Sunday, July 26, 2026

 

From heat dissipation bottlenecks to designable thermal functional units: interfacial heat transport in two-dimensional materials







Science Exploration Press
Interfacial heat transport in 2D heterostructures as a designable degree of freedom. 

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2D heterointerfaces can be formed as vertically stacked van der Waals interfaces or laterally stitched in-plane junctions. Their thermal behavior is determined by a sequence of linked processes. Interface formation through direct growth or transfer assembly defines the initial structure and quality of the boundary. Thermal metrology, including optical, electrical and mapping-based approaches, enables interfacial heat transport to be quantified. Microscopic mechanisms such as elastic transmission, inelastic scattering and interface-specific phonon modes govern how vibrational energy crosses or is redistributed at the interface. These mechanisms can be modified through intrinsic and external tuning strategies, including interface geometry, strain, twist and intercalation. When such tunability is connected to device operation, 2D heterointerfaces can move beyond passive heat dissipation toward thermal functionality, including rectification, switching and transistor-like heat-flow control. 2D: two-dimensional; TDTR: time-domain thermoreflectance.

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Credit: © Xing Zhang, et al. 2026. This is an Open Access article licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, sharing, adaptation, distribution and reproduction in any medium or format, for any purpose, even commercially, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.





As chips and electronic devices continue to evolve toward greater miniaturization and higher integration, heat generation becomes increasingly localized while heat dissipation becomes progressively more challenging. In heterostructures composed of two-dimensional (2D) materials, heat must often traverse atomically thin interfaces before being dissipated into the surrounding environment. Consequently, interfacial thermal transport has become a key factor governing device performance, operational stability, and long-term reliability.

Recently, researchers presented a comprehensive Perspective on interfacial thermal transport in 2D heterostructures, systematically reviewing recent advances in the field and outlining future research directions. The article establishes an integrated framework for understanding interfacial heat transport by examining interface formation, thermal transport characterization, phonon transport mechanisms, interface engineering strategies, and thermal functional devices.

The authors argue that interfaces in 2D heterostructures should no longer be regarded merely as unavoidable boundaries for heat flow, but rather as designable and tunable thermal functional units. The mode of interface formation directly determines the actual contact configuration, interlayer coupling, and ultimately the interfacial thermal conductance. Consequently, the interfacial structure established during material synthesis fundamentally determines the subsequent thermal transport behavior.

To elucidate how heat traverses atomically thin interfaces, the Perspective further reviews the principal experimental techniques for characterizing interfacial thermal transport, including Raman thermometry, time-domain and frequency-domain thermoreflectance (TDTR/FDTR), and electrical thermal measurements based on micro- and nanoscale device platforms. The authors compare the advantages and limitations of these techniques in terms of spatial resolution, structural applicability, and measurement accuracy.

The authors further point out that future advances in interfacial thermal metrology will require the integration of high-spatial-resolution and high-temporal-resolution measurements with in situ device characterization to accurately probe heat transport under realistic operating conditions. Regarding the underlying transport mechanisms, the article emphasizes that heat transfer across 2D heterointerfaces is fundamentally governed by phonon transmission across the interface, involving elastic transmission, inelastic scattering, and interface-specific localized phonon modes.

The Perspective also highlights that maximizing interfacial thermal conductance is not always the optimal objective. Instead, thermal transport should be tailored to the functional requirements of specific devices. By tuning parameters such as twist angle, strain, pressure, ion intercalation, defects, and interfacial chemical modification, interfacial heat flow can be actively manipulated to realize thermal rectification, thermal switches, thermal transistors, and other thermal functional devices, thereby providing new strategies for active thermal management.

Overall, two-dimensional heterostructures offer a unique platform for advancing interfacial thermal transport, enabling atomically thin interfaces to evolve from conventional heat dissipation bottlenecks into designable, measurable, and tunable thermal functional units. This paradigm shift is expected to underpin the development of next-generation electronic and thermal functional devices.

 

Scientists turn modern biobanks into a new window on human evolution




National Yang Ming Chiao Tung University
Age-stratified allele-frequency trajectories uncover ongoing selection 

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By tracking allele-frequency changes across adult age groups, researchers identified ongoing natural selection acting on rare genetic variants linked to human disease, providing new insights into human evolution and precision medicine.

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Credit: National Yang Ming Chiao Tung University





For more than a century, scientists have sought to reconstruct human evolution using diverse lines of evidence, including fossils, genetic variation across populations, and ancient DNA. Building on these approaches, researchers are increasingly using large population biobanks to investigate how natural selection continues to shape the genomes of living populations.

 

In a new study, researchers analyzed genomic data from over 72,000 Han Taiwanese participants in the Taiwan Biobank by comparing allele frequencies across adult age groups. This analytic framework enabled them to identify genomic signatures of ongoing natural selection and uncover disease-associated genetic variants that may otherwise have gone undetected.

 

Published in The American Journal of Human Genetics, the study shows that large biobanks can function not only as tools for precision medicine but also as platforms for examining modern human evolution. The researchers suggest this framework could be used globally, providing new chances to identify medically relevant genetic variants in different populations.

 

“One of the most exciting aspects of this study was seeing how age-stratified allele-frequency trajectories could reveal ongoing natural selection in a contemporary population,” said first author Jing-Lian Chen, formerly a master's student in Dr. Wen-Ya Ko's laboratory at National Yang Ming Chiao Tung University in Taiwan. “This approach complements existing methods and helps uncover disease-associated variants that might otherwise remain undetected.”

 

"Biobanks are usually viewed as resources for studying disease," said corresponding author Dr. Wen-Ya Ko. " Our study demonstrates that these same resources can also help uncover how ongoing natural selection continues to shape disease-related genetic variation. This creates new opportunities to integrate evolutionary biology with precision medicine."

 

Finding rare disease variants that conventional studies often miss

The researchers examined 509,817 genome-wide variants in 72,635 Han Taiwanese individuals aged 24 to 70. Instead of targeting genes linked to specific diseases, they investigated whether certain inherited variants consistently increased or decreased in frequency across various adult age groups.

 

Their analysis revealed 168 variants that deviated from neutral expectations, with 159 displaying signs of ongoing purifying selection, an evolutionary process that gradually eliminates harmful genetic variants. Notably, about 90% of these variants were extremely rare, indicating that the approach can detect evolutionary signals that previous selection scans, which mainly focused on common variants, might miss.

 

Many of these rare variants were previously linked to inherited disorders. Seventy-one are classified as pathogenic or likely pathogenic in ClinVar, with many others associated with cancer, neurological conditions, cardiovascular problems, kidney disease, and other serious health issues. The identification of these medically relevant variants indicates that evolutionary analyses can be valuable in prioritizing mutations that cause disease for future research.

 

 

Unexpected evolutionary patterns in BRCA1 and DNA repair genes

One of the most notable discoveries was an unexpected evolutionary pattern involving BRCA1, a well-known cancer susceptibility gene. Researchers identified a rare BRCA1 haplotype carrying 16 protein-altering variants, of which 15 are already classified as pathogenic. This haplotype seems to be under purifying selection, gradually becoming less common in the population.

 

Interestingly, regions near BRCA1, as well as BRCA2 and MLH1, indicated evidence of positive selection. This suggests that different variants within the same DNA repair genes have experienced distinct forms of natural selection over evolutionary time. Rather than conflicting, these results highlight the complex interplay between genetic variants that increase disease risk and those that may have conferred advantages in past environments.

 

"Evolution rarely acts on genes in a straightforward manner," said Prof. Yoko Satta of SOKENDAI (The Graduate University for Advanced Studies), Japan. "A variant increasing disease risk now might have been beneficial in a different environmental context earlier. Understanding these evolutionary trade-offs enhances our interpretation of disease-related variants in current populations."

 

One gene, many health effects

The study also found evidence that natural selection might favor genes impacting multiple facets of human biology. Two genes, ATG9A and FADS2, demonstrated significant pleiotropy, where a single gene influences numerous seemingly unrelated traits. Variations in these genes were linked to blood cell characteristics, liver and kidney functions, lipid metabolism, diabetes-related traits, cardiovascular metrics, and bone density. This extensive biological influence may explain why these regions are recurrently influenced by natural selection; changing one gene can impact many physiological systems at once. This finding indicates that evolutionary research can help identify genes at central points of human biology, making them promising targets for future functional and clinical studies.

 

 

Red blood cells emerge as a shared evolutionary signature

Although the candidate variants are spread across the genome and occur in genes with diverse biological functions, many converge on a common physiological pattern. About 150 variants consistently associate with red blood cell traits, particularly increased mean corpuscular volume and reduced mean corpuscular hemoglobin concentration. The researchers propose that this pattern may be due to historical adaptation to infectious diseases like malaria, which was once widespread in Taiwan. While further research is necessary to confirm the exact mechanism, this discovery highlights how evolutionary pressures can shape similar physiological traits through genetic variation across multiple genes, rather than affecting single variants in isolation.

 

 

Toward more representative precision medicine

Beyond individual discoveries, the researchers see the greatest impact in showcasing a new analytical framework adaptable to other large-scale genomic datasets. Most existing genomic reference datasets are skewed toward populations of European ancestry. Applying this framework to one of the world's largest Han Taiwanese cohorts demonstrates how population-specific evolutionary histories can uncover medically significant variants that might otherwise go unnoticed. As more nations develop national biobanks, this approach could be expanded globally to better understand the ongoing influence of evolution on human health across diverse populations.

 

"Human evolution did not cease thousands of years ago," the scientists stated. "Living populations still bear its genetic imprints. Combining large biobanks with advanced genomic analysis offers a powerful new method to explore how evolution continues to shape health, disease, and human diversity."

 

Venture-backed maternal health startups and the US maternal health crisis



JAMA Health Forum


About the study: 

How many venture capital-backed maternal health startups exist in the US and what are their characteristics and purpose? In this cross-sectional study of 172 venture capital–backed maternal health startups identified from 2014 to 2022, $977.5 million was collectively raised during the study period and the health care category raising the most capital was maternal and fetal health diagnostics ($520.1 million). The most common company type was virtual or hybrid wraparound pregnancy care and few startups mentioned health equity or maternal mortality or accepted Medicaid. Results of this study suggest that venture capital–backed startups are filling gaps in pregnancy care delivery and while startups have the potential to facilitate needed innovation, few focus on low-income populations or health equity.


Corresponding Author: Madeline F. Perry, MD, Hospital of the University of Pennsylvania, 423 Guardian Dr, Philadelphia, PA 19104 (mfrancesperry@gmail.com).

10.1001/jamahealthforum.2026.2324

To access the embargoed study: Visit our JAMA Network Media Center website at this link https://media.jamanetwork.com/

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Time of day of influenza vaccination and subsequent influenza risk



JAMA Network Open


About the study: This cross-sectional study examines whether time of day of influenza vaccination is associated with differences in vaccine effectiveness.


Corresponding Author: Anupam B. Jena, MD, PhD, Department of Health Care Policy, Harvard Medical School, 180 Longwood Ave, Boston, MA 02115 (jena@hcp.med.harvard.edu).

10.1001/jamanetworkopen.2026.25267

To access the embargoed study: Visit our JAMA Network Media Center website at this link https://media.jamanetwork.com/

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Wildfire-sourced PM and emergency department visits for migraine and other primary headache


JAMA Network Open


About the study:

Is exposure to wildfire-sourced fine particulate matter with an aerodynamic diameter of 2.5 μm or less (PM 2.5) associated with emergency department (ED) visits for migraine and other primary headache syndromes? In this case-crossover study of 997 701 ED visits in Alberta and Ontario, Canada, between 2010 and 2023, wildfire-sourced PM 2.5 was significantly associated with a 6% increase in ED visits for migraine and other primary headache syndromes. Associations were attenuated in the least materially and socially deprived areas, and no significant association was observed for PM 2.5 on nonwildfire days. These findings suggest that wildfire-sourced PM 2.5 may precede severe headache episodes requiring ED care.


Corresponding Author: Sabit Cakmak, PhD, Health Canada, Environmental Health Science sabit.cakmak@hc-sc.gc.ca.

10.1001/jamanetworkopen.2026.25015

To access the embargoed study: Visit our JAMA Network Media Center website at this link https://media.jamanetwork.com/

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Advancing efficient AI workflows



Harvard-developed automation system receives boost from Laude Institute



Harvard John A. Paulson School of Engineering and Applied Sciences






Your online order arrives damaged, so you request a refund. What often follows is an artificial intelligence workflow involving multiple AI models: One model checks your request against company policy, another analyzes the image you uploaded, and yet another drafts a response.

Since many of today’s AI applications no longer rely on a single model, engineers must custom-build these increasingly complex products — deciding what model should handle each step, and how they should coordinate. Researchers at the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) have something more streamlined in mind.  

A team led by Minlan Yu, the Gordon McKay Professor of Computer Science; and Michael Mitzenmacher, the Thomas Watson, Sr. Professor of Computer Science, with postdoctoral fellow Rana Shahout and Boston University software developer Hayder Tirmazi, are developing a new AI framework called Orla that simplifies building and running AI workflows while automatically optimizing them for cost, accuracy, and speed. Engineers simply describe the workflow they want, and Orla determines how best to execute it.

The project was recently funded by the nonprofit Laude Institute with a Slingshot award, which supports computer scientists building foundational AI infrastructure. 

For the Harvard team, Orla is part of a broader effort to bring together computer systems and theoretical ideas to tackle emerging AI challenges. Previous work by the same group focused on scheduling, load balancing, and memory management for AI inference. 

“As AI evolves from individual models to teams of collaborating agents, we’re applying those same ideas to managing entire AI workflows,” said Shahout, lead author of a recent demo paper on Orla presented at the ACM Conference on AI and Agentic Systems.

In tests, Orla reduced computing costs and response times without sacrificing the quality of the answers. As AI applications continue to grow in complexity, the researchers believe systems like Orla could make them more practical to build and operate at scale.

Learn more: 

Orla: A Library for Serving LLM-Based Multi-Agent Systems
Don’t stop me now: Embedding based scheduling for LLMs 
Queueing, predictions, and large language models: Challenges and open problems
Fast inference for augmented large language models


 

Oh, snap: Fabrics with multiple stable shapes



Researchers create knit textiles for switches, step counting



Harvard John A. Paulson School of Engineering and Applied Sciences

micro_1 

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The researchers used highly elastic yarns to create dense textiles that snap into different configurations. 

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Credit: Kausalya Mahadevan / Harvard SEAS






Knitting has come a long way from sweaters and blankets. 

Researchers at the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) have turned everyday knitting into a powerful platform for making shape-shifting devices that can act as switches, sensors, and more — paving the way to next-generation functional, programmable textiles. 

The researchers created unique, machine-knitted fabrics that “snap” between multiple stable shapes, exhibiting a quality known to physicists as multistability. The work was led by recent Ph.D. graduate Kausalya Mahadevan, currently a postdoctoral associate in the lab of Katia Bertoldi, the William and Ami Kuan Danoff Professor of Applied Mechanics. The research is published in Advanced Functional Materials.  

“I’ve always been excited about fabrics and textiles, and what we can engineer and build with them,” said Mahadevan, who began working in Bertoldi’s lab as an undergraduate. “Our ideas around multistability in textiles arose from being inspired by textile artists and how they approach structures, combined with how [Bertoldi’s] lab has traditionally thought about nonlinear mechanics in solids. We tried to approach thinking about textiles in that context.” 

Structures that curve and retain their shape are more typically molded from polymers and created by carefully programming residual stress within the material. In the new study, the researchers show that weft knitting – the same industrial process used for making hats and gloves – can generate more complex curvatures with nothing but yarn. 

They chose highly elastic yarns and employed a technique called plating, which exposes different yarns on each face of the fabric. They were able to produce dense, thick textiles that naturally curl into three-dimensional shapes, exploiting the same basic mechanism of when a cut T-shirt curls up from the bottom. 

“The yarn selection and machine parameter choices allowed us to basically select a fabric that is going to be as snappy as we can possibly get,” Mahadevan said. 

By systematically combining horizontal and vertical stripes, they built fabrics that snap and settle into more than one stable configuration, like how a light switch has an on and off function. By mapping how geometry and material choice affected the snap-through behavior, they identified the physical regimes in which their knitted textiles became multistable. They were also able to accurately model the textiles’ behavior using simulations that treat the textile as a continuous material, rather than tracking each individual yarn. 

To demonstrate potential applications, the researchers embedded fine conductive yarns into their knits, turning the fabrics into soft, stretchable, electric switches that change state as the textile snaps back and forth. 

They created, for example, a multistable knitted shell shape that turns an LED on and off as it flips between states. They also made a wearable textile switch that, when mounted over the knee or elbow, creates a snapping motion can be read by an Arduino to count steps. Finally, they designed a reconfigurable lamp shade with three separate multistable switches, each controlling a different color of light as the fabric stretches and snaps. These and other devices were the subject of a recent Art Lab installation

The researchers made a reconfigurable lamp shade with multistable switches that correspond to different colors of light. 

The machines Mahadevan and the team used are similar to standard industrial knitting machines in garment factories, pointing to rapid scalability of future devices. 

Scientifically, the project edges textiles closer to the broader field of nonlinear mechanical metamaterials, where structures are engineered to bend, buckle and snap in useful ways. Looking ahead, Mahadevan is intrigued by the possibilities of using multistable control to design textiles that are soft, seamless and functional. The team envisions fabrics that unobtrusively monitor movement, provide tactile feedback, or even morph into new shapes on demand. 

The research was supported by NSF grant DMR-2011754 and ARO MURI program W911NF-22-1-0219. Equipment was supported by ONR DURIP Award N00014-19-1-2220. 


knitting_fabric [VIDEO] 

 

UofL, Norton led study helps opioid-exposed newborns recover sooner




University of Louisville






A major new study shows that individualized treatment for babies born with opioid withdrawal can speed recovery and reduce time spent in the hospital.

The clinical trial led by Lori A. Devlin, professor in the University of Louisville School of Medicine Department of Pediatrics and neonatologist with Norton Children’s, found a customized approach to treating babies with opioid withdrawal helps them recover faster than current standardized practices.

The findings were recently published in the Journal of the American Medical Association (JAMA), one of the nation’s leading medical journals. More than 100 researchers across the country contributed to the study.

Every year, over 1,000 Kentucky babies are born with neonatal opioid withdrawal syndrome (NOWS). The syndrome can develop when mothers ingest opioids during pregnancy, causing the infant to experience withdrawal symptoms after birth. Those symptoms can include irritability, difficulty with feeding and sleeping concerns.

The study compared two treatments: a fixed medication schedule and a symptom-based approach that adjusts care based on the severity of each infant’s symptoms. Results showed babies treated with the symptom-based approach recovered faster.

When this individualized treatment was combined with the Eat, Sleep, Console (ESC) model of care – which includes family involvement, holding and swaddling before prescribing medication – infants with NOWS left the hospital an average of 2.3 days sooner. Notably, 65% of babies treated with this approach did not need scheduled opioid medications and gradual weaning.

“These findings confirm that ESC, combined with symptom-based dosing, helps babies recover faster and reduces unnecessary medication exposure,” Devlin said. “This work represents a true team effort involving researchers, nurses, administrators and families across the nation, including our team at Norton Children’s Research Institute and the UofL Department of Pediatrics.”

Nearly two dozen hospitals nationwide participated in the study, including neonatal intensive care units (NICU) at Norton Children’s Hospital, Norton Women’s & Children’s Hospital and UofL Hospital.

The study builds on more than a decade of research aimed at improving care for infants with NOWS. Devlin previously led the ESC-NOW trial that showed using the family-centered ESC approach reduced hospital stays by about a week and decreased the need for medication from 52% to 19%.

“This research is actively changing how babies with NOWS are treated around the world,” Devlin said. “Our team is currently conducting another multicenter study to determine the best type of medication for NOWS.”

UofL faculty members Sucheta Telang, Scott Duncan and Ryan Smith were co-authors on the study. 

The study was funded by the National Institutes of Health (NIH), with support from the Eunice Kennedy Shriver National Institute of Child Health and Human Development and the NIH HEAL (Helping to End Addiction Long-term) Initiative.