The researchers investigated the alloy using hot uniaxial compression tests at 350–450 °C and strain rates of 0.01–1 s⁻¹. They also conducted strain-rate-jump compression tests to examine the influence of loading-rate history. These were laboratory deformation experiments on one spray-formed alloy; the available abstract does not describe replication, uncertainty estimates or the number of specimens tested.

According to the abstract, subgrain rotation driven by dynamic recovery and deformation was identified as the principal mechanism of continuous dynamic recrystallization. Three forms of low-angle grain boundaries were observed: equiaxed subgrain structures, and low-angle boundaries with preferred orientations either parallel to the compression direction or perpendicular to it. The reported orientations were also associated with grain orientation.

The strain-rate-jump tests showed an asymmetric response in flow stress and microstructure evolution to loading history, which the abstract describes as observed for the first time in hot deformation of Al–Zn–Mg–Cu alloy. The authors suggest that dislocation accumulation and the time available for rearrangement through dynamic recovery may contribute to differences from constant-strain-rate uniaxial compression. The available summary does not provide the magnitude of the flow-stress changes, quantitative texture data, detailed boundary statistics or full methodological information, so the scope of these findings is limited to the reported abstract rather than an assessment of the complete article.

Subject of Research: Hot-deformation microstructure and continuous dynamic recrystallization in spray-formed Al–Zn–Mg–Cu alloy

Article Title: Microstructure evolution and dynamic recrystallization of spray-formed Al–Zn–Mg–Cu alloy under hot deformation

Article References: Tao, L., Zhang, Z., Jia, W., Sun, C., Li, D., Jia, Z., & Zhou, G. (2026). Microstructure evolution and dynamic recrystallization of spray-formed Al–Zn–Mg–Cu alloy under hot deformation. Journal of Materials Science, 61(43), 33974-33994. https://doi.org/10.1007/s10853-026-13710-y

Image Credits: AI Generated

DOI: 10.1007/s10853-026-13710-y

Keywords: Al–Zn–Mg–Cu alloy, spray-formed alloy, hot deformation, continuous recrystallization, dynamic recovery, uniaxial compression, strain-rate history, microstructure evolution, texture intensity, grain boundaries, Microstructure, evolution

According to the study abstract, the experimental films were examined by nanoindentation to assess hardness. Chromium was added in solid solution to strengthen the lattice, while yttrium was observed to enrich the examined grain boundaries. The researchers systematically varied the alloying-element contents with grain size kept constant, allowing them to investigate how grain-interior and grain-boundary chemistry jointly affected mechanical response.

Chromium additions produced solid-solution strengthening, but the abstract reports that this effect saturated at higher concentrations as grain-boundary-dominated deformation processes emerged. Indentation pileups containing slip steps and grain rotation provided evidence for those processes. Increasing yttrium concentration strengthened the grain boundaries by pinning dislocations and suppressing dislocation emission, grain-boundary sliding and grain rotation. The authors associated a weakened chromium contribution at higher yttrium concentrations with a reduced dislocation-bowing distance caused by dopant pinning.

The findings are based on the published abstract; the supplied source does not provide the full article, so the report cannot assess the complete methods, underlying measurements or uncertainties. Within the stated scope of nanocrystalline Ni-Cr-Y sputtered films, the results indicate that controlling both grain and grain-boundary chemistry can influence deformation mechanisms and increase hardness. The authors present this tuning approach as a possible strategy for strengthening nanocrystalline metals, but the reported evidence concerns hardness measured by nanoindentation rather than a broader range of structural or engineering performance tests.

Subject of Research: Effects of chromium and yttrium doping on hardness and deformation mechanisms in nanocrystalline Ni-Cr-Y films

Article Title: Synergistic doping of the grain interior and grain boundary alters deformation mechanisms and enables extreme strength in nanocrystalline Ni-Cr-Y alloys

Article References: Liu, Y., Trelewicz, J. R., & Rupert, T. J. (2026). Synergistic doping of the grain interior and grain boundary alters deformation mechanisms and enables extreme strength in nanocrystalline Ni-Cr-Y alloys. Journal of Materials Science, 61(43), 34103-34123. https://doi.org/10.1007/s10853-026-13753-1

Image Credits: AI Generated

DOI: 10.1007/s10853-026-13753-1

Keywords: nanocrystalline alloys, nickel-chromium-yttrium, grain boundaries, solid-solution strengthening, nanoindentation, hardness, yttrium segregation, chromium doping, deformation mechanisms, materials science, Synergistic, doping

For the analysis, the researchers established a strain-compensated hyperbolic-sine Arrhenius constitutive model and constructed hot-processing maps. The model showed a correlation coefficient of R = 0.992, a root mean square error of 8.992 MPa, and an average absolute relative error of 7.283%. The reported processing maps were used to divide the deformation conditions into instability, instability-edge, and stable regions. The work examined dynamic recrystallization mechanisms and assessed the roles of second phases under the different deformation conditions.

Microstructural analysis indicated that deformation in the instability region was dominated by prismatic <a> slip. The dynamic recrystallization fraction there was below 10%, and discontinuous dynamic recrystallization was the primary mechanism, while continuous dynamic recrystallization was suppressed by lamellar long-period stacking-ordered phases. At the instability edge, prismatic <a> slip remained dominant, with limited basal and pyramidal slip; discontinuous dynamic recrystallization also dominated this region. In the stable region, several slip systems were active simultaneously, and distinct Orowan looping was observed.

At high temperatures, most lamellar long-period stacking-ordered phases dissolved. The phases that remained undissolved, together with α–Mn particles, inhibited grain-boundary migration and were associated with a bimodal grain structure. The study therefore connects the alloy’s hot-processing conditions, deformation mechanisms and recrystallization behavior with the influence of its second phases. Because the supplied source is an abstract and subscription preview, details such as specimen dimensions, deformation conditions beyond those reported, replicate numbers and the limits of the processing map cannot be independently evaluated from the available evidence.

Subject of Research: Hot-deformation mechanisms and dynamic recrystallization in a Mg–Gd–Y–Zn–Mn alloy

Article Title: Investigation on deformation mechanism and recrystallization behavior of a Mg–Gd–Y–Zn–Mn alloy by hot compression

Article References: Zhang, M., Jiang, J., Luo, H., Ye, Y., & Chen, X. (2026). Investigation on deformation mechanism and recrystallization behavior of a Mg–Gd–Y–Zn–Mn alloy by hot compression. Journal of Materials Science, 61(43), 34124-34146. https://doi.org/10.1007/s10853-026-13758-w

Image Credits: AI Generated

DOI: 10.1007/s10853-026-13758-w

Keywords: Mg–Gd–Y–Zn–Mn alloy, hot compression, dynamic recrystallization, constitutive modeling, processing maps, deformation mechanisms, LPSO phases, microstructure, Orowan looping, grain boundaries, Investigation, deformation

The appeal of removing polymer binders becomes clearer when considering how conventional electrodes are actually made. In a typical fabrication, catalyst particles are mixed with a polymer such as Nafion or PTFE along with a conductive additive, and the resulting slurry is painted onto a support. This approach is cheap and scalable, but the binder inevitably buries a fraction of the catalytic surface, adds resistance at every particle-particle and particle-substrate junction, and can swell, crack, or detach under the strongly alkaline conditions common in carbon dioxide electrolysis. Over hours of operation, such degradation manifests as rising overpotentials and falling selectivity. A self-supported architecture, in which the active material grows directly as an integrated array on a conductive scaffold, eliminates these failure modes at the source, which is precisely the design philosophy behind the nanowire electrodes developed by the Hefei team.

The template method they employed deserves particular attention. Anodic aluminum oxide is a classic nanofabrication material, formed by electrochemically oxidizing aluminum in an acidic electrolyte so that self-organized, hexagonally packed pores grow perpendicular to the metal surface. Conventional AAO templates, however, produce only straight, isolated channels, and nanowires grown within them emerge as parallel but disconnected pillars. The three-dimensional AAO used in this work incorporates transverse pores that intersect the longitudinal ones, creating a genuinely interconnected network. When metal is deposited into this template and the alumina is dissolved, the resulting nanowire membrane is not a bundle of separate wires but a woven, scaffold-like structure in which every wire is electrically continuous with its neighbors. This connectivity means that even if individual contact points degrade, electrons can still find alternative conduction paths, a redundancy that conventional particulate electrodes lack.

The silver electrode, designated 3D-ICAg, illustrates how this architecture translates into measurable electrochemical advantages. Silver is well established as the most selective metal for reducing carbon dioxide to carbon monoxide, operating through a mechanism in which adsorbed carbon dioxide is activated at the surface, protonated to form a carboxyl intermediate, and then cleaved to release carbon monoxide. The competing reaction, hydrogen evolution, consumes the same electrons and protons, so selectivity hinges on how quickly carbon dioxide intermediates form relative to hydrogen adsorption. The reported Faradaic efficiency of 97.28 percent indicates that nearly every electron passing through the electrode went into making carbon monoxide rather than hydrogen gas, a figure that places the electrode among the better-performing silver catalysts reported in H-type cells. The current density of 59.06 milliamperes per square centimeter is equally significant, because high selectivity is easy to achieve at low current densities where carbon dioxide supply is not limiting; maintaining it at industrially relevant current densities is the harder test.

Mass transport is where the open, scaffold-like geometry pays its greatest dividend. In a conventional bound electrode, carbon dioxide dissolved in the electrolyte must diffuse through tortuous pathways flooded with polymer to reach buried active sites, and the gaseous products must diffuse back out. As current density rises, this diffusion limitation causes local carbon dioxide depletion and pH gradients that erode selectivity. The interconnected nanowire array, by contrast, presents open channels between the wires through which reactants and products can move freely, so the concentration of carbon dioxide at the active surface stays closer to the bulk value even at high current densities. The ordered, parallel arrangement of the wires also ensures uniform current distribution, avoiding the hot spots that accelerate degradation in disordered electrodes.

The fifty-hour stability test provides a meaningful benchmark for this design. Catalyst electrodes frequently show excellent initial performance followed by rapid decline as binders fail or nanostructures agglomerate. Sustaining near-quantitative carbon monoxide selectivity for two days of continuous operation suggests that the direct electrical integration of the nanowires into the substrate, without any intermediate adhesive layer, resists the mechanical and chemical stresses of prolonged electrolysis. The team complemented these performance measurements with in situ Raman spectroscopy, a technique in which a laser is focused on the working electrode while it operates, allowing vibrational fingerprints of adsorbed intermediates to be recorded in real time. Such measurements can reveal which surface species accumulate during the reaction and how their populations change with applied potential, offering mechanistic insight that static ex situ characterization cannot provide.

The copper electrode, GB-ICCu, tackles an even more demanding problem. Copper is the only elemental metal that reduces carbon dioxide to multicarbon products with appreciable efficiency, because its unique surface chemistry stabilizes the carbon monoxide intermediates long enough for them to couple through carbon-carbon bond formation. Yet this same reactivity produces a bewildering mixture of products, including ethylene, ethanol, acetate, and various alcohols, with n-propanol typically a minor component. Forming the three-carbon chain of n-propanol requires at least two carbon-carbon coupling steps and careful control of intermediate coverage on the surface, which is why Faradaic efficiencies for this product have historically remained in the single digits for most catalysts. The reported 17.47 percent efficiency therefore represents a substantial advance for an H-type cell configuration.

Two design features of GB-ICCu appear to drive this selectivity. The first is the abundance of surface grain boundaries, the disordered interfaces where crystalline domains of different orientation meet. Grain boundaries introduce strained, undercoordinated atoms whose electronic structure differs from that of terrace sites, and prior computational and experimental studies have linked such sites to enhanced carbon dioxide activation and stabilized carbon-carbon coupling intermediates. By deliberately engineering a nanowire surface dense with these defects, the team increased the population of the most reactive sites. The second feature is the nanoconfinement effect arising from the interconnected geometry. When reaction intermediates are generated within the narrow spaces between closely spaced nanowires, their effective local concentration rises, and the probability that two carbon-containing intermediates encounter each other before desorbing increases accordingly. Confinement thus biases the branching of the reaction network toward coupling rather than toward protonation to single-carbon products.

The flow cell measurement of 77.7 milliamperes per square centimeter partial current density for n-propanol points toward practical relevance. In an H-type cell, carbon dioxide reaches the catalyst only by dissolving in the electrolyte, and its low solubility caps the achievable current density. Flow cells circumvent this by pumping carbon dioxide gas through a gas diffusion electrode so that the gas, liquid, and catalyst meet at a three-phase interface, dramatically increasing the carbon dioxide supply. Achieving high partial current density in this configuration is a critical step because industrial deployment requires both high selectivity and high throughput, and the two are usually in tension. The fact that the same self-supported nanowire concept performs well in both cell types suggests the architecture is robust rather than tuned to one narrow operating regime.

Taken together, the two studies demonstrate that the template-synthesized, binder-free nanowire approach is a general platform rather than a material-specific trick. The same three-dimensional interconnected architecture accommodates silver, a selective single-carbon product catalyst, and copper, a multicarbon product catalyst, with the grain boundary and confinement levers providing additional control over product distribution. As carbon dioxide electrolysis moves from laboratory curiosity toward industrial deployment, the remaining challenges include scaling the template synthesis to large electrode areas, integrating the arrays into gas diffusion layers, and verifying durability over thousands of hours. The Hefei team’s results indicate that the structural foundations of the electrode, long treated as a secondary consideration behind catalyst composition, can be as decisive for performance as the choice of metal itself.

Subject of Research: Self-supported nanowire electrodes for electrocatalytic carbon dioxide reduction

Article Title: Self-supported nanowire electrodes improve CO2 conversion rate

Article References: Self-supported nanowire electrodes improve CO2 conversion rate. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: CO2 reduction, electrocatalysis, nanowire electrodes, silver nanowires, copper nanowires, n-propanol, carbon monoxide, Faradaic efficiency, anodic aluminum oxide, grain boundaries, flow cell, Energy & Environmental Materials

The asymmetry Kamachali describes is subtle but consequential. In most RIS frameworks, the governing description is closed through coupled transport equations for solutes and irradiation-generated point defects, augmented by source, recombination, and sink terms. The microstructural defects, such as grain boundaries, dislocations, and cavities, typically enter the equations through sink strength, capture efficiency, geometry, or boundary conditions. Their thermodynamic identity, however, is represented only in simplified form. Even where segregation energetics are included, they are often projected onto bulk thermodynamic factors or effective interfacial properties rather than being based on a sink-specific free-energy landscape. In other words, the equations know how fast solutes flow, but they know surprisingly little about the thermodynamic character of the destination. Kamachali argues that a more complete understanding of RIS can emerge when sink-specific thermodynamic landscapes and their interaction with non-equilibrium fluxes are taken explicitly into account.

This is not a call to discard existing models, which have grown increasingly sophisticated. Recent RIS models are already aware of the assumptions of perfect-sink behavior or homogeneous chemical potentials and aim to relax them. Thomas Schuler and colleagues, for instance, have emphasized the need to move beyond static sink idealizations and to describe the coupled interplay between segregation kinetics and sink evolution itself using atomistic simulations. Multiscale RIS frameworks such as those of Laurine Thuinet and co-workers and of Liangzhao Huang and collaborators have combined atomistic transport information with continuum-level segregation modeling, moving beyond purely phenomenological sink treatments. Phase-field investigations by Gauthier Bertrand Moladje and colleagues on RIS near dislocations and low-angle grain boundaries have shown that biased sinks require an explicit treatment of local defect character rather than a neutral-sink approximation. Experimental studies have reinforced this viewpoint, showing that grain boundary plane and character strongly influence the resulting segregation and precipitation behavior under irradiation.

Further recent developments have broadened the scope of RIS modeling and validation even more, including two- and three-dimensional treatments of sink geometry and morphology, nonlinear coupling between neighboring nanoscale sinks, machine-learning-assisted parameterization of defect-mediated diffusion kinetics, and correlative atom probe tomography and scanning transmission electron microscopy validation of RIS profiles. These advances suggest, Kamachali writes, that the important next step is not only to refine transport coefficients, but also to develop thermodynamic representations of sinks as structurally and chemically differentiated states. A grain boundary is not a neutral drain for solutes; it is a quasi-two-dimensional region with its own atomic density, its own coordination numbers, and its own mixing enthalpies and entropies, all of which can differ dramatically from the bulk crystal that surrounds it.

The systematic step forward that Kamachali proposes connects RIS frameworks with ongoing advances in the thermodynamic and kinetic theory of defects, in particular the density-based thermodynamic and phase-field framework known as DPF. The DPF theory offers a route to view defects as local thermodynamic states with their own structural, chemical, and energetic degrees of freedom, describing them through a density parameter that represents their local structural state, while restoring the thermodynamic properties of the parent bulk phase. The significance of this idea is far-reaching: defects and bulk phases are no longer treated as conceptually separate objects, but as distinguishable yet continuously connected states within a single free-energy landscape. This provides a natural thermodynamic language for describing defect stability, segregation, and defect-phase transitions in direct continuity with the surrounding bulk material.

Within the broad landscape of existing theory, DPF can be understood as a strong addition rather than a replacement. Classical rate-theory and sink-strength models remain central for describing defect production, recombination, migration, and biased fluxes under irradiation. Atomistic simulations, kinetic Monte Carlo, and cluster-dynamics approaches provide essential information on defect-solute binding, transport pathways, cascade debris, and the evolution of defect clusters. DPF offers a thermodynamically adaptable and compatible route for representing defect states and sinks, and it can be directly integrated with phase-field models, which have become increasingly important for connecting irradiation-modified thermodynamic driving forces to precipitation, phase stability, and mesoscale microstructure evolution. Crucially, DPF opens a comprehensive route for integrating defect thermodynamics with existing bulk CALPHAD databases, the vast repositories of assessed thermodynamic data that underpin computational materials design. Recent detailed investigations have shown that the density parameter can be derived from atomistic simulations, establishing a streamlined bridge between atomistic calculations and continuum thermodynamic and phase-field modeling.

Kamachali identifies two profound ways in which DPF can enrich RIS studies. The first is by remapping phase stability under irradiation through irradiation-conditioned phase diagrams. The framework begins with a density-based free-energy functional, in which the atomic density acts both as a field variable in simulations and as a mean-field descriptor in the free-energy formulation. For a grain boundary embedded in a multicomponent alloy, the functional combines a volume integral over the density-based Gibbs free energy density with a plane integral accounting for the interfacial contribution of the grain boundary, whose potential and gradient coefficients relate to the underlying grain-boundary properties such as atomic planes and misorientation and can be derived from atomistic simulations. The elastic energy density is formalized for multicomponent alloys with lattice strain coefficients due to solutes in the host lattice and elastic constants defined as a function of local atomic density. These equations are fed by CALPHAD thermodynamic data of the corresponding alloy system together with a minimum set of grain-boundary-specific quantities, including the free energy of the homogeneous bulk substance, gradient energy coefficients, and the bulk mixing enthalpy and entropy.

If a steady irradiation condition is viewed, at a coarse-grained thermodynamic level, as maintaining a supersaturated population of point defects, it can be connected to density-based phase diagrams through two intermediate links: the well-established connection between irradiation intensity and the resulting excess concentration of point defects, and the recent demonstration that point defects can be effectively described based on an atomic density field through both a reduction in coordination number and a change in excess free volume. Once these links are established, CALPHAD-integrated density-based free-energy functionals can be constructed and minimized to compute irradiation-conditioned phase diagrams. These differ fundamentally from so-called radiation-modified phase diagrams constructed essentially in terms of radiation-modified solubility, the solute concentration at which the growth rate of an irradiated precipitate vanishes. The density-based diagrams have a free-energy foundation and enable studying the conditions of phase stability, including nucleation and dissolution of various phases, directly not only in the supersaturated bulk but also at defects acting as sinks. Notably, it has been shown that the miscibility gap in Fe-Mn-X alloy systems can dramatically change for a reduced atomic density, meaning that even modest defect-induced reductions in atomic density can shift local thermodynamic driving forces and phase equilibria.

The second enrichment is defect-sensitive transport and phase evolution. In the Onsager framework, the quantities entering the RIS equations are not independent objects but descend from the underlying thermodynamic structure of the system. Once the free-energy landscape is allowed to depend explicitly on the local defect state, both the driving forces and the kinetic couplings become functions of the local defect state. The generalized diffusional potentials of the alloying species follow from the variational derivatives of the density-based defect free-energy functional, and the fluxes are expressed in Onsager form as linear responses to gradients in these generalized potentials, with the Onsager coefficients themselves depending on the local atomic density and hence on the local defect state. The vacancy and self-interstitial concentrations and fluxes can be consistently expressed in terms of the atomic density field while still being retained as distinct transport variables when required, allowing interstitial-mediated RIS mechanisms to be incorporated. Segregation, counter-segregation, and coupled solute-defect transport need not be described through fixed sink parameters alone but can be treated as consequences of a defect-dependent free-energy landscape and its associated mobilities, with parameterization obtained from atomistic simulations, kinetic Monte Carlo calculations, rate-theory estimates, or spatially resolved irradiation experiments.

Recent applications demonstrate the promise of this approach. Kadambi and colleagues explicitly coupled the atomic density field to CALPHAD-informed free-energy descriptions to capture segregation and phase stability in the vicinity of defects, with particular emphasis on maintaining thermodynamic consistency across bulk and defect regions in ternary Fe-Cr-Ni alloys. A more extensive effort by Calbert, Messina, and Thuinet embedded the DPF concept, together with a density-dependent Gibbs free-energy functional directly linked to CALPHAD-accessible quantities, into a classical phase-field framework to describe grain boundaries and radiation-induced segregation in Fe-Cr alloys, treating the grain-boundary density as a governing parameter and systematically varying it to show how the grain-boundary state directly modifies segregation profiles and sink efficiencies. A key aspect lies in making the defect-elastic interaction explicitly dependent on the local atomic density field: rather than prescribing a constant eigenstrain at the grain boundary, the eigenstrain of each defect species is derived as a continuous function of local density, leading to a density-dependent relaxation volume for solutes, vacancies, and interstitials. In terms of experimental validation, a thermodynamic defect-state framework generates measurable predictions beyond classical enrichment or depletion profiles, including possible transitions between distinct chemical or structural states of the sink, sink-specific excess compositions, and variations in segregation behavior with grain-boundary character. A particularly useful strategy would be to compare chemically resolved segregation profiles at different sinks exposed to the same irradiation condition: if two sinks experience comparable fluxes but display different segregation levels or precipitation tendencies due to their structural character, this would suggest the necessity for adopting thermodynamic-aware sink-strength parameters. The view of defects as passive sinks characterized by fixed parameters, Kamachali concludes, can and should be replaced by a dynamic framework that captures their thermodynamic identity, a necessary step toward preventative and ultimately design-driven strategies for materials under irradiation.

Subject of Research: Thermodynamics of radiation-induced segregation and phase change in nuclear materials

Article Title: Thermodynamics for radiation-induced segregation and phase change needed

Article References: Kamachali, R. D. (2026). Thermodynamics for radiation-induced segregation and phase change needed. Frontiers in Nuclear Engineering, 5, Article 1868886. https://doi.org/10.3389/fnuen.2026.1868886

Image Credits: AI Generated

DOI: 10.3389/fnuen.2026.1868886

Keywords: radiation-induced segregation, thermodynamics, nuclear materials, CALPHAD, phase diagrams, density phase-field, grain boundaries, irradiation, radiation-induced, segregation, phase, change

Tuchinda’s winning project, titled The Role of Entropy in the Interfacial Cohesion of Metals and Alloys, sets its sights on a factor that conventional models of material failure have long treated as an afterthought: entropy. Entropy is a thermodynamic property related to the number of possible arrangements and motions that atoms can adopt within a material at finite temperatures. That may sound abstract, but it describes the actual environment that engineering materials face in real processing routes and real applications, where heat, vibration and atomic shuffling are unavoidable facts of life. Although scientists have spent decades studying how chemical elements accumulate along crystal boundaries and alter their strength, the entropic contributions are frequently excluded from predictive calculations altogether, simply because they are difficult and computationally expensive to account for. Tuchinda’s project aims to close that gap by developing a more complete understanding of how atomic arrangements, chemical composition and temperature jointly determine the strength of the interfaces that hold metals together.

The practical stakes of this question are enormous. Metals and alloys contain microscopic crystals separated by internal boundaries, and these boundaries can become vulnerable points where fractures begin. Chemical elements that segregate along these boundaries can either strengthen the connections between crystals or weaken them dramatically, influencing whether a material withstands mechanical stress or becomes susceptible to sudden brittle failure. Sulfur embrittling steel at high temperature, or beneficial elements toughening a superalloy, are two sides of the same atomic-scale coin. Understanding this type of mechanism, Tuchinda explained, will help materials scientists and engineers design both new processing routes and alloys that are resistant to fracture, such as advanced steels and refractory alloys intended for nuclear applications. In other words, the research could contribute to the development of stronger, more reliable materials for the demanding energy environments where failure is simply not an option.

To attack the problem, Tuchinda will deploy a toolkit that reflects the modern transformation of materials science. His approach combines advanced computer simulations, thermodynamic modeling and machine-learning-assisted techniques to disentangle the interplay between atomic structure, chemistry and temperature at internal interfaces. At NJIT he leads the Imperfection Engineering Group, a research team that uses accelerated computer modeling and simulations to investigate the structure of imperfections in crystalline materials. The group studies grain boundaries, triple junctions, which are the locations where three crystals meet, and other structural imperfections within crystalline materials, blending computational materials science, thermodynamics and data-driven modeling to understand how these features affect material behavior. Rather than treating defects as nuisances to be eliminated, the group treats them as designable features whose properties can be engineered.

The DOE award builds on a substantial foundation of published research. In a 2026 review published in the journal Acta Materialia, Tuchinda and collaborators examined advances in computational models that predict how chemical elements accumulate along grain boundaries. Their review highlights how accounting for differences in atomic environments and thermodynamic properties, including entropy, can improve predictions of material behavior and inform the design of more stable alloys. The message of that review is that the field’s predictive models have been leaving measurable accuracy on the table by ignoring entropic effects, and that correcting this omission could change how alloy designers think about stability at elevated temperatures.

Tuchinda’s earlier research, carried out during his doctoral studies at the Massachusetts Institute of Technology, investigated how alloy composition and atomic-scale interactions influence material strength and stability. Those studies examined grain-boundary embrittlement in aluminum alloys, developed large computational databases to predict how chemical elements affect interfacial cohesion, and advanced machine-learning-assisted methods for understanding atomic interactions across different alloy systems. Each of these strands feeds directly into the new DOE project. The databases provide the raw predictive machinery, the machine-learning methods accelerate the exploration of vast chemical spaces, and the embrittlement studies supply the physical intuition about how segregation translates into fracture.

The new project will also expand the scope of the research well beyond grain boundaries. Engineering alloys contain many other types of internal interfaces, including boundaries between different material phases, interfaces involving intermetallic compounds, and surfaces where reinforcing particles meet the surrounding metal matrix. The research will examine how atomic arrangements and their stability at different temperatures influence the accumulation of chemical elements at these interfaces and the strength of the connections between them. This is territory where scientists still lack comprehensive models to explain and predict what happens, which means the project could establish explanatory frameworks that do not currently exist. Success would give alloy designers a unified picture of interfacial cohesion across the full menagerie of interfaces found in real engineering materials, not just the classical grain boundaries that have dominated the literature.

The award carries institutional as well as scientific weight. This DOE project will help establish my lab and support graduate students who will further develop the future STEM workforce, and help mentor undergraduate students at NJIT, Tuchinda said. The funding arrives at a formative moment for a young research group, providing the sustained five-year horizon that fundamental computational research requires. The DOE Early Career Research Program, administered through the Office of Science, supports scientists at U.S. universities, national laboratories and user facilities pursuing fundamental research in areas central to the department’s mission, and the 2026 cohort draws its 67 scientists from 39 universities and 11 DOE national laboratories and user facilities. Tuchinda’s project was selected through the DOE Office of Basic Energy Sciences, which supports research into the fundamental properties and behavior of matter.

Tuchinda’s trajectory traces a clear line from Bangkok to Newark. He earned his bachelor’s degree in metallurgical and materials engineering from Chulalongkorn University in Thailand in 2018, then moved to MIT, where he completed his Ph.D. in materials science and engineering in 2023. Five years later he stands at the head of his own laboratory, federally funded to pursue the entropic physics of the seams that hold metals together. If his project succeeds, the atomic-scale interactions that determine whether a nuclear alloy toughens or shatters will become predictable quantities in the equations of alloy design, transforming a long-overlooked thermodynamic property into a practical engineering tool for the materials that power the nation’s energy future.

Subject of Research: Entropy-driven interfacial cohesion and failure prediction in metals and alloys

Article Title: NJIT professor selected for DOE early career award to advance research on metal failure

Article References: NJIT professor selected for DOE early career award to advance research on metal failure. Original publication (Bibliographic details unavailable.)

Image Credits: AI Generated

DOI: Not provided

Keywords: materials science, metallurgy, entropy, grain boundaries, DOE Early Career Research Program, NJIT, alloy design, brittle fracture, computational materials science, machine learning, professor, selected

The SEI is a passive layer, typically several hundred angstroms thick, that forms spontaneously when the electrolyte decomposes on contact with lithium metal, the most reducing electrode known. Ideally, it should block electrons while letting lithium ions pass freely, but in practice it is a heterogeneous, mosaic-like bi-layer: an inorganic-rich inner layer hugging the electrode and a porous organic outer layer facing the electrolyte. Microscopic studies have shown that the inorganic sublayer is not a continuous film but a dense packing of crystalline grains separated by numerous grain boundaries, and it is precisely this grain-boundary-rich architecture that shapes how ions travel. Nonuniform transport through these grains and boundaries concentrates lithium deposition in localized spots, which amplifies with every charge-discharge cycle until dendrites nucleate, grow, and penetrate.

Earlier computational work mapped lithium-ion transport only in a handful of representative SEI components, mostly lithium fluoride and lithium oxide, using density functional theory with nudged elastic band, or NEB, calculations to trace minimum-energy pathways. Those studies revealed that grain boundaries create open diffusion channels that can speed ion transport, but they covered few pathways and few surface orientations. The Oklahoma team instead built a systematic dataset spanning eight major inorganic SEI phases: lithium fluoride, chloride, bromide, and iodide; lithium oxide; lithium sulfide; lithium nitride; and lithium carbonate. For each, they generated NEB diffusion data across low- and medium-energy crystal surfaces and across both homogeneous grain boundaries and heterogeneous interfaces between different phases, producing a unified design space for SEI ion migration.

The computational machinery behind the dataset was substantial. Bulk structures were drawn from the Materials Project repository and optimized with the Vienna Ab-initio Simulation Package using the Perdew-Burke-Ernzerhof functional, a 500 eV plane-wave cutoff, and forces converged below 0.1 eV per angstrom. Grain slabs were cut from surfaces with energies below 250 meV per square angstrom, since such low-energy facets are the ones most likely to appear in real grains. Homogeneous grain boundaries were constructed using coincidence site lattice theory with sigma values of 3, 5, 7, 9, 11, and 13, and boundaries exceeding 1,000 millijoules per square meter in energy were discarded as physically implausible. Heterogeneous interfaces were assembled with the Zur-McGill lattice-matching algorithm, keeping only commensurate models with average lattice mismatch below five percent. Diffusion was modeled as vacancy-mediated hopping, the mechanism prior work identified as most favorable in SEI compounds, with climbing-image NEB calculations locating the saddle points along each pathway.

The resulting dataset comprised 280 grain-diffusion NEB calculations plus 198 homogeneous grain-boundary and 104 heterogeneous-interface cases, each NEB run containing seven intermediate structures along the migration path, for a total of 2,114 data points. That volume of quantum-mechanical data is exactly what makes machine learning worthwhile: exhaustive NEB screening of every conceivable SEI chemistry, surface orientation, and boundary configuration would be computationally prohibitive, so a predictive model trained on a representative sample can extend the reach of first-principles accuracy to configurations never explicitly calculated.

The modeling architecture is where the study departs from conventional approaches. Each NEB image, whether initial, intermediate, or final, was converted into a periodic crystal graph in which atoms are nodes and interatomic interactions within a cutoff radius are edges, encoded by the directional message-passing network DimeNet++. A pretrained graph variational autoencoder, adapted from the crystal diffusion VAE of Xie and colleagues, then learned latent representations of entire NEB trajectories, encoding all seven structures of a diffusion event jointly rather than treating each configuration in isolation. The autoencoder’s decoder is denoising-based, recovering structures from Gaussian-perturbed coordinates and interpolated atom-type distributions, which strengthens the latent space. These latent embeddings were concatenated with composition-based descriptors from the Matminer library and structural descriptors such as exposed surface, surface or grain-boundary energy, and a saddle-point indicator, then processed by a multi-layer Transformer encoder whose self-attention captures energy curvature and collective structural evolution along the pathway.

The framework’s predictive performance was strong in both transport regimes. For grain diffusion, the best model, combining original descriptors with GVAE latent embeddings, achieved a test-set R-squared of 0.93; for grain-boundary diffusion, the corresponding model reached 0.94. In both cases, the model that fused raw descriptors with latent embeddings outperformed versions trained on either alone, indicating that the autoencoder’s latent space carries physically meaningful information about configurational relationships among diffusion pathways that fixed feature vectors miss. Predicted minimum-energy paths reproduced the saddle points of independently calculated NEB profiles across all eight SEI components, and a held-out validation set never touched during training or testing confirmed the model’s reliability.

Feature-importance analysis, performed by permutation, revealed what actually governs migration. Composition-derived descriptors such as melting temperature, space-group number, and ground-state volume ranked high statistically, but the authors interpret these as proxies for bonding character rather than direct causal variables. The physically direct signals were structural: the saddle-point indicator carried the largest importance score among structural features, followed by grain-boundary energy, boundary type, and coincidence site lattice value. Lower-sigma boundaries, which preserve better atomic registry between grains, supported smoother, lower-barrier pathways, while exposed surface orientation, particularly the (210) and (111) planes, shaped the local coordination geometry and bottleneck topology that determine how easily a lithium ion can hop.

The transport trends that emerged are strikingly chemistry-specific. Latent-space sampling showed lithium halides defining the lowest and most uniform barrier landscape, with mean migration barriers of just 0.12 eV for lithium chloride and 0.11 eV for lithium iodide, and narrow standard deviations below 0.10 eV. Lithium nitride and lithium carbonate, by contrast, exhibited much broader and higher barrier distributions, reaching means of 0.77 and 0.86 eV respectively, and heterogeneous interfaces were systematically more resistive than homogeneous ones, with halide-carbonate combinations exceeding 1.50 eV. Even the most favorable homogeneous boundaries, such as LiF-LiF and LiI-LiI, had mean barriers of 0.62 and 0.71 eV, higher than the best intra-grain values, confirming that grain boundaries act as bottlenecks even when their parent phases are good conductors.

The authors are candid about limitations: the analysis covers only vacancy-mediated diffusion, only crystalline inorganic phases, and static zero-temperature energetics, omitting the organic species, amorphous regions, and dynamic disorder of real SEI layers. Even so, the framework delivers something the field has lacked: a quantitative structure-transport map showing that SEI performance must be engineered through phase selection, surface orientation, grain-boundary character, and interface stability together, not through chemistry alone. Because localized low-energy pathways concentrate ionic flux and thereby promote nonuniform lithium deposition, controlling the microstructural distribution of grains and boundaries may prove just as important as choosing the right electrolyte additives in the quest to keep lithium-metal batteries dendrite-free.

Subject of Research: Machine learning prediction of lithium-ion transport barriers in the inorganic solid electrolyte interphase of lithium-metal batteries

Article Title: Deep learning assisted modeling of Li-ion transport in SEI: a graph neural network based study

Article References: Kulathuvayal, A. S., & Su, Y. (2026). Deep learning assisted modeling of Li-ion transport in SEI: a graph neural network based study. Frontiers in Batteries and Electrochemistry, 5, Article 1849012. https://doi.org/10.3389/fbael.2026.1849012

Image Credits: AI Generated

DOI: 10.3389/fbael.2026.1849012

Keywords: solid electrolyte interphase, lithium-metal batteries, graph neural networks, density functional theory, nudged elastic band, migration barrier, grain boundaries, lithium dendrites, variational autoencoder, machine learning, ion diffusion, battery materials

The scale of the problem is easy to underestimate. When neutrons slam into the lattice of a metal such as iron or tungsten, they knock atoms out of position, leaving behind vacancies and clusters of vacancies. As irradiation continues, these vacancy clusters grow into nano-voids, tiny empty cavities just nanometers across. Individually they are minuscule, but collectively they cause the material to swell, harden, and creep, degrading mechanical properties in ways that can shorten component lifetimes and compromise reactor safety. Fusion devices are particularly demanding because, unlike fission reactors, they subject structural materials to an especially harsh neutron spectrum that simultaneously creates both displacement damage and new chemical species inside the metal.

Among those species, helium is the most insidious. It is not present in the material to begin with; instead it is born inside the lattice through nuclear reactions between incoming neutrons and the atoms of the alloy itself. Helium atoms are essentially insoluble in most metals, so they drift toward defects, vacancies, dislocations, and especially grain boundaries, the interfaces between the microscopic crystallites that make up a polycrystalline metal. There they coalesce into bubbles. Grain boundaries act as traps, soaking up the mobile helium, but trapping is a double-edged solution: over time the accumulated helium can build pressure and concentration to the point where the boundary itself weakens, a process that embrittles the material and undermines the very interfaces that hold it together.

To understand the first half of this damage cascade, the HFIPS team needed to know what nano-voids actually look like when they are stable, a surprisingly difficult question because the possible atomic arrangements of a cavity grow combinatorially with its size. Their answer came from a new computational framework built on the differential evolution algorithm, an evolutionary optimization method that searches vast configuration spaces for the arrangement that minimizes energy. Applied to body-centered cubic metals, the framework mapped out the ground-state structures, energetic properties, and a linear discrete model describing how nano-void properties change with size. The simulations revealed a clear pattern: small nano-voids tend to adopt compact, polyhedral shapes, while larger voids develop faceted geometries bounded by low-energy crystallographic surfaces, notably the (110) and (100) planes. In other words, as voids grow, the metal effectively carves out cavities whose walls align with the crystallographic directions that cost the least energy.

That structural insight had a kinetic payoff. The researchers found that vacancies situated around a nano-void do not all behave identically; their energy levels depend on the local atomic environment, meaning that a vacancy adjacent to a smooth facet sits in a different energetic landscape than one tucked into a corner or edge of the cavity. By linking the energy levels of nano-voids directly to their atomic structures, the team built a bridge between what a void looks like and how it moves. This connection helps explain why some voids are remarkably stable while others migrate through the lattice, a distinction that ultimately governs whether defects disperse harmlessly or accumulate into the clusters that cause swelling, hardening, and creep. A linear discrete model relating void energetics to size gives researchers a quantitative tool for predicting this behavior without simulating every atom of every possible configuration.

With the defect physics established, the team turned to the second, and arguably more dangerous, half of the problem: what to do about the helium. Grain boundaries had long been viewed mainly as sinks, passive traps where helium collects and bubbles nucleate. Li’s group asked a different question: could some grain boundaries, rather than merely storing helium, actually help move it out of the material entirely? To answer it, the researchers combined high-throughput calculations with object kinetic Monte Carlo simulations, a modeling approach that tracks defect populations over experimentally relevant length and time scales far beyond what atom-by-atom dynamics alone can reach.

The simulations delivered a result with real engineering promise. Grain boundaries are not interchangeable; their atomic structure varies widely depending on how the adjacent crystals are misoriented. The team found that some boundaries, those with suitable atomic structures, act as rapid diffusion channels for helium. Along these boundaries, helium atoms move orders of magnitude faster than they can through the perfect lattice. Crucially, when such a fast-diffusion boundary is connected to a free surface of the material, it becomes a pipeline: helium that would otherwise stagnate in the interior can instead be carried along the boundary and released at the surface. The researchers observed this same behavior in both iron and tungsten, the two signature bcc metals of fusion structural materials research, suggesting the mechanism is general rather than an accident of one particular element.

From these findings the researchers distilled a design philosophy they describe as a capture-transport-expulsion strategy. Instead of relying on grain boundaries purely as passive sinks, a properly engineered microstructure would use them as a coordinated system: boundaries capture the mobile helium, transport it along fast diffusion pathways, and, when those pathways intersect free surfaces, expel it from the material altogether. This reframing moves helium management from passive capture toward active removal, offering a theoretical basis for grain-boundary engineering as a route to materials that resist helium-induced damage rather than merely tolerating it. In practice, such engineering would mean tailoring the types, densities, and connectivity of boundaries in an alloy so that the microstructure functions as a built-in helium plumbing network.

The significance for fusion energy development is considerable. One of the central obstacles to a viable fusion power plant has always been the lifetime of first-wall and blanket materials, which must endure decades of neutron exposure in a commercial-scale device. Every mechanism that mitigates swelling, embrittlement, and helium bubble formation extends component lifetimes, reduces maintenance, and improves the economics of fusion power. The HFIPS work contributes on two fronts simultaneously: a predictive, size-resolved model of how the vacancy defects that drive swelling form and evolve, and a microstructural design principle aimed specifically at the helium that embrittles boundaries. Because the atomistic picture was developed for body-centered cubic metals, it speaks directly to tungsten, the leading candidate for plasma-facing components, and to the iron-based ferritic and reduced-activation steels favored for structural applications.

The team frames the achievement in terms of fundamental understanding feeding directly into design. By understanding how these defects form and evolve, Li Xiangyan said, the researchers hope to provide useful guidance for developing fusion materials with better radiation resistance. The combination of evolutionary algorithms for ground-state searching, discrete models of defect energetics, and kinetic Monte Carlo simulation of defect populations illustrates how modern computational materials science can close the gap between atomic-scale mechanisms and engineering-scale strategies. What emerges is a picture of radiation damage that is not an unavoidable fate but a set of processes that can, in principle, be routed and redirected, with the right atomic-scale architecture turning a material’s own grain boundaries from collection points for helium into escape routes for it.

Subject of Research: Irradiation damage mechanisms and helium mitigation in fusion reactor structural materials

Article Title: Researchers reveal irradiation damage mechanisms and mitigation strategies for fusion reactor structural materials

Article References: Researchers reveal irradiation damage mechanisms and mitigation strategies for fusion reactor structural materials. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: fusion reactors, nano-voids, irradiation damage, helium bubbles, grain boundaries, tungsten, iron, differential evolution algorithm, kinetic Monte Carlo, radiation resistance, structural materials, HFIPS

Organic thin-film transistors are attractive because they can be printed or coated at low temperatures on flexible substrates, opening the door to wearable sensors, flexible displays, radio-frequency identification tags, and low-cost integrated circuits. Among the candidate semiconductors, TIPS pentacene stands out for its high solubility in common organic solvents, good environmental stability, and strong hole transport. Yet when the material crystallizes from solution, it tends to form needle-like domains that branch dendritically, point in many different directions, and leave large patches of the underlying dielectric exposed. Each of these imperfections interrupts the continuous pathways that carriers need to travel from source to drain.

The physics of the problem is well understood in outline. TIPS pentacene transports charge most efficiently along the long axis of its needle-shaped crystals, roughly the [210] crystallographic direction, where favorable π–π stacking combines with a low density of grain and twin boundaries. When that direction is parallel to the transistor channel, holes move along relatively unobstructed intermolecular highways; when it is perpendicular, carriers must cross more boundaries, and mobility can drop by as much as an order of magnitude. Previous work has also shown that grain-boundary mobility in TIPS pentacene is several orders of magnitude lower than the mobility inside a crystalline domain, so even narrow boundary regions can dominate the overall performance of a device.

External alignment techniques such as inkjet printing, solution shearing, and zone casting can produce highly ordered films, but they often demand specialized equipment and precise control of externally applied forces. Polymer-additive engineering takes a different approach: the semiconductor crystallization is regulated intrinsically, through changes in solution rheology, molecular interactions, phase separation, and crystal growth, simply by mixing an insulating polymer into the semiconductor solution before deposition. Because the additive goes directly into the ink, the method is inherently compatible with large-area and flexible manufacturing.

In the new study, the researchers compared two closely related styrenic polymers: polystyrene with a weight-average molecular weight of roughly 25 kg/mol, and poly(α-methylstyrene) with a weight-average molecular weight of roughly 10 kg/mol. Both carry pendant phenyl groups on a hydrocarbon backbone, but poly(α-methylstyrene) has an extra methyl substituent at the α-position of each repeating unit, which increases steric crowding near the backbone and can alter how the chains organize during solvent evaporation. The team screened both additives at 5, 10, 33, and 50 weight percent relative to total solids and identified 33 weight percent polystyrene and 10 weight percent poly(α-methylstyrene) as the optimized formulations for detailed comparison.

Quantitative image analysis of polarized optical micrographs revealed stark differences. Pristine TIPS pentacene films showed an average absolute misorientation angle of 36.46 ± 17.88 degrees, an average domain width of about 38.77 ± 24.10 micrometers with enormous variability, and crystal coverage of only 64.34 percent, meaning more than a third of the substrate stayed bare. Adding polystyrene cut the misorientation angle to 9.97 ± 7.29 degrees and raised coverage to 70.14 percent, but the domains remained narrow and their boundaries stayed pronouncedly dendritic, with feather-like or tooth-like edges visible in scanning electron micrographs. Poly(α-methylstyrene) did something qualitatively different: it produced nearly parallel domains with an average misorientation angle of just 1.07 ± 1.29 degrees, a comparatively uniform width of 75.13 ± 24.63 micrometers, and coverage of 83.17 percent.

The team interpreted these results through a grain-boundary-limited transport model in which conductive crystalline domains and resistive boundary regions act as resistors in series along the channel. In that picture, the inverse of the effective channel mobility grows approximately with the inverse of the domain width, so wider domains mean fewer low-mobility boundaries for a carrier to cross, while better alignment reduces orientation-dependent boundary penalties. Coverage matters too: uncovered dielectric regions introduce physical discontinuities and interdomain hopping barriers that the simplified model does not even capture, further suppressing measured mobility. Poly(α-methylstyrene) improved all three parameters at once, which is why its films formed the most continuous and least boundary-limited network.

The electrical data tracked the morphology closely. Average saturation mobility rose from 0.08 ± 0.06 square centimeters per volt-second for pristine devices to 0.18 ± 0.08 for polystyrene-blended devices and 0.32 ± 0.09 for poly(α-methylstyrene)-blended devices, with the best poly(α-methylstyrene) devices reaching approximately 0.5 square centimeters per volt-second, more than three times the pristine maximum. Subthreshold swing fell from 6.2 ± 1.2 to 4.3 ± 0.7 volts per decade, the effective trap density estimated from the subthreshold swing dropped from (8.9 ± 1.7) × 10¹² to (6.1 ± 1.0) × 10¹² per square centimeter per electron volt, and the on/off ratio climbed to (3.8 ± 1.5) × 10⁴. Threshold voltage also shifted from 5.5 ± 2.6 volts down to 1.0 ± 1.2 volts, consistent with less gate bias being needed to turn the channel on.

The authors are careful about what their comparison can and cannot prove. Because the two polymers differ in both molecular weight and optimized loading, the observed differences reflect the combined effects of polymer structure, molecular weight, and concentration rather than the α-methyl substitution alone. They also note that their measurements characterize lateral morphology only; vertical phase separation, which determines whether semiconductor or insulator sits near the charge-accumulating dielectric interface, was not directly measured and will require depth-profile XPS or ToF-SIMS in future work. Improved initial morphology likewise does not by itself establish better environmental or operational stability, which will need controlled aging, bias-stress, and illumination tests.

Even with those caveats, the demonstration is striking for its simplicity. A drop-cast solution, a slight substrate tilt to guide solvent flow, and a few weight percent of a commodity insulating polymer were enough to transform a disordered, patchy semiconductor film into a densely aligned crystalline network with tripled peak mobility. As flexible electronics move from laboratory curiosities toward wearable health monitors, printed displays, and disposable sensors, strategies that upgrade performance without new equipment or exotic materials may prove decisive. This study shows that sometimes the fastest way to better transistors is not a new semiconductor at all, but a smarter recipe for the one already in the bottle.

Subject of Research: Polymer-additive engineering of crystalline defects and charge transport in TIPS-pentacene organic thin-film transistors

Article Title: Styrenic polymer-additive engineering of crystalline defects and charge transport in TIPS-pentacene organic thin-film transistors

Article References: He, Z., & Asare-Yeboah, K. (2026). Styrenic polymer-additive engineering of crystalline defects and charge transport in TIPS-pentacene organic thin-film transistors. Frontiers in Nanotechnology, 8, Article 1943509. https://doi.org/10.3389/fnano.2026.1943509

Image Credits: AI Generated

DOI: 10.3389/fnano.2026.1943509

Keywords: organic thin-film transistors, TIPS pentacene, polystyrene, poly(α-methylstyrene), polymer additives, crystalline defects, grain boundaries, charge transport, flexible electronics, solution processing, field-effect mobility, Styrenic

The study, published in the Journal of Materials Science, examines a series of alloys with the composition V35Ti30Cr35-xCox, where the cobalt content x was varied systematically from 0 to 5, 10 and 15 atomic substitutions for chromium. This family belongs to the broader class of body-centered cubic (BCC) vanadium-titanium-based solid solution alloys, which have attracted sustained attention because they combine high hydrogen capacity with the ability to absorb and release hydrogen at near-ambient conditions. The research team, led by Tianhao Wu and corresponding author Xueling Hou, set out to map how cobalt content reshapes the hydrogen absorption and desorption kinetics and thermodynamics, the phase structure, the microstructure, the binding energy of hydrogen in the lattice, and the chemical states of the constituent elements.

The headline finding is that the alloy with ten cobalt substitutions, V35Ti30Cr25Co10, emerges as the clear winner of the series. It exhibits the optimal thermodynamic performance for both hydrogen uptake and release, cycling hydrogen more completely than its siblings. Just as importantly, the microstructure tells a story of why. The x = 10 composition developed the smallest and most uniform grains of any alloy in the series, and consequently the largest number of grain boundaries per unit volume. These internal interfaces do more than add surface area; they also confer enhanced resistance to pulverization, the gradual fracturing of alloy particles that plagues metal hydride beds over repeated cycles and degrades their performance in real-world tanks and compressors.

The physics behind this optimization is a delicate tug-of-war between competing effects, and the authors unpack it with unusual clarity. Hydrogen storage capacity in these alloys is strongly influenced by the lattice parameters of the crystal: a larger unit cell offers more interstitial room for hydrogen atoms, effectively raising capacity. But cobalt’s atomic radius is slightly smaller than chromium’s, so every substitution of cobalt for chromium tends to shrink the lattice parameters and the unit-cell volume. Left unchecked, that contraction erodes exactly the structural spaciousness that hydrogen storage depends on.

Against that negative, the team weighed a positive: cobalt’s higher electronegativity. Electronegativity governs how strongly the metal atoms attract the electrons of absorbed hydrogen, and a more electronegative partner element can improve the thermodynamics of hydrogen absorption and the energetics of the adsorption interface. At moderate cobalt contents, this electronic benefit helps the alloy absorb and desorb hydrogen more readily. The study found, however, that when cobalt substitution becomes excessive, at the x = 15 composition, the detrimental effect of the shrunken lattice parameters overwhelms the beneficial effect of cobalt’s higher electronegativity, and overall hydrogen storage performance suffers. The sweet spot sits in between, where the electronic advantages are retained while the lattice contraction remains tolerable.

Beyond capacity and thermodynamics, the optimal alloy also delivered practical dividends for engineering use. The x = 10 composition showed improved oxidation resistance, a valuable property because the surfaces of hydrogen storage alloys are constantly exposed to trace oxygen and moisture during cycling, and oxide layers can block hydrogen from reaching the reactive interior. The study further indicates that an appropriate cobalt content optimizes the hydrogen adsorption interface itself, smoothing the pathway by which gas-phase hydrogen molecules dissociate and enter the lattice. Together with the refined grain structure and pulverization resistance, these surface and interface improvements explain why the mid-range composition achieved more complete absorption-desorption cycles than either the cobalt-free baseline or the heavily cobalt-substituted variants.

The methodological breadth of the work is notable. Rather than measuring only bulk hydrogen uptake, the investigators probed phase structure and microstructure, computed binding energies, and analyzed chemical states, connecting macroscopic storage behavior to atomic-scale mechanisms. Binding energy calculations address how tightly hydrogen is held within interstitial sites, which determines whether desorption is easy or energetically costly. Chemical state analysis, informed by techniques of the kind pioneered in X-ray photoelectron spectroscopy of first-row transition metals, reveals how cobalt modifies the surface chemistry where hydrogen first makes contact with the alloy. This multi-scale picture, from unit-cell dimensions to grain boundaries to surface states, is precisely the kind of evidence needed to turn empirical composition screening into rational alloy design.

The context for this study is a rapidly maturing field. V-Ti-based solid solution alloys and Ti-V-Cr BCC-type high-entropy alloys have been extensively reviewed in recent years as leading candidates for solid-state hydrogen storage, and they have already found application in hydrogen compressors, where cyclic absorption and desorption are the operating mode. Cyclic stability has emerged as a central concern: repeated hydrogenation swells the lattice and repeated dehydrogenation contracts it, generating the mechanical stresses that pulverize particles and alter local structure over time. Studies of local structural changes in V-Ti-Cr hydrides during cycling confirm that degradation is a real and measurable phenomenon. By identifying a composition that resists pulverization while maintaining complete cycling, the Shanghai team addresses one of the key failure modes that has limited deployment.

What makes the result compelling for a general audience is its counterintuitive lesson: adding a smaller atom can improve a hydrogen storage alloy, but only up to a point. If one judged purely by lattice size, substituting a smaller atom for chromium would seem to be a mistake. Yet the electronic effect of cobalt, through its electronegativity and its influence on the hydrogen adsorption interface, buys real thermodynamic and kinetic gains, and the microstructural refinement it induces adds durability. The art of alloy design, the study shows, lies in finding the composition where these opposing influences balance, and for the V35Ti30Cr35-xCox family that balance point is x = 10.

The work was supported by the National Natural Science Foundation of China and the Foundation Strengthening Program in Technical Field of China. As hydrogen infrastructure scales up worldwide, incremental advances of this kind, a better understanding of how each elemental substitution ripples through lattice, grain structure, surface chemistry and cycle life, accumulate into the materials toolbox that practical storage systems will ultimately require. The V35Ti30Cr25Co10 alloy may not be the final word in hydrogen storage media, but it demonstrates with unusual precision how careful composition engineering can coax more complete, more durable hydrogen cycling out of one of the field’s most promising alloy platforms, and it offers other researchers a template for how electronic, structural and microstructural effects can be systematically balanced in the search for next-generation energy materials.

Subject of Research: Effect of cobalt substitution on the hydrogen storage performance and microstructure of V-Ti-Cr alloys

Article Title: Co addition on the hydrogen storage performance and microstructure of V35Ti30Cr35-xCox (x = 0, 5, 10, 15) alloys

Article References: Wu, T., Guan, L., Guo, J., Ouyang, C., Xiang, J., Huang, S., & Hou, X. (2026). Co addition on the hydrogen storage performance and microstructure of V35Ti30Cr35-xCox (x = 0, 5, 10, 15) alloys. Journal of Materials Science. https://doi.org/10.1007/s10853-026-13694-9

Image Credits: AI Generated

DOI: 10.1007/s10853-026-13694-9

Keywords: hydrogen storage, V-Ti-Cr alloys, cobalt substitution, metal hydrides, BCC alloys, microstructure, grain boundaries, pulverization resistance, hydrogen absorption desorption, thermodynamics, lattice parameters, energy materials