphase Flow Simulation:

Eulerian-Lagrangian particle tracking

Optimal nozzle placement reduces cleaning time by 35%

3.2 Predictive Maintenance Integration

[miiirrrooohhh]

تنظيف خزانات وقود السفن

تنظيف خزانات وقود السفن

Crude Oil Storage Tank Cleaning: The Ultimate Technical Encyclopedia

I. Advanced Sludge Characterization & Analysis

1.1 Molecular Composition Profiling

High-Resolution Mass Spectrometry (HRMS)

Identifies >5,000 unique compounds in sludge

Key markers:

C30 hopanes (biodegradation indicators)

DBE 12 (highly condensed aromatics)

3D Micro-CT Scanning

Resolution: 5μm voxel size

Reveals pore structure and solids distribution

1.2 Rheological Behavior Modeling

Modified Herschel-Bulkley with Thixotropy

math

\tau = [\tau_y + K\dot{\gamma}^n] × (1 + λe^{-t/θ})

Where:

λ = 0.7 (thixotropic index)

θ = 120s (recovery time constant)

II. Cutting-Edge Cleaning Technologies

2.1 Autonomous Robotic Systems

Next-Gen Specifications:

Model    Pressure (bar)     Flow (L/min) AI Features API Class

CleanBot-X12      500 300 Real-time viscosity adjustment   653 IV

SludgeTerminator Pro 450 280 Self-learning path optimization       650 VI

2.2 Plasma Arc Cleaning 2.0

Triple-Torch System:

Primary torch: 12,000°C (organic removal)

Secondary torch: 8,000°C (metal decontamination)

Tertiary torch: 15,000°C (final sterilization)

III. Hyper-Optimized Operational Protocols

3.1 CFD-Optimized Cleaning

Multiphase Flow Simulation:

Eulerian-Lagrangian particle tracking

Optimal nozzle placement reduces cleaning time by 35%

3.2 Predictive Maintenance Integration

[mirrrraaa]

تنظيف خزانات وقود السفن

تنظيف خزانات وقود السفن

Crude Oil Storage Tank Cleaning: The Ultimate Technical Encyclopedia

I. Advanced Sludge Characterization & Analysis

1.1 Molecular Composition Profiling

High-Resolution Mass Spectrometry (HRMS)

Identifies >5,000 unique compounds in sludge

Key markers:

C30 hopanes (biodegradation indicators)

DBE 12 (highly condensed aromatics)

3D Micro-CT Scanning

Resolution: 5μm voxel size

Reveals pore structure and solids distribution

1.2 Rheological Behavior Modeling

Modified Herschel-Bulkley with Thixotropy

math

\tau = [\tau_y + K\dot{\gamma}^n] × (1 + λe^{-t/θ})

Where:

λ = 0.7 (thixotropic index)

θ = 120s (recovery time constant)

II. Cutting-Edge Cleaning Technologies

2.1 Autonomous Robotic Systems

Next-Gen Specifications:

Model    Pressure (bar)     Flow (L/min) AI Features API Class

CleanBot-X12      500 300 Real-time viscosity adjustment   653 IV

SludgeTerminator Pro 450 280 Self-learning path optimization       650 VI

2.2 Plasma Arc Cleaning 2.0

Triple-Torch System:

Primary torch: 12,000°C (organic removal)

Secondary torch: 8,000°C (metal decontamination)

Tertiary torch: 15,000°C (final sterilization)

III. Hyper-Optimized Operational Protocols

3.1 CFD-Optimized Cleaning

Multiphase Flow Simulation:

Eulerian-Lagrangian particle tracking

Optimal nozzle placement reduces cleaning time by 35%

3.2 Predictive Maintenance Integration

[biotechscientist]

Revolutionizing Powder Analysis with AI! #sciencefather #AIinMaterialsScience

Revolutionizing powder analysis with the power of AI! From real-time particle characterization to predictive quality control, our cutting-edge solutions are transforming material science and manufacturing efficiency. Visit Our Website : http://biotechnologyscientist.com Contact Us : support@biotechnologyscientist.com Nomination Link : https://biotechnologyscientist.com/award-nomination/?ecategory=Awards&rcategory=Awardee #AIinMaterialsScience #PowderAnalysis #SmartManufacturing #MachineLearning #AdvancedAnalytics #MaterialInnovation #AIForIndustry #QualityControl #IndustrialAI #SmartMaterials #TechInnovation #AIResearch #DataDriven #ProcessOptimization #DigitalTransformation #NextGenManufacturing #ScientificAI #ParticleAnalysis #AutomationTech #AIRevolution

[didanawisgi]

Genomic characterization and infectivity of a novel SARS-like coronavirus in Chinese bats

Dan Hu 1,2, Changqiang Zhu 2, Lele Ai 2, Ting He 2, Yi Wang 3, Fuqiang Ye 2, Lu Yang 2, Chenxi Ding 2, Xuhui Zhu 2, Ruicheng Lv 2, Jin Zhu 2, Bachar Hassan 4, Youjun Feng 5,✉, Weilong Tan 2,✉, Changjun Wang 1,2,✉

Abstract

SARS coronavirus (SARS-CoV), the causative agent of the large SARS outbreak in 2003, originated in bats. Many SARS-like coronaviruses (SL-CoVs) have been detected in bats, particularly those that reside in China, Europe, and Africa. To further understand the evolutionary relationship between SARS-CoV and its reservoirs, 334 bats were collected from Zhoushan city, Zhejiang province, China, between 2015 and 2017. PCR amplification of the conserved coronaviral protein RdRp detected coronaviruses in 26.65% of bats belonging to this region, and this number was influenced by seasonal changes. Full genomic analyses of the two new SL-CoVs from Zhoushan (ZXC21 and ZC45) showed that their genomes were 29,732 nucleotides (nt) and 29,802 nt in length, respectively, with 13 open reading frames (ORFs). These results revealed 81% shared nucleotide identity with human/civet SARS CoVs, which was more distant than that observed previously for bat SL-CoVs in China. Importantly, using pathogenic tests, we found that the virus can reproduce and cause disease in suckling rats, and further studies showed that the virus-like particles can be observed in the brains of suckling rats by electron microscopy. Thus, this study increased our understanding of the genetic diversity of the SL-CoVs carried by bats and also provided a new perspective to study the possibility of cross-species transmission of SL-CoVs using suckling rats as an animal model.

Acknowledgements

This study was supported by National Major Infectious Diseases (2017ZX10303401-007), National Natural Science Foundation of China (U1602223), Army Logistics Scientific Research Projects (BWS14C051), Jiangsu Province Science and Technology Support Program Project (BE2017620), National Postdoctoral Special Aid (2016T91011), and Jiangsu Postdoctoral Fund (1501147C).

[apparel-architects]

Silent Crisis: Apparel Industry’s Impact on Environmental Plastic Pollution

Silent Crisis: Apparel Industry’s Impact on Environmental Plastic Pollution

The apparel industry stands as one of the most prominent sectors in the global economy, valued at trillions of dollars. It is a vibrant tapestry woven with creativity, culture, and commerce. Yet, beneath this façade lies a troubling reality: the industry’s contribution to plastic pollution. Recent studies have highlighted that the fashion sector is leaking millions of tons of plastic into our environment each year, presenting an urgent call to action for sustainable practices and more responsible consumption.

This post dives into the scale of the issue, the toll on the environment, the role of consumers, innovations shaping the future, and the critical need for collaboration.

How AI is Transforming the Industry The fashion industry

The Scale of the Problem

In an era characterized by fast fashion—where garments are produced rapidly at low costs to keep pace with ever-changing trends—the ecological repercussions of mass production are stark and alarming. According to a groundbreaking report by the Ellen MacArthur Foundation, the fashion industry is responsible for around 92 million tons of waste annually. A significant portion of this waste, approximately 10% (or over 9 million tons), comes from plastic-derived materials such as polyester, nylon, and acrylic.

The apparel industry is a multi-trillion-dollar global powerhouse, producing over 100 billion garments annually. Fast fashion—a business model that prioritizes cheap, mass-produced clothing—has escalated demand for synthetic fabrics like polyester, nylon, and acrylic. These materials are derived from fossil fuels and account for over 60% of the fibers used in clothing today. While they provide durability, affordability, and versatility, synthetic fabrics have a dark side: plastic pollution.

Every year, an estimated 14 million tons of plastic enter oceans, with the textile industry responsible for roughly 35% of global microplastic emissions. Microplastics are tiny particles that shed from synthetic clothing during washing and wear. Unlike larger plastic items, microplastics are nearly impossible to filter out of water systems, eventually infiltrating oceans, soil, and even human food chains.

The Environmental Toll of Plastic Use

The environmental implications of this pollution are dire. Marine ecosystems suffer tremendously from the influx of microplastics, which are ingested by aquatic life, leading to toxic accumulation in the food chain. Small organisms confuse these particles for food, while larger predators face the risk of ingesting contaminated prey. The consequences echo up the food chain, affecting not only fish populations but also the broader health of marine biodiversity and impacting human consumers.

Plus-Size Fashion Industry Set to Reach $964.9 Billion by 2033

Plastic-based fabrics may be a modern marvel, but their environmental toll is staggering. The process of producing synthetic fibers relies heavily on nonrenewable resources like petroleum, contributing to carbon emissions. For instance, polyester production alone generates an estimated 700 million tons of CO2 emissions annually.

Moreover, synthetic clothing contributes to plastic pollution throughout its lifecycle:

Production: Manufacturing synthetic fabrics consumes significant energy and water, releasing harmful chemicals into surrounding ecosystems. Factories located in developing countries often operate with minimal environmental regulations, further exacerbating the issue.

Washing: Each time synthetic garments are washed, microplastics are released into wastewater. A single load of laundry can shed up to 700,000 microplastic fibers, most of which end up in rivers, lakes, and oceans. Marine organisms mistake these microplastics for food, disrupting ecosystems and entering the food chain.

Disposal: Clothing that ends up in landfills takes hundreds of years to break down. Unlike organic fabrics like cotton or wool, synthetic materials do not biodegrade but instead fragment into smaller and smaller particles that persist in the environment.

The Consumer’s Role and Responsibility

Environmental: Consumers play a pivotal role in addressing this crisis. The rise of fast fashion has instilled a pervasive “throwaway culture,” encouraging individuals to prioritize quantity over quality. However, raising awareness and making conscious choices can shift the trajectory of the apparel industry. Importantly, this shift requires a collective effort from both consumers and brands.

Brands are increasingly recognizing their responsibility to mitigate plastic pollution. Several companies are investing in sustainable materials, including organic cotton, Tencel, and recycled polyester. They are also adopting processes that minimize waste and reduce microplastic release, such as using filtration systems in production facilities. Brands like Patagonia and Eileen Fisher have become leaders in this endeavor, emphasizing transparency and sustainability in their operations.

While industries must bear much of the responsibility, consumers play a pivotal role in addressing the plastic crisis in apparel. Conscious consumer choices can drive systemic change and reduce demand for unsustainable practices. Here are some actionable steps consumers can take:

Choose Natural Fibers: Opt for clothing made from natural and biodegradable materials like organic cotton, hemp, wool, or linen. These fabrics have a lower environmental footprint compared to synthetics.

Prioritize Quality Over Quantity: The fast fashion cycle thrives on low-cost, short-lived garments. Consumers can reduce waste by investing in high-quality, durable clothing that lasts for years.

Wash Mindfully: Use microplastic filters for washing machines to capture synthetic fibers. Washing clothes less frequently and at lower temperatures can also reduce shedding.

Support Sustainable Brands: Look for brands that prioritize sustainability, transparency, and innovation. Certifications such as Global Organic Textile Standard (GOTS) or OEKO-TEX can guide consumers toward eco-friendly choices.

Extend Clothing Lifespan: Repair, reuse, or donate clothes instead of discarding them. The rise of second-hand markets, thrift stores, and clothing rental platforms makes it easier for consumers to extend garment lifecycles.

While individual actions may seem small, collective consumer efforts have the power to shift industry norms and demand accountability from brands.

Rediscovering 90s Fashion: Nostalgia Meets 2025 Trends

Innovations on the Horizon

Innovation plays a significant role in addressing this crisis. Entrepreneurs and researchers are developing new materials that either fully biodegrade or are sourced from sustainable origins, such as algae-based fabrics or textiles made from agricultural waste. Additionally, technological advancements such as washing machine filters and innovative recycling methods are being explored to capture microfibers before they enter waterways.

The apparel industry is beginning to recognize its role in the plastic pollution crisis, and innovations are emerging to address the problem. Technological advancements, sustainable materials, and creative solutions are paving the way for a cleaner future.

Bio-Based and Biodegradable Fabrics: Companies are experimenting with fabrics derived from natural sources like algae, fungi, and recycled agricultural waste. For instance, bioengineered fibers such as Mylo (made from mushroom roots) and Piñatex (derived from pineapple leaves) offer sustainable alternatives to synthetic fabrics.

Recycled Textiles: Efforts to close the loop in fashion production have led to advancements in recycling technology. Companies like Worn Again Technologies and Re:newcell are developing methods to break down old textiles and recreate high-quality fibers.

Microplastic Capture Technologies: Innovations in washing machines and filters aim to reduce microplastic pollution. Companies are also developing treatments that reduce fiber shedding from synthetic fabrics.

Circular Fashion: Brands are embracing circular models, where garments are designed to be reused, repaired, or recycled. Initiatives like clothing take-back programs and rental services are helping reduce waste and dependency on virgin materials.

Transparency and Blockchain: Technology like blockchain allows for greater transparency across supply chains, ensuring that brands are held accountable for their environmental impact.

Although these innovations offer hope, widespread adoption will require significant investment, consumer demand, and supportive policies.

The Urgency of Collaboration

The apparel industry’s environmental reckoning necessitates collaboration among stakeholders. Policymakers must enact stricter regulations regarding plastic use in textiles, set standards for microplastics emissions, and promote the circular economy. Concurrently, manufacturers, retailers, and consumers must advocate for better practices, emphasizing quality over quantity.

Addressing the apparel industry’s impact on plastic pollution is not a one-sided effort. It requires collaboration between governments, businesses, and consumers to drive meaningful change.

Corporate Responsibility: Apparel brands must take proactive steps to reduce plastic use, adopt sustainable alternatives, and be transparent about their environmental impact. Leading companies like Patagonia and Stella McCartney are setting an example, but industry-wide change is needed.

Government Regulations: Governments play a critical role in enforcing environmental standards. Policies that limit microplastic pollution, encourage sustainable manufacturing, and regulate waste management are essential to hold industries accountable.

Consumer Advocacy: Consumers have the power to influence change through their purchasing habits and voices. Supporting sustainable brands, advocating for stricter policies, and spreading awareness can accelerate progress.

Cross-Sector Partnerships: Collaboration between scientists, environmental organizations, and the fashion industry can drive innovation and solutions. Partnerships like The Microfibre Consortium are already working to address the impact of microplastics in textiles.

The clock is ticking, and the urgency cannot be overstated. Without coordinated efforts, the damage caused by plastic pollution will become irreversible.

Textiles 300 AD Unveiling the Past: Can We Truly Date Ancient Textiles?

Conclusion

The apparel industry’s contribution to plastic pollution is a pressing issue that requires immediate attention. As we push through the constraints of fast fashion, we must reflect on the environmental toll it exacts. By embracing sustainable practices, demanding transparency, and choosing wisely, we can help turn the tide against plastic pollution in the apparel industry.

As we evolve in our understanding of this intricate relationship between fashion and the environment, let us rise to the occasion. The runway to a sustainable and ethically responsible future in fashion is not merely a trend; it is a necessary transformation that promises a healthier planet for generations to come. It is time for the apparel industry to replace its legacy of plastic waste with a pledge for sustainable practices and genuine commitment to the environment.

[colinwilson11]

Ophthalmic Drugs Contract Manufacturing: An Overview Of The Rapidly Evolving

Regulatory compliances play a pivotal role in ophthalmic drugs manufacturing due to stringent norms and quality standards set by regulatory bodies like US FDA, EMA, etc. Ophthalmic products manufacturing needs to adhere to Current Good Manufacturing Practices (CGMP) to ensure product safety, efficacy, and quality. Ophthalmic drugs contract manufacturers invest heavily in approvals, certifications, and manufacturing facilities upgradation to meet evolving regulatory guidelines. They focus on establishing robust quality management systems, validation protocols, change control systems, and document controls. Regular product quality reviews and internal audits also help contract manufacturers deliver regulatory compliance.

Leading Technology And Specialized Equipment

Ophthalmic drugs require highly sophisticated and precise manufacturing technologies and equipment due to small volumes and concentrations. Contract manufacturers leverage leading technologies like microprocessing, microfluidics, micro-molding, and precision coating to produce a diverse range of ophthalmic products. They invest in specialized, high-end equipment like micronizing mills, soft-gel encapsulation systems, and laser-marking machines. Automation and digitization using IoT, AI, and analytics also help boost production efficiency and quality. The technologies and equipment enable contract manufacturers to cater to customized packaging and dosing requirements of ophthalmic drugs.

Specialized Facilities And Cleanrooms 

Ophthalmic products demand stringent environmental control and hygiene standards owing to small dosage forms and direct exposure to eyes. Contract manufacturers operate highly specialized facilities with ISO classified cleanrooms to minimize microbial and particulate contaminations. Features like laminar air flow, differential air pressures, high-efficiency particulate air (HEPA) filtration help maintain critical environmental conditions. Periodic qualification and calibration of facilities and utility systems also ensure process validation. Designated areas for raw material receipts, products manufacturing, quality testing, packaging, and warehousing follow zoning principles. These specialized facilities enable contract manufacturers to ensure sterility, stability, and preserved efficacy of Ophthalmic Drugs Contract Manufacturing and storage.

Capabilities In Sterile Fill/Finish

A major portion of ophthalmic drugs require sterile fill/finish due to direct administration into eyes. Contract manufacturers have dedicated sterile suites equipped with barrier isolators, aseptic processing equipment, and self-contained environmental control systems. Technologies like lyophilization and terminal sterilization aid microbial decontamination. Stringent personnel training on garbing and cross-transfer procedures helps avoid contamination risks. Regular media fills and endotoxin challenge simulations validate sterilization process efficacy. Quality control testing through rapid microbiological methods, particulate testing and endotoxin assays ensure sterility assurance of aseptically filled ophthalmic products. These capabilities enable outsourcing of sterile fill/finish operations for preservative-free ophthalmic drugs.

Specialized Analytical Testing 

Ophthalmic drugs require meticulous analytical characterization and quality testing due to small amounts administered near eye region. Contract manufacturers invest in -leading analytical instruments like HPLC, GC, dissolution testing equipment, and particle size analyzers. Methods involve testing of identity, purity, content uniformity, particulate matters, pH, osmolarity, sterility, bacterial endotoxin, and preservative content. Stability indicating methods help real-time product monitoring on storage. Various ophthalmic dosage forms like ointments, gels, suspensions etc. also require formulations development and evaluation of rheological properties, spreadability and bioavailability. Contract testing laboratories employ highly trained analytical experts, validated methods and computerized data integrity systems. These specialized testing capabilities help ensure efficacy and safety of outsourced ophthalmic products.

Case Studies And Fill-Finish Agreement 

A leading UK-based ophthalmic drug firm outsourced development and fill-finish operations of its novel anti-inflammatory eye drop to a US-based contract manufacturer. Impressed by proven sterile fill/finish capabilities, quality systems, and regulatory compliance track record, six-month technology transfer was completed on schedule. Further, a 1-year commercial supply agreement was signed with production scale-up clauses. Another Ophthalmic Drugs Contract Manufacturing giant outsourced manufacturing of its portable multi-dose ophthalmic dispensers to a reputed Japanese contract manufacturer specializing in medical-device moulding. Leveraging expertise in micro-molding and precision assembly, the firm ensured precise dosing and improved patients' compliance. These cases illustrate effective collaborations aiding faster access of critical ophthalmic therapies. 

Get more insights on this topic: https://www.trendingwebwire.com/ophthalmic-drugs-contract-manufacturing-meeting-global-ophthalmic-medications-demands-through-specialized-services/

About Author:

Priya Pandey is a dynamic and passionate editor with over three years of expertise in content editing and proofreading. Holding a bachelor's degree in biotechnology, Priya has a knack for making the content engaging. Her diverse portfolio includes editing documents across different industries, including food and beverages, information and technology, healthcare, chemical and materials, etc. Priya's meticulous attention to detail and commitment to excellence make her an invaluable asset in the world of content creation and refinement. (LinkedIn - https://www.linkedin.com/in/priya-pandey-8417a8173/)

*Note: 1. Source: Coherent Market Insights, Public sources, Desk research 2. We have leveraged AI tools to mine information and compile it