The study, published in the Journal of Materials Science by Mahdieh Sabbaghian and Mohammad Zaman Kabir, focuses on a copper-aluminum-manganese alloy with a composition of 15.8 percent aluminum and 11 percent manganese by atomic fraction. Copper-based shape memory alloys have attracted attention for decades precisely because their raw materials are cheap and abundant compared with nickel and titanium. Yet they have historically suffered from a critical weakness: in polycrystalline form, meaning materials made of many small crystals rather than a single crystal, they tend to crack along grain boundaries during repeated elastic cycling. The intergranular brittleness has been the Achilles heel that kept them confined to laboratory curiosities and niche applications.

The Iranian team approached this challenge through the lens of thermomechanical processing, the art and science of combining heat treatment with mechanical deformation to sculpt a material’s internal structure. They compared several processing routes applied to the same base alloy: hot rolling followed by quenching, conventional annealing, and a more exotic procedure called cyclic heat treatment, in which the material is repeatedly heated and cooled through a critical temperature range. Each route leaves a distinct fingerprint on the microstructure, and the researchers set out to map exactly how those fingerprints translate into functional performance.

Characterization was carried out with an impressive battery of techniques. Differential scanning calorimetry measured the temperatures at which the alloy transforms between its high-temperature austenite phase and its low-temperature martensite phase, the reversible crystallographic shift that underpins all shape memory behavior. X-ray diffraction identified the phases present, while optical and scanning electron microscopy revealed the grain structures, and microhardness testing probed local mechanical resistance. Superelasticity itself was evaluated through cyclic tensile testing, in which specimens are stretched and unloaded repeatedly while stress-strain curves are recorded, and the shape memory effect was assessed through bending recovery experiments in which pre-strained samples are heated and their recovery angle measured.

The physics here deserves a moment of explanation. Superelasticity is not ordinary elasticity. In a superelastic alloy, applying stress at a temperature above the austenite finish temperature triggers a stress-induced transformation from austenite to martensite. The material yields at a nearly constant stress plateau as the transformation proceeds, absorbing enormous strain, sometimes several percent, which would permanently deform an ordinary metal. When the load is removed, the martensite becomes unstable and reverts to austenite, and the material snaps back almost completely. The catch is that this reversible transformation must sweep through entire grains without generating damaging stress concentrations at grain boundaries. Large grains, and ideally single crystals, make this far easier, which is why grain size control is the central battleground for polycrystalline shape memory alloys.

This is where cyclic heat treatment enters the story, and it is the most striking part of the new work. The technique, pioneered by researchers including Takashi Omori and Ryosuke Kainuma at Tohoku University, exploits a phenomenon called abnormal grain growth. Under normal circumstances, heating a metal causes its grains to grow uniformly and modestly. But under specific cyclic conditions, a select few grains develop a growth advantage, consuming their neighbors until they dominate the entire microstructure. The result can be grains centimeters long, effectively transforming a polycrystal into an oligocrystal or even a single crystal without any of the expensive directional solidification or crystal-pulling methods traditionally required. The mechanism is thought to involve the repeated dissolution and reprecipitation of phases during each thermal cycle, which selectively favors grains with particular orientations or defect structures.

Applying cyclic heat treatment to their Cu-Al-Mn alloy, the researchers achieved dramatic results. Differential scanning calorimetry of the treated specimens revealed austenite finish temperatures below zero degrees Celsius, a crucial finding because it means the alloy is fully austenitic, and therefore superelastic, at room temperature. Cyclic tensile testing then showed that the cyclically heat treated material exhibited pronounced superelasticity, with a recoverable strain of 6.24 percent, more than five times that of the untreated control specimen. For a polycrystalline copper-based alloy, that is an extraordinary figure, and it demonstrates that the abnormal grain growth strategy transfers effectively from the iron-manganese-aluminum-nickel systems where it was first demonstrated to the copper-based family.

Hot rolling, meanwhile, delivered a different but complementary set of benefits. The rolled specimens showed ultimate tensile strength and cumulative energy density to fracture increased by approximately 74 percent and 39 percent respectively compared with the control. Rolling refines the microstructure, breaks up casting defects, and can introduce beneficial texture, aligning the crystallographic grains in ways that accommodate the transformation strain more gracefully. The most exciting result, however, came from combining the two processes. A route that paired hot rolling with cyclic heat treatment promoted pronounced abnormal grain growth while simultaneously enhancing strength, ductility, and superelasticity, yielding an ultimate tensile strength of up to 572 megapascals, a total strain at fracture of up to 15.4 percent, and a recoverable superelastic strain of up to 6.86 percent. Achieving all three properties together is rare; usually improving one comes at the expense of another.

The implications extend well beyond the laboratory. Shape memory alloys are increasingly specified in civil infrastructure, where their superelasticity allows them to absorb seismic energy and re-center structures after earthquakes, and where their shape memory effect lets them apply permanent prestressing forces to concrete elements as they are heated. Reviews of the field have highlighted applications ranging from bridge shear reinforcement to column retrofitting and vibration damping systems. In these large-scale structural uses, the cost of nickel-titanium is often prohibitive, since tonnage quantities would be required. A copper-based alternative with competitive functional properties, produced from inexpensive raw materials through conventional rolling and furnace treatments, could change the economics of resilient infrastructure design entirely.

There are, of course, questions that future work must address. Cyclic heat treatment schedules can be time-consuming, and scaling the abnormal grain growth process from laboratory coupons to commercial bar and plate stock will demand careful process control. Fatigue behavior over thousands of superelastic cycles, corrosion resistance in realistic environments, and compatibility with welding and joining methods all remain to be fully characterized for the processed alloy. Still, the demonstration that a simple combination of rolling and thermal cycling can coax a cheap copper alloy into delivering nearly seven percent recoverable strain alongside 572 megapascals of strength marks a genuine advance. It suggests that the era of superelastic metals may not belong exclusively to nickel and titanium after all, and that with clever processing, some of the oldest and most familiar metals in human history still have remarkable new tricks to teach us.

Subject of Research: Thermomechanical processing and cyclic heat treatment of Cu–Al–Mn shape memory alloys to enhance superelasticity

Article Title: Adapting superelasticity in Cu–Al–Mn shape memory alloys via thermomechanical processing and cyclic heat treatment

Article References: Sabbaghian, M., & Kabir, M. Z. (2026). Adapting superelasticity in Cu–Al–Mn shape memory alloys via thermomechanical processing and cyclic heat treatment. Journal of Materials Science, 61(43), 34049-34087. https://doi.org/10.1007/s10853-026-13738-0

Image Credits: AI Generated

DOI: 10.1007/s10853-026-13738-0

Keywords: shape memory alloys, superelasticity, Cu–Al–Mn, cyclic heat treatment, abnormal grain growth, thermomechanical processing, hot rolling, martensitic transformation, grain size, structural materials, seismic resilience, Journal of Materials Science

Research Units are one of the DFG’s principal instruments for supporting coordinated, multi-site collaboration. They allow teams at different institutions to pursue pressing questions in their fields and to take innovative directions that would be difficult to achieve within the boundaries of individual projects. Funding can run for up to eight years, distributed across successive periods that each depend on favourable external evaluation. With the latest decisions, the DFG is currently supporting 191 Research Units, seven Clinical Research Units and 15 Centres for Advanced Studies in Humanities and Social Sciences. Clinical Research Units are distinguished by the close coupling of laboratory research with clinical practice, while the Centres for Advanced Studies are tailored specifically to the working methods of the humanities and social sciences, where sustained reflection and theory development often matter as much as data collection.

The new units span a striking range of disciplines, from environmental history and communication studies to neuroscience, climate law, nutritional physiology, materials science, psychology, dermatology and early modern philology. Their breadth illustrates the DFG’s competitive, bottom-up funding model, in which researchers themselves define the questions and assemble consortia that are then assessed in a rigorous peer review process. What follows is a survey of the nine new networks, each of which will bring together specialists from multiple institutions under a designated spokesperson.

Wetlands, long treated in European history as sinister and unproductive spaces to be drained and cultivated, are the subject of a unit based at the University of Augsburg. Today these transition zones are recognised as vital carbon sinks, coastal shields and natural water filters, yet the cultural history of how people related to them remains poorly understood. Working within the environmental humanities, the unit Thinking with wetlands. Histories from the quaking zone 1630-1997, led by Professor Simone Müller, will examine the ambivalent experiences, contested visions and shifting terminology that shaped the human-wetland relationship in Central and Western Europe. Its aim is to reconstruct how communities lived and thought with swamps, drew philosophical inspiration from them and, remarkably early in industrial history, began campaigning for their protection. The project promises to connect environmental science debates about peatland restoration with a much longer intellectual and social history.

At the Freie Universität Berlin, Professor Margreth Lünenborg will lead a unit on Media Practices of Contradicting in Networked Publics. The network approaches contradiction as a relational and dynamic form of communication through which people who have been disadvantaged socially, economically or culturally raise their voices against dominance they perceive as hegemonic. Beyond the discursive practices by which media convey dissenting content, the researchers will analyse the digital conditions, including social media platforms, that have fundamentally reshaped such practices. They will also study material and creative forms of contradiction in which the media themselves, as organisations, infrastructures and technologies, become the object of dissent. The work is expected to sharpen theoretical and empirical tools for understanding protest communication in contemporary networked publics.

Neuroscience is represented by a unit at the University of Bonn led by Professor Christian Henneberger, entitled Inside and outside the synapse: Challenging dogmas of synaptic signalling and neuromodulation. Information in the nervous system travels not only through highly targeted communication at synapses but also via messenger substances whose effects extend beyond the boundaries of individual synaptic contacts. Recent research increasingly reveals the diversity and dynamic character of the interplay between these signalling pathways. The unit will investigate how nervous tissue filters and translates incoming information and converts it into electrical and chemical activity, with the explicit aim of reviewing established ideas about synaptic transmission and broadening understanding of information processing in the brain. Better models of neuromodulation could ultimately inform how neuroscientists interpret everything from learning to the action of psychoactive drugs.

Legal scholarship enters the portfolio through a University of Bremen unit led by Professor Claudio Franzius on Transformative climate law: space – time – society. Germany’s Federal Climate Change Act commits the country to complete climate neutrality by 2045, a goal that demands a clear, legally binding roadmap for fundamental changes to the economy and society. The unit’s central premise is that the question of how legislation can drive such a transformation is itself transforming the legal system. Researchers will examine the economic, environmental and social dimensions of the transition to climate neutrality, seeking to identify the new framework required for effective, future-oriented and therefore sustainable climate law. The findings could influence how legislatures across Europe structure decarbonisation mandates.

A jointly funded D-A-CH unit at Dresden University of Technology, led by Professor Klaus Reinhardt in cooperation with the Swiss National Science Foundation, will study heat-treated dietary lipids, abbreviated HTDL. Humans are the only known species to process food with heat, and while cooking makes food easier to digest it also triggers metabolic and physiological changes, for example through altered lipid compounds in dietary fats. Little is known so far about the bioactivity of these compounds. The unit will test whether heat treatment changes lipidomes, the complete lipid inventories of organisms, along with membrane and biophysical properties of cells, neurometabolic processes, metabolic signalling pathways and reproductive processes. It will even ask whether such changes can alter the evolution of organisms that consume heat-treated fats, connecting food chemistry with physiology and evolutionary biology in an unusually ambitious synthesis.

Materials science gains a unit at the University of Kassel under Professor Thomas Niendorf focused on iron-based shape-memory alloys. These materials could open new component-design applications compared with established nickel-titanium alloys, yet their various shape-memory effects have largely been considered and exploited separately, and no suitable alloy design exists for combining them systematically in products. The unit Combined effects in Fe-based shape memory alloys – Model-driven alloy design taking into account process-microstructure-property relationships aims to investigate these combined effects in depth, develop high-performance alloys through model-driven design and build a fundamental understanding of the underlying mechanisms. Because iron-based alloys are cheaper and more workable than nickel-titanium, success could broaden shape-memory technology from niche actuators toward large-scale engineering applications.

Psychology and communication studies converge in a University of Mainz unit led by Professor Roland Imhoff, Beyond Crazy: Integrating Benefits into the Analysis of Conspiracy Beliefs. Previous research has concentrated almost exclusively on the harmful consequences of conspiracy thinking, but this network asks what potential functions and benefits such beliefs may offer their adherents. By investigating these functions systematically from psychological and societal perspectives, the unit hopes to explain the popularity and enduring appeal of conspiracy theories more convincingly and to advance the methodological development of the field. The reframing is intended to produce a more nuanced theoretical understanding rather than to trivialise the real dangers of conspiratorial narratives.

Medicine and history complete the list. At the University of Tübingen, Professor Claudia Günther will lead a unit on the immunopathology of cutaneous lupus erythematosus, an autoimmune skin disease that appears in several forms and can cause severe scarring and hair loss, profoundly affecting patients’ quality of life. No therapies beyond glucocorticosteroids, commonly known as cortisone, have been approved for the condition, and its molecular mechanisms and observable subtypes remain inadequately defined. The unit aims to close these gaps and lay foundations for future treatments. Finally, at the University of Würzburg, Professor Regina Toepfer will direct a unit on ‘Alternative Facts’ in the Sixteenth Century, tracing a phenomenon named during Donald Trump’s first presidency back to the early modern period, an era that shaped Europe’s understanding of itself and its media landscape. The unit defines alternative facts as a linguistic practice that challenges accepted standards of knowledge and deliberately undermines them through competing claims in rhetoric, religion or politics, in order to obstruct dialogue, disrupt discourse, create uncertainty or stage particular narratives. Together, the nine networks demonstrate how competitive funding can connect the deepest historical questions with the most immediate challenges of climate, health and democratic communication.

Subject of Research: DFG funding of nine new interdisciplinary Research Units and extensions of existing networks

Article Title: DFG to fund nine new research units

Article References: DFG to fund nine new research units. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: DFG, Research Units, research funding, Germany, climate law, neuroscience, shape-memory alloys, conspiracy beliefs, cutaneous lupus, wetlands, heat-treated dietary lipids, alternative facts

Microjoining, as the authors define it, covers the joining of thin sheets up to 0.5 millimeters thick and fine wires with diameters no greater than one millimeter. The scale is not merely a smaller version of conventional welding. At these dimensions, physics itself changes character. Surface and interfacial effects begin to dominate bulk behavior, capillary forces can overwhelm gravity, and the limited material volume means heat transfer and solidification kinetics behave in ways that defy macroscale intuition. The result is that micro-joints carry thermal stresses and microstructures fundamentally different from their large-scale counterparts, making microjoining a discipline that demands its own scientific foundation rather than a simple downscaling of established practice.

The range of materials involved is striking. Metals remain the workhorses of the field, with stainless steel, titanium and magnesium alloys long favored for their mechanical performance, biocompatibility and cost-effectiveness. Stainless steel has served in surgical implants since the 1920s, but modern demands have pushed far beyond. Shape-memory alloys, particularly nickel-titanium or NiTi, owe their indispensability to reversible martensitic phase transformations that produce the shape memory effect and superelasticity, properties exploited in orthodontic archwires, stents and guidewires. Laser microwelding between NiTi microtubes and platinum-iridium wires has even been used to tailor transformation temperatures for specific device needs. Biodegradable magnesium and zinc alloys, noble metals such as gold, silver and platinum that enhance X-ray visibility, and refractory metals like niobium that serve as biocompatible intermediates round out an expanding metallic palette.

Polymers and composites bring their own advantages, particularly deformability, corrosion resistance and machinability. Laser welding has successfully bonded three-dimensional polymer fabrics for orthopedic applications, achieving reliable fiber-to-fiber joints without surface damage. Researchers have also microjoined polymers to dissimilar materials, as in polyimide-titanium and PETG-stainless steel systems, and integrated metal-coated chips into the inner surfaces of polymer stents. Commercially, the FARAWAVE pulsed field ablation catheter relies on joining metal-ring electrodes to polymer wires, balancing flexible motion with X-ray mapping capability. The looming replacement of PFAS with environmentally sustainable polymers, the authors note, may create new joining challenges as unfamiliar materials enter the production pipeline.

Ceramics present the steepest hurdles. Bioinert oxides and nitrides, bioresorbable calcium phosphates and bioactive glasses are prized for bone and dental restoration, but their high melting points and poor deformability restrict both fusion and solid-state joining at the microscale. Soldering, brazing and adhesive bonding dominate instead. Implantable neural stimulators demonstrate the feasibility of micro-brazing platinum-iridium pins into ceramic substrates, and hermetically packaged neurostimulation devices have been built by co-firing ceramics with platinum tracks, pointing toward a ceramic-rich future for next-generation implantables.

Four families of joining methods have been adapted to the microscale. Fusion welding, the most widely used, employs laser beams, electron beams, plasma arcs or contact-based resistance heating to melt and re-solidify base materials. Laser microwelding leads the field thanks to its high energy density and precise controllability. Yet fusion welding of dissimilar metals reveals the discipline’s central difficulty: when NiTi wires are laser welded to stainless steel, rapid heating and cooling produce uneven mixing and non-equilibrium solidification, filling the fusion zone with brittle intermetallic compounds that cripple joint strength. Resistance microwelding offers an elegant workaround. Using miniature copper-chromium electrodes roughly one millimeter in diameter, researchers have squeezed molten liquid out of the interface entirely, achieving quasi-solid-state direct bonding between NiTi and stainless steel while preserving flexible deformability on one side and superelasticity on the other.

Solid-state welding sidesteps melting altogether, relying on interdiffusion under pressure through friction, ultrasonic vibration or diffusion bonding. Ultrasonic microwelding of thin titanium sheets produces interfacial regions less than five micrometers thick, while vapor foil actuator welding joins NiTi wires to brass sheets without significant alloy intermixing, suppressing intermetallic formation. Brazing and soldering with low-melting-point fillers enable complex configurations, exemplified by furnace micro-brazing of shape-memory alloy wires into honeycomb stent architectures that retain superelastic response, and laser micro-brazing of platinum rings to copper-coated stainless steel wires for interventional devices requiring both radiopacity and signal feedback. Adhesive bonding remains indispensable for assembling thermoplastic microfluidic substrates used in bioanalysis and diagnostics, though surface preparation through plasma cleaning proves critical to joint quality.

Evaluating micro-joints for biomedical service requires far more than simple strength measurements. Digital image correlation has revealed high strain localization around weld nuggets in resistance-welded shape-memory alloy sheets, identifying crack nucleation sites, while scanning electron microscopy enables in-situ testing of wire joints too small for optical strain mapping. Functional performance matters as much as mechanics: arc-welded NiTi wires show markedly increased residual strain during superelastic cycling compared with base material, attributed to grain coarsening and microstructural evolution in the weld zone. Thermomechanical fatigue testing under cyclic martensitic transformations shows welded joints suffer reduced fatigue life, though post-weld heat treatment can homogenize microstructure and restore durability. Corrosion and biocompatibility add further complexity, with studies showing that beneficial alloying element mixing during fusion welding can improve passive film formation, while toxic elements like copper, cobalt and nickel must be rigorously avoided.

The perspective outlines four frontiers for the coming decade. Smart devices such as MEMS sensor-equipped fractional flow reserve guidewires will demand increasingly sophisticated multi-material joining strategies combining soldering, adhesive bonding and fusion welding in a single assembly. Process optimization offers immediate gains, as demonstrated by electromagnetic-field-assisted laser microwelding of NiTi to stainless steel, where induced Lorentz forces drive the liquid fusion zone toward the steel side, limiting brittle iron-titanium phases and boosting tensile strength by 28 percent and ductility by 137 percent. Deeper fundamental understanding will come from in-situ X-ray imaging, smoothed particle hydrodynamics simulations and density functional theory calculations applied at microscale resolution. Finally, the authors call for standardized joining and testing protocols, whose current absence limits cross-study comparison and industrial adoption. With human lifespans lengthening and medical technology accelerating, the researchers argue that microjoining stands poised to become a defining enabler of the next generation of reliable, multifunctional biomedical devices.

Subject of Research: Microjoining technologies for the fabrication of biomedical devices

Article Title: Microjoining for biomedical device fabrication: a perspective

Article References: Zhang, K., Zhou, Y. N., & Peng, P. (2026). Microjoining for biomedical device fabrication: a perspective. Advanced Materials Joining, 1(1), Article 3. https://doi.org/10.1007/s44500-026-00006-z

Image Credits: AI Generated

DOI: 10.1007/s44500-026-00006-z

Keywords: microjoining, biomedical devices, laser microwelding, shape memory alloys, NiTi, stents, resistance welding, solid-state welding, brazing, biocompatibility, intermetallic compounds, implantable sensors

The core of the innovation lies in the elastocaloric effect itself. When a shape memory material such as a nickel-titanium alloy is mechanically stressed, it undergoes a reversible phase transformation from austenite to martensite. This transformation is endothermic in one direction and exothermic in the other: stretching or compressing the material forces the crystal structure to rearrange, absorbing heat from the surroundings, while releasing the stress causes the structure to revert, releasing heat elsewhere. In principle, this cycle can pump heat with no refrigerant gases at all, sidestepping the hydrofluorocarbons responsible for substantial greenhouse gas emissions. Because the working body is a solid metal film, the concept promises compact, leak-free, and environmentally benign cooling devices.

Until recently, however, elastocaloric systems faced a fundamental obstacle: the mechanical work needed to drive the phase transformation must be supplied by electric motors, actuators or other powered mechanisms, which erodes the efficiency gains and keeps the devices tethered to the grid. The new work elegantly removes this dependency. The team’s architecture couples two distinct shape memory film components in a single system. The first acts as a thermal engine, exploiting the one-way shape memory effect: when heated by a low-grade source, it contracts and generates mechanical force. That force is mechanically transmitted to a second shape memory element, the elastocaloric refrigerant, which is thereby cyclically loaded and unloaded. The loading stage absorbs heat from the cold side of the device; the unloading stage rejects it to the hot side, completing a refrigerator cycle driven purely by heat at the input.

The use of thin films rather than bulk alloys is a deliberate and consequential design choice. In bulk shape memory elements, the large cross-sections required to generate useful cooling power also create steep thermal and mechanical gradients, limiting cycling frequency and accelerating fatigue. Thin films, by contrast, can be cycled rapidly because heat penetrates their tiny thickness almost instantly, and the stresses involved in martensitic transformation are better tolerated at small dimensions. The researchers fabricated film-based elements that undergo superelastic cycles at high frequency, enabling the continuous, rhythmic exchange of heat that a practical refrigerator demands. Film geometry also allows thousands of elements to be patterned and operated in parallel, a route to scaling cooling capacity without redesigning the underlying physics.

The concept of heat-driven elastocaloric cooling was not born overnight. A 2019 theoretical study by Shan Qian and colleagues at the University of Maryland laid out the design principle and numerical simulation of a heat-driven system based on regenerative compression, showing in silico that the idea could in principle be thermodynamically competitive. Subsequent reviews catalogued the promise of film-based elastocaloric devices, noting their high power density and mechanical simplicity. In parallel, experimental groups worldwide pushed elastocaloric cooling toward practical power levels; in 2025, a team led by Gengqiang Zhou reported a multi-cell architecture achieving kilowatt-scale cooling power, a landmark that proved the technology could compete with conventional compressors in raw capacity. The new demonstration ties these threads together, converting that accumulated expertise into a system that runs on heat rather than electricity.

The thermodynamics of the device reward careful attention. The thermal engine element operates between a hot reservoir, supplied by the low-grade heat source, and a rejection temperature, extracting work as the shape memory film contracts through its transformation range. Because low-grade heat is thermodynamically dilute, the conversion efficiency of this stage is inherently modest, but the essential point is that the input energy is heat that would otherwise be discarded. The elastocaloric stage, meanwhile, can achieve high coefficients of performance because the mechanical work applied is almost entirely recovered during unloading; superelastic shape memory alloys dissipate only a small fraction of the input work per cycle as hysteresis. In the coupled system, therefore, the net electrical input required to run the cycle can approach zero, with small amounts needed only for control, valves and heat-transfer auxiliaries.

Materials science challenges remain at the heart of making such systems durable. Shape memory alloys are subject to functional fatigue: after many thousands of superelastic cycles, their transformation characteristics degrade, the temperature hysteresis widens, and cooling performance drifts. The researchers addressed this through film composition and microstructure optimization, exploiting the superior fatigue resistance that thin-film sputtered nickel-titanium can offer when grain size and texture are controlled. Thermal design was equally critical. Because the engine and refrigerant films operate at different temperatures, the system must shuttle heat efficiently between stages, and the team’s regenerative arrangement recovers heat within the cycle rather than venting it, boosting the overall temperature lift the device can sustain from a given quality of input heat.

The practical implications are considerable. Enormous quantities of low-grade heat, below roughly 150 degrees Celsius, are released every day by power plants, data centers, factories, refrigeration condensers, and vehicle engines, and nearly all of it is simply rejected to the atmosphere. A cooling technology that can convert this stranded resource into useful refrigeration, with minimal electricity, would upend the energy economics of cold chains, building climate control, and electronics thermal management. In remote or off-grid settings, solar thermal collectors could supply the driving heat directly, creating cooling systems entirely independent of electrical infrastructure. For electric vehicles, where every watt drawn from the battery reduces range, a heat-driven elastocaloric air conditioner could tap engine and power-electronics waste heat instead.

The environmental stakes add urgency. Hydrofluorocarbon refrigerants, while ozone-safe, are potent greenhouse gases thousands of times more effective at trapping heat than carbon dioxide, and international agreements are phasing them down. Vapor-compression systems are also responsible for a substantial fraction of global electricity demand, a share that rises as the planet warms and cooling needs multiply. Solid-state elastocaloric cooling eliminates the refrigerant entirely and, in the heat-driven configuration described here, can largely eliminate the electricity demand as well. If scaled successfully, the technology attacks both halves of the cooling problem at once.

Considerable engineering hurdles still separate the laboratory demonstration from commercial products. Cooling power densities must be maintained over millions of cycles, heat exchangers must be integrated without negating the system’s compactness, and the mechanical linkages coupling the engine and refrigerant films must survive continuous high-frequency operation. Nevertheless, the trajectory of the field is unmistakable: from theoretical proposals five years ago, to kilowatt-scale demonstrations, and now to a heat-driven architecture that dissolves the technology’s biggest structural weakness. What has been demonstrated is a proof of principle with genuinely disruptive potential, a refrigerator whose primary fuel is heat that the world already produces and squanders. As the researchers and their peers refine the materials and architectures, elastocaloric cooling may move from the pages of journals into the machinery of everyday life, driven not by the grid but by the warmth we throw away.

Subject of Research: Heat-driven elastocaloric cooling using shape memory alloy films

Article Title: A heat-driven route to elastocaloric cooling

Article References: A heat-driven route to elastocaloric cooling. (n.d.). https://doi.org/10.1038/s41560-026-02128-0

Image Credits: AI Generated

DOI: 10.1038/s41560-026-02128-0

Keywords: elastocaloric cooling, shape memory alloys, nickel-titanium films, solid-state refrigeration, low-grade waste heat, martensitic phase transformation, thermal engine, functional fatigue, cooling energy efficiency, refrigerant-free cooling, Nature Energy, thermal management

The research, carried out by Samuel Onimpa Alfred of the Department of Aerospace Engineering at the University of Michigan, belongs to a rapidly growing field called triboinformatics, where artificial intelligence is used to decode the messy, nonlinear world of friction, lubrication, and wear. Tribology, the science of interacting surfaces in relative motion, is not a niche pursuit. Earlier studies cited in the work estimate that friction and wear-related losses consume a staggering share of global energy, contributing substantially to costs and emissions across industry. Making surfaces last longer, in artificial hip joints or in jet engine bearings, translates directly into energy saved and devices that survive longer inside the human body or inside an aircraft engine.

What makes Nitinol such a fascinating test case is its shape-memory and superelastic character. Deform it and it snaps back; heat it past a critical temperature and it returns to a previously memorized configuration. But these same properties make its tribological behavior notoriously complex. In this study, Alfred examined four distinct Nitinol conditions: an equiatomic titanium-nickel alloy, and three versions of a nickel-rich composition known as 60NiTi that had been aged, annealed, or solution-treated. Each heat treatment changes the alloy’s microstructure, hardness, and elasticity, and therefore changes how it wears when scraped against a counterface in dry, reciprocating sliding. Classical wear laws, which tend to assume wear scales simply with load and sliding distance while inversely scaling with hardness, capture these shifts poorly.

To tame that complexity, Alfred assembled a dataset of 336 individual measurements drawn from previously published, peer-reviewed reciprocating dry-sliding experiments, covering weight loss, cumulative wear over time, and steady-state coefficient of friction for all four material conditions. The modeling strategy then subjected a battery of algorithms to a demanding examination. Instead of splitting the data randomly, the study used grouped cross-validation, meaning that entire series of wear tests were withheld from the model during training. This is the scientific equivalent of asking a student to answer questions about chapters of a book they were never allowed to read, and it guards against the overly optimistic predictions that plague many machine-learning studies in materials science.

Even under this harsh test, gradient boosting, an ensemble method that builds a predictive model from many sequentially corrected decision trees, emerged as the clear winner. It predicted weight loss with an R-squared of 0.92 and the coefficient of friction with an R-squared of 0.91, beating support-vector regression, random forests, and simple linear baselines. When the cross-validation was made less restrictive and random splits were allowed, those scores climbed to 0.98 for wear and 0.94 for friction. The result confirms that gradient boosting does not just memorize data; it learns genuinely transferable relationships between operating conditions and tribological outcomes, even for material-test combinations it has never encountered.

Crucially, the study did not stop at prediction. Using SHapley Additive exPlanations, or SHAP, a technique borrowed from cooperative game theory that assigns each input variable its fair share of credit for a model’s output, Alfred opened the black box. The analysis revealed that applied load is the dominant driver of wear, while oscillation frequency dominates friction behavior, with higher frequencies associated with lower friction coefficients, a trend consistent with frictional heating at the sliding interface. This kind of transparency matters enormously for engineers, because a model that merely outputs numbers without explanations offers no guidance on which design levers to pull.

Perhaps the most striking achievement is a deep learning result: a gated recurrent unit network, a type of neural network designed for sequential data, reproduced the full time-resolved wear trajectories of completely unseen tests with an R-squared of 0.91. In other words, given the early portion of a wear test, the network could accurately trace how material loss would accumulate over the entire remaining test, test after test, across all four heat treatments. That capability opens the door to digital wear forecasting, where a short initial experiment or monitoring window could stand in for long and expensive laboratory campaigns.

The study then confronted the granddaddy of wear science, the Archard equation, formulated in 1953, which states that wear volume is proportional to load and sliding distance and inversely proportional to hardness. When that classical law was fitted to the Nitinol dataset, it managed an R-squared of only 0.27, and performed even worse, going negative, when hardness was imposed rather than fitted. Alfred instead let the data speak, recovering a generalized Archard-type law in which the exponents on load, sliding distance, frequency, and hardness are free parameters. The resulting equation, weight loss equals 0.0425 times load to the power 0.78, sliding distance to the power 0.54, frequency to the power minus 0.14, and hardness to the power minus 0.26, described all four heat treatments with an R-squared of 0.79, using only measured hardness rather than material identity labels.

The exponents themselves tell a physical story. The sub-linear load exponent of 0.78 suggests that superelastic Nitinol distributes contact stress in a way that softens the wear increase as loads climb, while the negative frequency exponent quantifies the frictional-heating effect seen in the SHAP analysis. Most intriguingly, the fitted wear coefficient for each material correlated almost perfectly, at r equals 0.97, with the ratio of elastic modulus to hardness, a dimensionless quantity long championed in surface engineering as an indicator of elastic, wear-tolerant contact. When the modulus-to-hardness ratio served as the sole material descriptor in the generalized law, the fit reached an R-squared of 0.83, essentially matching models that knew which alloy they were dealing with.

For a metal that must survive inside arteries, bearings, and aerospace mechanisms without the benefit of lubrication, these findings provide something genuinely new: accurate, transparent, and physically consistent models that connect processing, properties, and performance. A designer can now estimate how a given heat treatment, hardness, and duty cycle will translate into wear and friction, before a single prototype is machined. More broadly, the work is a template for how triboinformatics should be done, with strict grouped validation, interpretable explanations, and laws recovered from data that honor the physics of contact rather than discarding it. As Nitinol finds its way into ever more demanding applications, the machines that predict its wear are, fittingly, learning from the metal that never forgets.

Beneath the headline results lies a dataset with an unusually clean provenance. The 336 measurements were not generated afresh for the modeling study but were compiled from two previously published, peer-reviewed experimental campaigns on superelastic TiNi and 60NiTi, with every table—loads, frequencies, durations, sliding distances, specimen masses before and after testing, cumulative weight loss, and steady-state friction coefficients—reproduced in the new paper’s appendix. That decision to expose the full experimental record alongside the models is itself a small contribution to a field where data scarcity and fragmentation remain the chief obstacles to progress.

The geometry underlying those tables also rewards a closer look. Each test used a 5.03 millimeter reciprocating stroke, so every cycle covered just over a centimeter of sliding, and the sliding distances reported for all four material conditions satisfy an exact arithmetic relation linking distance to frequency and test duration. All fifty-six wear-time series were strictly monotonic, with no missing entries, meaning the recurrent network tasked with reconstructing wear trajectories never had to impute gaps—an often unappreciated advantage when deep learning meets sparse laboratory data.

The strong correlation between the fitted wear coefficient and the elastic-modulus-to-hardness ratio also has a pedigree worth noting. Surface engineers have argued for decades that this ratio, rather than hardness alone, governs how well a material tolerates elastic contact and resists abrasion, particularly for coatings and for alloys whose elastic resilience absorbs deformation that would otherwise be permanent. The Nitinol results give that long-standing heuristic a quantitative, data-driven endorsement for shape-memory metals specifically.

The study situates itself in a broader movement. Recent systematic reviews of machine learning in tribology have catalogued a wave of applications, from aluminum-matrix composites to modified zinc alloys to diamond-like carbon coatings, where algorithms predict friction and wear from operating parameters. What distinguishes the present work within that wave is its insistence on withholding whole test series during validation and on recovering an interpretable wear law from the same data used to train opaque models. The author notes that the code underlying the analysis is available on reasonable request, and the supplementary data file, roughly 800 kilobytes in spreadsheet form, invites others to replicate or extend the models for their own shape-memory alloy systems.

Subject of Research: Machine learning prediction of wear and friction behavior in heat-treated Nitinol shape-memory alloys.

Article Title: Triboinformatic modeling of nitinol alloys under different heat-treatment regimes

Article References: Alfred, S. O. (2026). Triboinformatic modeling of nitinol alloys under different heat-treatment regimes. Journal of Materials Science. https://doi.org/10.1007/s10853-026-13713-9

Image Credits: AI Generated

DOI: 10.1007/s10853-026-13713-9

Keywords: Nitinol, tribology, machine learning, wear prediction, shape-memory alloys, gradient boosting, SHAP, Archard equation, deep learning, heat treatment, friction, triboinformatics