WVU psychologist ‘reverse engineers’ slot machines to better understand compulsive gambling

WEST VIRGINIA UNIVERSITY

 

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MARIYA CHERKASOVA (LEFT), ASSISTANT PROFESSOR OF PSYCHOLOGY AT WVU, AND GRADUATE STUDENT POLINA KROM TEST A SLOT MACHINE SIMULATOR TO STUDY HOW USERS ENTER THE “ZONE” AND LOSE TOUCH WITH THE OUTSIDE WORLD.

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CREDIT: WVU PHOTO/BRIAN PERSINGER

A West Virginia University researcher is studying slot machines to determine what makes them a potentially addictive form of gambling.

Mariya Cherkasova, assistant professor in the Department of Psychology at the WVU Eberly College of Arts and Sciences, will spend the next two years “reverse engineering” certain structural characteristics of slot machines to find out what makes them an immersive product. Her research is supported by the International Center for Responsible Gaming.

In hopes of understanding the addictive nature of the games, Cherkasova will examine the interactions between subjects’ individual characteristics and the slot machines’ structural characteristics. Subjects will play several versions of a highly realistic slot machine simulator that runs in a browser.

“Some versions of the game will include the typical bells and whistles that accompany wins, while others will not,” she said. “This exemplifies the reverse engineering of the sensory feedback — one version has bells and whistles while the other lacks them.”

She will also manipulate how often and how much the players win, known as a reinforcement schedule. Game versions will be engineered to have specific reinforcement ratios and intervals.

In an additional experiment in her laboratory, Cherkasova will track subjects’ eyes during simulator play.

“That part is pretty innovative,” she said. “Because when you’re measuring immersion, it’s mostly been based on self-report, and there’s a bit of a paradox in there — how can you measure immersion without disrupting those states? You either have to measure it retrospectively, or you have to disrupt the state to measure it. Some of our past work suggests that you can study immersion using eye tracking. We hope to validate those indices as tacit measures of immersion that do not involve explicit self-report or interrupting the immersive state.”

A graduate research assistant will run the laboratory study and collect data in the second year of the two-year study.

Studies have shown slot machines are associated with harms more than other gambling modalities like the lottery.

“From a public health perspective, there’s a continuum of gambling,” Cherkasova said. “Some products are associated with very few harms. Few people develop problematic gambling patterns buying lottery tickets. Slot machines are still ‘king’ in terms of how many people play them. And they still account for the lion’s portion of gambling revenue and are on the other end of the harm continuum.”

Some slot machine gamblers become highly immersed and absorbed in the game, a state sometimes referred to as the “zone.” Similar states may be experienced while playing video games or binge watching a show. However, those states may be especially harmful during slot machine play because they can lead to a person losing significant sums of money.

“The person loses track of time,” she said. “They forget everything around them and just keep playing and playing the slot machine. This is something that’s associated with compulsive gameplay and very significant losses.”

In past work, Cherkasova and other researchers found higher levels of depression and lower levels of dispositional mindfulness are both strongly correlated with immersion. However, just as a biological predisposition may lead to gambling problems, gambling products and environments also bring out these same tendencies.

“For that reason, it’s as important to study the characteristics of gambling products as it is to study individual characteristics of the players that may be liabilities,” she said.

While the gambling industry doesn’t share information about the characteristics of slot machines, a kind of natural selection process guides which models stay on the floor or online — those that make the most money tend to remain in use.

In future research, Cherkasova would like to study what happens in a player’s brain when they enter a flow state, like “the zone,” when playing a slot machine. A small number of studies have focused on players’ flow states during video gameplay, but none have looked at gambling or slot machine use.

“Frankly, we really don’t know what goes on in the brain,” Cherkasova said.

She said she believes her work will help researchers understand why slot machines are one of the most harmful gambling modalities and how slot machine design interacts with players’ individual vulnerabilities to cause harm.

“Diagnosable gambling disorders are rare,” she said. “But just like drinking alcohol, there’s really no completely safe level of gambling.”

 

Do opponents’ race, gender, and party impact US congressional fundraising?

WILEY

Donations for a political candidate can be motivated by support for that candidate or by opposition to the candidate’s opponent. New research published in Social Science Quarterly found that female Democrats and non-white male Democrats in the United States have a fundraising advantage when running against a white male Republican. Female Republicans or non-white male Republicans do not have this advantage when running against white male Democrats.

To assess the impact that race, gender, and party affiliation of a candidate and that candidate’s opponent have on the candidate’s fundraising, Dennis Halcoussis, PhD, of California State University, Northridge, examined data from the 2016, 2018, and 2020 US Congressional elections.

The results of his analysis suggest that Democratic donors give more when their party nominates a white female or non-white male to run against a white male Republican. Republican donors do not behave similarly—they do not donate more if the Republican candidate is a white female or a non-white male running against a white male Democrat.

“Any analysis of race, gender, and campaign contributions needs to consider the characteristics of both the Democratic and Republican candidate, not just one candidate in isolation,” said Prof. Halcoussis.

URL: https://onlinelibrary.wiley.com/doi/10.1111/ssqu.13369

 

Additional Information
NOTE: The information contained in this release is protected by copyright. Please include journal attribution in all coverage. For more information or to obtain a PDF of any study, please contact: Sara Henning-Stout, newsroom@wiley.com.

About the Journal
Nationally recognized as one of the top journals in the field, Social Science Quarterly, the journal of the Southwestern Social Science Association, publishes current research on a broad range of topics including political science, sociology, economics, history, social work, geography, international studies, and women's studies.

About Wiley
Wiley is a knowledge company and a global leader in research, publishing, and knowledge solutions. Dedicated to the creation and application of knowledge, Wiley serves the world’s researchers, learners, innovators, and leaders, helping them achieve their goals and solve the world's most important challenges. For more than two centuries, Wiley has been delivering on its timeless mission to unlock human potential. Visit us at Wiley.com. Follow us on Facebook, Twitter, LinkedIn and Instagram.

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JOURNAL

Social Science Quarterly

DOI

10.1111/ssqu.13369 

ARTICLE TITLE

Impact of Opponents' Race, Gender, and Party on United States Congressional Fundraising

 

Cracking the code of flash floods: new insights from China's mountainous regions

IGSNRR CAS

 

IMAGE: 

SPATIAL DISTRIBUTION OF DEM AND WATER SYSTEM (A), LAND USE (B) AND SOIL TEXTURE TYPES (C) IN ANHE CATCHMENT

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CREDIT: JOURNAL OF GEOGRAPHICAL SCIENCES

Recently, researchers have made breakthroughs in flash flood forecasting by studying how different rainfall patterns affect flash floods in China's mountainous regions. This research leads to the possibility of more accurate and localized flood warnings, potentially enhancing disaster preparedness and reducing the devastating effects of flash floods on at-risk communities.

Flash floods, marked by their sudden onset and devastating impact, pose a significant threat globally, particularly in China where they account for over 70% of flood-related fatalities and substantial economic losses. The complexity of predicting these events arises from the intricate interplay between intense, short-duration rainfall and the subsequent rapid catchment responses. This underscores the urgent need for advanced research into rainfall patterns and flash flood dynamics to improve forecasting accuracy and develop effective early warning systems, aiming to mitigate the severe consequences of these natural disasters.

In light of this, a study (https://doi.org/10.1007/s11442-023-2188-5) published in the Journal of Geographical Sciences in December 2023 offers a fresh perspective on flash flood forecasting by evaluating simulation capabilities with respect to rainfall variability in Anhe Catchment, a small mountainous region in southeastern China.

This study combined multivariate statistical analysis and hydrological simulations to meticulously evaluate the capabilities of two advanced hydrological models (Xinanjiang hydrological model, XAJ and China Flash Flood hydrological Model, CNFF), and predict flash flood responses under these diverse rainfall conditions. The findings reveal a significant proficiency of both models in accurately simulating water balances, hydrographs, flash flood behavior indices and flood dynamics indices for flash flood events triggered by extended periods of uniform rainfall. However, the models faced difficulties in precisely forecasting flash flood behaviors associated with short, intense bursts of rainfall. The essence of this research underscores the complexity of flash flood phenomena, driven by the distinct characteristics of the identified rainfall patterns. Through the application of the XAJ and CNFF models, the study highlights the challenges in bridging the gap between model simulations and the erratic nature of intense rainfall events.

Dr. Wang Xuemei, the lead author, emphasizes the critical nature of understanding the intricacies of rainfall-induced flash floods for improved prediction and management. "Our findings reveal the significant influence of rainfall temporal patterns on flash flood dynamics, highlighting the need for tailored forecasting approaches in different hydrological settings," she states.

This research offers significant advancements in flash flood forecasting, providing a nuanced understanding of how different rainfall patterns affect flash flood genesis and progression. Such insights are invaluable for developing more accurate and region-specific flood prediction tools, ultimately enhancing disaster preparedness and mitigation strategies.

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References

DOI

10.1007/s11442-023-2188-5

Original Source URL

https://doi.org/10.1007/s11442-023-2188-5

Funding information

National Natural Science Foundation of China, No.42171047, No.42071041

About Journal of Geographical Sciences

Journal of Geographical Sciences is an international and multidisciplinary peer-reviewed journal focusing on human-nature relationships. It publishes papers on physical geography, natural resources, environmental sciences, geographic information, remote sensing and cartography. Manuscripts come from different parts of the world.

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JOURNAL

Journal of Geographical Sciences

DOI

10.1007/s11442-023-2188-5 

SUBJECT OF RESEARCH

Not applicable

ARTICLE TITLE

Evaluating flash flood simulation capability with respect to rainfall temporal variability in a small mountainous catchment

 

How scientists are accelerating chemistry discoveries with automation

New statistical-modeling workflow may help advance drug discovery and synthetic chemistry

DOE/LAWRENCE BERKELEY NATIONAL LABORATORY

 

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BERKELEY LAB SCIENTISTS HAVE DEVELOPED A NEW AUTOMATED WORKFLOW THAT APPLIES STATISTICAL ANALYSIS TO PROCESS DATA FROM NUCLEAR MAGNETIC RESONANCE (NMR) SPECTROSCOPY. THE ADVANCE COULD HELP SPEED THE DISCOVERY OF NEW PHARMACEUTICAL DRUGS AND ACCELERATE THE DEVELOPMENT OF NEW CHEMICAL REACTIONS.

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CREDIT: JENNY NUSS/BERKELEY LAB

A new automated workflow developed by scientists at Lawrence Berkeley National Laboratory (Berkeley Lab) has the potential to allow researchers to analyze the products of their reaction experiments in real time, a key capability needed for future automated chemical processes.

The developed workflow – which applies statistical analysis to process data from nuclear magnetic resonance (NMR) spectroscopy – could help speed the discovery of new pharmaceutical drugs, and accelerate the development of new chemical reactions.

The Berkeley Lab scientists who developed the groundbreaking technique say that the workflow can quickly identify the molecular structure of products formed by chemical reactions that have never been studied before. They recently reported their findings in the Journal of Chemical Information and Modeling.

In addition to drug discovery and chemical reaction development, the workflow could also help researchers who are developing new catalysts. Catalysts are substances that facilitate a chemical reaction in the production of useful new products like renewable fuels or biodegradable plastics.

“What excites people the most about this technique is its potential for real-time reaction analysis, which is an integral part of automated chemistry,” said first author Maxwell C. Venetos, a former researcher in Berkeley Lab’s Materials Sciences Division and former graduate student researcher in materials sciences at UC Berkeley. He completed his doctoral studies last year. “Our workflow really allows you to start pursuing the unknown. You are no longer constrained by things that you already know the answer to.”

The new workflow can also identify isomers, which are molecules with the same chemical formula but different atomic arrangements. This could greatly accelerate synthetic chemistry processes in pharmaceutical research, for example. “This workflow is the first of its kind where users can generate their own library, and tune it to the quality of that library, without relying on an external database,” Venetos said.

Advancing new applications

In the pharmaceutical industry, drug developers currently use machine-learning algorithms to virtually screen hundreds of chemical compounds to identify potential new drug candidates that are more likely to be effective against specific cancers and other diseases. These screening methods comb through online libraries or databases of known compounds (or reaction products) and match them with likely drug “targets” in cell walls.

But if a drug researcher is experimenting with molecules so new that their chemical structures don’t yet exist in a database, they must typically spend days in the lab to sort out the mixture’s molecular makeup: First, by running the reaction products through a purification machine, and then using one of the most useful characterization tools in a synthetic chemist’s arsenal, an NMR spectrometer, to identify and measure the molecules in the mixture one at a time.

“But with our new workflow, you could feasibly do all of that work within a couple of hours,” Venetos said. The time-savings come from the workflow’s ability to rapidly and accurately analyze the NMR spectra of unpurified reaction mixtures that contain multiple compounds, a task that is impossible through conventional NMR spectral analysis methods.

“I’m very excited about this work as it applies novel data-driven methods to the age-old problem of accelerating synthesis and characterization,” said senior author Kristin Persson, a faculty senior scientist in Berkeley Lab’s Materials Sciences Division and UC Berkeley professor of materials science and engineering who also leads the Materials Project.

Experimental results

In addition to being much faster than benchtop purification methods, the new workflow has the potential to be just as accurate. NMR simulation experiments performed using the National Energy Research Scientific Computing Center (NERSC) at Berkeley Lab with support from the Materials Project showed that the new workflow can correctly identify compound molecules in reaction mixtures that produce isomers, and also predict the relative concentrations of those compounds.

To ensure high statistical accuracy, the research team used a sophisticated algorithm known as Hamiltonian Monte Carlo Markov Chain (HMCMC) to analyze the NMR spectra. They also performed advanced theoretical calculations based on a method called density-functional theory.

Venetos designed the automated workflow as open source so that users can run it on an ordinary desktop computer. That convenience will come in handy for anyone from industry or academia.

The technique sprouted from conversations between the Persson group and experimental collaborators Masha Elkin and Connor Delaney, former postdoctoral researchers in the John Hartwig group at UC Berkeley. Elkin is now a professor of chemistry at the Massachusetts Institute of Technology, and Delaney a professor of chemistry at the University of Texas at Dallas.

“In chemistry reaction development, we are constantly spending time to figure out what a reaction made and in what ratio,” said John Hartwig, a senior faculty scientist in Berkeley Lab’s Chemical Sciences Division and UC Berkeley professor of chemistry. “Certain NMR spectrometry methods are precise, but if one is deciphering the contents of a crude reaction mixture containing a bunch of unknown potential products, those methods are far too slow to have as part of a high-throughput experimental or automated workflow. And that's where this new capability to predict the NMR spectrum could help,” he said.

Now that they’ve demonstrated the automated workflow’s potential, Persson and team hope to incorporate it into an automated laboratory that analyzes the NMR data of thousands or even millions of new chemical reactions at a time.

Other authors on the paper include Masha Elkin, Connor Delaney, and John Hartwig at UC Berkeley.

NERSC is a DOE Office of Science user facility at Berkeley Lab.

The work was supported by the U.S. Department of Energy’s Office of Science, the U.S. National Science Foundation, and the National Institutes of Health.

###

Lawrence Berkeley National Laboratory (Berkeley Lab) is committed to delivering solutions for humankind through research in clean energy, a healthy planet, and discovery science. Founded in 1931 on the belief that the biggest problems are best addressed by teams, Berkeley Lab and its scientists have been recognized with 16 Nobel Prizes. Researchers from around the world rely on the Lab’s world-class scientific facilities for their own pioneering research. Berkeley Lab is a multiprogram national laboratory managed by the University of California for the U.S. Department of Energy’s Office of Science.

DOE’s Office of Science is the single largest supporter of basic research in the physical sciences in the United States, and is working to address some of the most pressing challenges of our time. For more information, please visit energy.gov/science.

 

 

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JOURNAL

Journal of Chemical Information and Modeling

DOI

10.1021/acs.jcim.3c01864 

METHOD OF RESEARCH

Data/statistical analysis

SUBJECT OF RESEARCH

Not applicable

ARTICLE TITLE

Deconvolution and Analysis of the 1H NMR Spectra of Crude Reaction Mixtures

ARTICLE PUBLICATION DATE

4-Apr-2024

 

PFAS ‘forever chemicals’ above drinking water guidelines in global source water

We’re likely underestimating the future impact of PFAS in the environment, new UNSW Sydney-led study shows.

UNIVERSITY OF NEW SOUTH WALES

Per-and poly-fluoroalkyl substances – commonly known as PFAS – are a group of over 14,000 human-made chemicals that have been popular since the 1950s for their diverse skills in resisting heat, water, grease and stains.  

They’ve been commonly found in household products like non-stick frypans, clothing, cosmetics, insecticides, and food packaging, as well as specialty industry products, like firefighting foam. 

But despite their broad skillset, the chemicals have a dark side: they’re known as ‘forever chemicals’ as once they’re in the environment – or our bodies – they don’t degrade further.  

PFAS have been linked to environmental and health issues, including some cancers, but a lot remains unknown about the true scale and potential impacts of the problem – including how much is in our water supply. 

A new UNSW-led international study, published today in Nature Geoscience, assessed the levels of PFAS contamination in surface and ground water around the globe.  

It found that much of our global source water exceeds PFAS safe drinking limits. 

“Many of our source waters are above PFAS regulatory limits,” says senior author of the study, UNSW Engineering Professor Denis O’Carroll. 

“We already knew that PFAS is pervasive in the environment, but I was surprised to find out the large fraction of source waters that are above drinking water advisory recommendations,” he says. “We're talking above 5 per cent, and it goes over 50 per cent in some cases.” 

The research team pulled together PFAS measurements from sources around the world, including government reports, databases, and peer-reviewed literature. Altogether, they collated more than 45,000 data points, which span over roughly 20 years.  

It’s the first study to quantify the environmental burden of PFAS on a global scale. 

The study also found high concentrations of PFAS in Australia, with many locations above recommended drinking water levels. This tended to be in areas where firefighting foams had been used in the past, like military institutions and fire training facilities.  

Prof. O’Carroll stresses that these PFAS traces are found in source water, such as dams, and not drinking water itself – drinking water goes through treatment plants, some of which are designed to reduce the amount of chemicals such as PFAS in our water before it comes out of the tap.  

But some water providers – for example, Sydney Water – don’t routinely measure the broad range of PFAS potentially in our drinking water, says Prof. O’Carroll.

“Drinking water is largely safe, and I don't hesitate drinking it,” he says. “I also don’t suggest that bottled water is better, because it doesn’t mean that they’ve done anything differently than what comes out of the tap. 

“But I certainly think that monitoring PFAS levels and making the data easily available is worthwhile.” 

A contentious debate: how much PFAS is too much? 

Most people in Australia – and in many places around the world – are likely to have low levels of PFAS in their bodies.  

But the potential health risks of PFAS chemicals are poorly understood and haven’t been agreed on universally. 

According to an Australian Government expert health panel, there is limited to no evidence that PFAS poses clinically significant harm to human health – although further afield, peak bodies in the US and Europe suggest that PFAS is linked to adverse health outcomes, such as lower birth weight in babies, higher levels of cholesterol, reduced kidney function, thyroid disease, altered sex hormone levels, reduced vaccine response, and liver, kidney, and testicular cancers. 

In 2023, the World Health Organisation (WHO) declared PFOA, a type of PFAS, a category one human carcinogen. 

While PFAS has been linked to many of these health outcomes, they haven’t necessarily been shown to cause them – but given the potential risks and ‘forever’ nature of these chemicals, many regulatory bodies have tightened PFAS use and introduced safe drinking water limits as a precaution. 

“Two forms of PFAS initially raised of concerns about 20 years ago: PFOS and PFOA,” says Prof. O’Carroll. 

“These chemicals are regulated to different extents around the world. In the US, the proposed drinking water limits for PFOS and PFOA are four nanograms per litre.” 

A third PFAS is also regulated in Australia, called PFHxS. Here, the sum of PFOS and PFHxS is limited to 70 nanograms per litre – well above the four nanograms per litre combined PFOS and PFOA limit in the US. 

But our acceptable levels for PFOA in drinking water is even higher.  

“PFOA, on the other hand, is regulated in Australia at 560 nanograms per litre, which is two orders of magnitude higher than in the US,” says Prof. O’Carroll. 

While Australia’s limits seem relaxed compared to the US, both countries’ recommended drinking water guidelines pale when compared to Canada’s: here, rather than limiting only two or three forms of PFAS in drinking water, Canada tallies up the sum of all 14,000 PFAS and limits the overall number to 30 nanograms per litre. 

The study found that 69 per cent of global groundwater samples with no known contamination source exceeded Health Canada’s safe drinking water criteria, while 32 per cent of the same samples exceeded the US’s proposed drinking water hazard index. 

“There’s debate about what level PFAS should be regulated to,” says Prof. O’Carroll. “Australia has much higher limits than the US, but the question is why. 

“Both health bodies would have different reasoning for that, and there’s not a really strong consensus here.” 

An underestimated risk 

The study suggests that actual PFAS pollution in global water resources could be higher than suspected. 

This is, in part, due to us only monitoring and regulating a limited number of the 14,000 PFAS in existence, and also because the levels of PFAS in consumer products are higher than expected. 

“There’s a real unknown amount of PFAS that we’re not measuring in the environment,” says Prof. O’Carroll. “Commercial products like garments and food packaging have a lot more PFAS in them than we realise.  

“This means we’re likely underestimating the environmental burden posed by PFAS.” 

Prof. O’Carroll and his team are now trying to develop their research by quantifying these levels of PFAS from commercial products in the environment.  

They’re also working to develop technologies that can degrade PFAS in drinking water systems, and looking at developing predictive models that determine where PFAS will go in the environment. 

“Part of this is figuring out how PFAS will associate with different parts of the environment and our bodies – proteins, for example,” says Prof. O’Carroll. 

These studies will be in progress over the next two years and aim to be completed by 2026. 

In the meantime, Prof. O’Carroll says manufacturers and consumers alike need to be careful and do our due diligence when using products containing PFAS. 

“We manufacture and distribute a lot of chemicals without having a full assessment on their potential health impacts,” he says. 

“We should have judicious use of some of these chemicals. Just because they’re available, doesn't mean that we should use them.” 

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JOURNAL

Nature Geoscience

DOI

10.1038/s41561-024-01402-8 

ARTICLE TITLE

Underestimated burden of per- and polyfluoroalkyl substances in global surface waters and groundwaters

ARTICLE PUBLICATION DATE

8-Apr-2024

This 3D printer can figure out how to print with an unknown material

The advance could help make 3D printing more sustainable, enabling printing with renewable or recyclable materials that are difficult to characterize.

NEWS RELEASE 8-APR-2024
MASSACHUSETTS INSTITUTE OF TECHNOLOGY

 

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RESEARCHERS DEVELOPED A 3D PRINTER THAT CAN AUTOMATICALLY IDENTIFY THE PARAMETERS OF AN UNKNOWN MATERIAL ON ITS OWN.

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CREDIT: COURTESY OF NEIL GERSHENFELD, JAKE READ, ET AL

While 3D printing has exploded in popularity, many of the plastic materials these printers use to create objects cannot be easily recycled. While new sustainable materials are emerging for use in 3D printing, they remain difficult to adopt because 3D printer settings need to be adjusted for each material, a process generally done by hand.

To print a new material from scratch, one must typically set up to 100 parameters in software that controls how the printer will extrude the material as it fabricates an object. Commonly used materials, like mass-manufactured polymers, have established sets of parameters that were perfected through tedious, trial-and-error processes. 

But the properties of renewable and recyclable materials can fluctuate widely based on their composition, so fixed parameter sets are nearly impossible to create. In this case, users must come up with all these parameters by hand.

Researchers tackled this problem by developing a 3D printer that can automatically identify the parameters of an unknown material on its own. 

A collaborative team from MIT’s Center for Bits and Atoms (CBA), the U.S. National Institute of Standards and Technology (NIST), and the National Center for Scientific Research in Greece (Demokritos) modified the extruder, the “heart” of a 3D printer, so it can measure the forces and flow of a material.

These data, gathered through a 20-minute test, are fed into a mathematical function that is used to automatically generate printing parameters. These parameters can be entered into off-the-shelf 3D printing software and used to print with a never-before-seen material.  

The automatically generated parameters can replace about half of the parameters that typically must be tuned by hand. In a series of test prints with unique materials, including several renewable materials, the researchers showed that their method can consistently produce viable parameters. 

This research could help to reduce the environmental impact of additive manufacturing, which typically relies on nonrecyclable polymers and resins derived from fossil fuels.

“In this paper, we demonstrate a method that can take all these interesting materials that are bio-based and made from various sustainable sources and show that the printer can figure out by itself how to print those materials. The goal is to make 3D printing more sustainable,” says senior author Neil Gershenfeld, who leads CBA.

His co-authors include first author Jake Read a graduate student in the CBA who led the printer development; Jonathan Seppala, a chemical engineer in the Materials Science and Engineering Division of NIST; Filippos Tourlomousis, a former CBA postdoc who now heads the Autonomous Science Lab at Demokritos; James Warren, who leads the Materials Genome Program at NIST; and Nicole Bakker, a research assistant at CBA. The research is published in the journal Integrating Materials and Manufacturing Innovation.

Shifting material properties

In fused filament fabrication (FFF), which is often used in rapid prototyping, molten polymers are extruded through a heated nozzle layer-by-layer to build a part. Software, called a slicer, provides instructions to the machine, but the slicer must be configured to work with a particular material. 

Using renewable or recycled materials in an FFF 3D printer is especially challenging because there are so many variables that affect the material properties. 

For instance, a bio-based polymer or resin might be composed of different mixes of plants based on the season. The properties of recycled materials also vary widely based on what is available to recycle. 

“In ‘Back to the Future,’ there is a ‘Mr. Fusion’ blender where Doc just throws whatever he has into the blender and it works ]as a power source for the DeLorean time machine]. That is the same idea here. Ideally, with plastics recycling, you could just shred what you have and print with it. But, with current feed-forward systems, that won’t work because if your filament changes significantly during the print, everything would break,” Read says.

To overcome these challenges, the researchers developed a 3D printer and workflow to automatically identify viable process parameters for any unknown material.

They started with a 3D printer their lab had previously developed that can capture data and provide feedback as it operates. The researchers added three instruments to the machine’s extruder that take measurements which are used to calculate parameters.

A load cell measures the pressure being exerted on the printing filament, while a feed rate sensor measures the thickness of the filament and the actual rate at which it is being fed through the printer.

“This fusion of measurement, modeling, and manufacturing is at the heart of the collaboration between NIST and CBA, as we work develop what we’ve termed ‘computational metrology,’” says Warren.

These measurements can be used to calculate the two most important, yet difficult to determine, printing parameters: flow rate and temperature. Nearly half of all print settings in standard software are related to these two parameters.  

Deriving a dataset

Once they had the new instruments in place, the researchers developed a 20-minute test that generates a series of temperature and pressure readings at different flow rates. Essentially, the test involves setting the print nozzle at its hottest temperature, flowing the material through at a fixed rate, and then turning the heater off.

“It was really difficult to figure out how to make that test work. Trying to find the limits of the extruder means that you are going to break the extruder pretty often while you are testing it. The notion of turning the heater off and just passively taking measurements was the ‘aha’ moment,” says Read.

These data are entered into a function that automatically generates real parameters for the material and machine configuration, based on relative temperature and pressure inputs. The user can then enter those parameters into 3D printing software and generate instructions for the printer.

In experiments with six different materials, several of which were bio-based, the method automatically generated viable parameters that consistently led to successful prints of a complex object.

Moving forward, the researchers plan to integrate this process with 3D printing software so parameters don’t need to be entered manually. In addition, they want to enhance their workflow by incorporating a thermodynamic model of the hot end, which is the part of the printer that melts the filament.

This collaboration is now more broadly developing computational metrology, in which the output of a measurement is a predictive model rather than just a parameter. The researchers will be applying this in other areas of advanced manufacturing, as well as in expanding access to metrology.

This research is supported, in part, by the National Institute of Standards and Technology and the Center for Bits and Atoms Consortia.

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Written by Adam Zewe, MIT News

Paper: “Online Measurement for Parameter Discovery in Fused Filament Fabrication”

https://link.springer.com/article/10.1007/s40192-024-00350-w

 

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JOURNAL

Integrating Materials and Manufacturing Innovation

DOI

10.1007/s40192-024-00350-w 

ARTICLE TITLE

“Online Measurement for Parameter Discovery in Fused Filament Fabrication”

Proof-of-principle demonstration of 3-D magnetic recording

Possibility of ultra-high density hard disk drives with areal densities exceeding 10 Tbit/in² using multi-level magnetic recording

NATIONAL INSTITUTE FOR MATERIALS SCIENCE, JAPAN

 

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SCHEMATIC VIEW OF (TOP) CURRENTLY USED HAMR AND (BOTTOM) THREE-DIMENSIONAL MAGNETIC RECORDING SYSTEMS. IN THE THREE-DIMENSIONAL MAGNETIC RECORDING SYSTEM, THE CURIE TEMPERATURE OF EACH RECORDING LAYER DIFFERS BY ABOUT 100 K AND DATA ARE WRITTEN TO EACH LAYER BY ADJUSTING THE LASER POWER.

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CREDIT: YUKIKO TAKAHASHI NIMS, THOMAS CHANG SEAGATE TECHNOLOGY, SIMON GREAVES TOHOKU UNIVERSITY

1. Research groups from NIMS, Seagate Technology, and Tohoku University have made a breakthrough in the field of hard disk drives (HDD) by demonstrating the feasibility of multi-level recording using a three-dimensional magnetic recording medium to store digital information. The research groups have shown that this technology can be used to increase the storage capacity of HDDs, which could lead to more efficient and cost-effective data storage solutions in the future.

2. Data centers are increasingly storing vast amounts of data on hard disk drives (HDDs) that use perpendicular magnetic recording (PMR) to store information at areal densities of around 1.5 Tbit/in². However, to transition to higher areal densities, a high anisotropy magnetic recording medium consisting of FePt grains combined with heat-assisted laser writing is required. This method, known as heat-assisted magnetic recording (HAMR), is capable of sustaining areal recording densities of up to 10 Tbit/in². Furthermore, densities of larger than 10 Tbit/in² are possible based on a new principle demonstrated by storing multiple recording levels of 3 or 4 compared with the binary level used in HDD technology.

3. In this study, we succeeded in arranging the FePt recording layers three dimensionally, by fabricating lattice-matched, FePt/Ru/FePt multilayer films, with Ru as a spacer layer. Measurements of the magnetization show the two FePt layers have different Curie temperatures. This means that three-dimensional recording becomes possible by adjusting the laser power when writing. In addition, we have demonstrated the principle of 3D recording through recording simulations, using a media model that mimics the microstructure and magnetic properties of the fabricated media.

4. The three-dimensional magnetic recording method can increase recording capacity by stacking recording layers in three dimensions. This means that more digital information can be stored with fewer HDDs, leading to energy savings for data centers. In the future, we plan to develop processes to reduce the size of FePt grains, to improve the orientation and magnetic anisotropy, and to stack more FePt layers to realize a media structure suitable for practical use as a high-density HDD.

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5. This research was conducted by Dr. P. Tozman, Distinguished Researcher, and Dr. Yukiko Takahashi, Group Leader of NIMS Center for Magnetic and Spintronics Materials Research, Dr. T.Y. Chang, Researcher at Seagate Technology, and Prof. S.J. Greaves of Tohoku University. This work was supported by Japan Science and Technology Agency (JST) Strategic Basic Research Programs (CREST) "Integrated Devices and Systems Utilizing Information Carriers" JPMJCR22C3.

6. This research was published in Acta Materialia on March 24, 2024.

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JOURNAL

Acta Materialia

DOI

10.1016/j.actamat.2024.119869 

METHOD OF RESEARCH

Experimental study