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Declarative specifications have a vital role to play in developing safe and dependable software systems. Writing specifications correctly, however, remains particularly challenging. This paper presents a controlled experiment on using large language models (LLMs) to write declarative formulas in the well-known language Alloy. Our use of LLMs is three-fold. One, we employ LLMs to write complete Alloy formulas from given natural language descriptions (in English). Two, we employ LLMs to create alternative but equivalent formulas in Alloy with respect to given Alloy formulas. Three, we employ LLMs to complete sketches of Alloy formulas and populate the holes in the sketches by synthesizing Alloy expressions and operators so that the completed formulas accurately represent the desired properties (that are given in natural language). We conduct the experimental evaluation using 11 well-studied subject specifications and employ two popular LLMs, namely ChatGPT and DeepSeek. The experimental results show that the LLMs generally perform well in synthesizing complete Alloy formulas from input properties given in natural language or in Alloy, and are able to enumerate multiple unique solutio

The growing need for structural materials with strength, mechanical stability, and durability in extreme environments is driving the development of high entropy alloys. These are materials with near equiatomic mixing of five or more principal elements, and such compositional complexity often leads to improvements in mechanical properties and high thermal stability, etc. Thus, high-entropy alloys have found their applications in domains like aerospace, biomedical, energy storage, catalysis, electronics, etc. However, the vast compositional design and experimental exploration of high-entropy alloys are both time consuming and expensive and require a large number of resources. Machine learning techniques have thus become essential for accelerating high entropy alloys discovery using data driven predictions of promising alloy combinations and their properties. Hence, this work employs a machine learning framework that predicts high entropy alloy hardness from elemental descriptors such as atomic radius, valence electron count, bond strength, etc. Machine learning regression models, like LightGBM, Gradient Boosting Regressor, and Transformer encoder, were trained on experimental data. A

The pursuit of novel alloys tailored to specific requirements poses significant challenges for researchers in the field. This underscores the importance of developing predictive techniques for essential physical properties of alloys based on their chemical composition and processing parameters. This study introduces AlloyBERT, a transformer encoder-based model designed to predict properties such as elastic modulus and yield strength of alloys using textual inputs. Leveraging the pre-trained RoBERTa encoder model as its foundation, AlloyBERT employs self-attention mechanisms to establish meaningful relationships between words, enabling it to interpret human-readable input and predict target alloy properties. By combining a tokenizer trained on our textual data and a RoBERTa encoder pre-trained and fine-tuned for this specific task, we achieved a mean squared error (MSE) of 0.00015 on the Multi Principal Elemental Alloys (MPEA) data set and 0.00611 on the Refractory Alloy Yield Strength (RAYS) dataset. This surpasses the performance of shallow models, which achieved a best-case MSE of 0.00025 and 0.0076 on the MPEA and RAYS datasets respectively. Our results highlight the potential o

We present the new concept of photonic alloy as a non-periodic topological material. By mixing non-magnetized and magnetized rods in a non-periodic 2D photonic crystal configuration, we realized photonic alloys in the microwave regime. Our experimental findings reveal that the photonic alloy sustains non-reciprocal chiral edge states (CESs) even at very low concentration of magnetized rods. The non-trivial topology and the associated edge states of these non-periodic systems can be characterized by the winding of the reflection phase. Our results indicate that the threshold concentrations for the investigated system within the first non-trivial band gap to exhibit topological behavior approach zero in the thermodynamic limit for substitutional alloys, while the threshold remains non-zero for interstitial alloys. At low concentration, the system exhibits an inhomogeneous structure characterized by isolated patches of non-percolating magnetic domains that are spaced far apart within a topologically trivial photonic crystal. Surprisingly, the system manifests CESs despite a local breakdown of time-reversal symmetry rather than a global one. Photonic alloys represent a new category of

Magnesium (Mg) and its alloys have attracted considerable attention owing to their excellent biodegradable properties and biocompatibility. Novel Mg-Sn-Ge ternary Mg alloys were developed as potential biodegradable materials for orthopedic applications because of their alloying elements naturally present in humans. The feasibility of these alloys was investigated in terms of mechanical properties, degradation, cytocompatibility, and hemocompatibility. The hardness and elastic modulus of Mg-2Sn-xGe alloys were improved significantly by increasing the Ge content. Among all the alloys, the Mg-2Sn-3Ge alloy displays outstanding biodegradable properties, as evidenced by the electrochemical tests and hydrogen evolution. The degradation products detected on the corroded alloy surfaces weaken at higher Ge levels. The in vitro cytotoxicity assay and hemolysis test showed that the Mg-2Sn-xGe alloys exhibit favorable biocompatibility and hemocompatibility, except for the Mg-2Sn-2Ge alloy.

The structural and magnetic properties of the as-cast and annealed V$_{0.6-x}$Si$_x$Ti$_{0.4}$ ($x$ = 0, 0.05, 0.10, 0.15) alloy superconductors are reported here. It is found that addition of silicon to the V-Ti alloys results in eutectic precipitation of Ti$_{5}$Si$_3$-phase in the body centred cubic (bcc) $β$-V-Ti matrix. In the as-cast V$_{0.6-x}$Si$_x$Ti$_{0.4}$ alloys, the superconducting transition temperature (T$_{C}$) changes non-monotonically with increasing silicon content whereas after annealing, it is about 7.7 K for all the alloys. On the other hand, the upper critical field decreases and the coherence length increases after annealing in the x = 0.10 alloy. The variations in the superconducting properties in the alloys are related to the solubility of 6 at.% Si in the V$_{0.60}$Ti$_{0.40}$ alloy and the vanadium enrichment in the $β$ matrix due to the precipitation of Ti$_{5}$Si$_3$ phase.

Recently, a photonic alloy with non-trivial topological properties has been proposed, based on the random mixing of Yttrium Iron Garnet (YIG) and magnetized YIG rods. When the doping concentration of magnetized YIG rods is less than one, a chiral edge state (CES) of the topological photonic alloy appears in the frequency range of the non-trivial topological gap of the magnetized YIG crystal. In this work, we surprisingly find that by randomly mixing the Perfect Electric Conductor (PEC) and magnetized YIG rods in a square lattice, the photonic alloy system with appropriate doping concentrations can present CES in special frequency intervals even when both components support the propagation of bulk states. Analyzing the band structure of two components, we noticed a shift between the first trivial bandgap for PEC and the first topological bandgap for magnetized YIG. When calculating the transmission spectrum of the photonic alloy, we discovered that the frequency range for the topological gap gradually opens from the lower limit frequency of the bandgap for PEC to the bandgap for the magnetized YIG rods. The topological gap opening occurs as the doping concentration of magnetized YIG

The "titanium fire" as produced during high pressure and friction is the major failure scenario for aero-engines. To alleviate this issue, Ti-V-Cr and Ti-Cu-Al series burn resistant titanium alloys have been developed. However, which burn resistant alloy exhibit better property with reasonable cost needs to be evaluated. This work unveils the burning mechanisms of these alloys and discusses whether burn resistance of Cr and V can be replaced by Cu, on which thorough exploration is lacking. Two representative burn resistant alloys are considered, including Ti14(Ti-13Cu-1Al-0.2Si) and Ti40(Ti-25V-15Cr-0.2Si)alloys. Compared with the commercial non-burn resistant titanium alloy, i.e., TC4(Ti-6Al-4V)alloy, it has been found that both Ti14 and Ti40 alloys form "protective" shields during the burning process. Specifically, for Ti14 alloy, a clear Cu-rich layer is formed at the interface between burning product zone and heat affected zone, which consumes oxygen by producing Cu-O compounds and impedes the reaction with Ti-matrix. This work has established a fundamental understanding of burning resistant mechanisms for titanium alloys. Importantly, it is found that Cu could endow titanium a

Eutectic high entropy alloys (EHEAs) are emerging as an exciting new class of structural alloys as they have shown very promising mechanical properties. However, how to design these alloys has been a challenge. In this work, a simple approach is presented for designing EHEAs. The introduced approach uses the composition of binary and ternary eutectic alloys for finding the composition of EHEAs. The approach is based on the assumption that EHEAs are originated from binary and ternary eutectic alloys. The approach is applied for alloy systems Al-Co-Cr-Fe-Ni, Co-Cr-Fe-Ni, Co-Cr-Fe-Ni-Ti, and Co-Cr-Fe-Ni-Ta and several EHEAs are predicted for these alloy systems. The predicted results are verified with thermodynamic simulations and experimental data. The results show that the introduced approach can be considered as a feasible and easy-to-use method for designing EHEAs. Based on the developed approach, any binary eutectic alloy can be used for designing multicomponent eutectic alloys.

Developing ductile refractory BCC alloys has remained a challenge. The intrinsic ductility (D) of an alloy is the ratio of surface energy ($γ_s$) and unstable stacking fault energy ($γ_{usfe}$). Lowering the valence electron concentration has been shown to improve the intrinsic ductility of refractory alloys. However, Re has been widely used to ductilize W, contrary to the low valency criteria suggested in the literature. Here we use density functional theory to calculate the enthalpy of formation, $γ_{usfe}$ and $γ_s$ of Group IV, V, VI elements and their 25 equiatomic binary alloys in BCC crystal structure. We found that positive enthalpy leads to a considerable reduction in $γ_{usfe}$ compared to composition averaged value, resulting in improved intrinsic ductility. Enthalpy is maximum at the equiatomic concentrations indicating the highly repulsive interaction between the alloy constituents and vicer-versa. We found that the repulsive interaction between the alloy constituents leads to a reduction in $γ_{usfe}$, making alloys intrinsically ductile.

In this communication,we propose a sustainable way to produce high entropy alloys from alloy scraps called Alloy mixing.We successfully demonstrate this method using a near equimolar CrCuFeMnNi HEA. Alloy scraps (304L stainless steel, Nichrome 80 and electrical wire grade Copper) obtained from various sources were melted together using vacuum arc melting along with minor additions of Mn and Cr to achieve the equiatomic composition.The alloy was characterized using X-ray Diffraction (XRD) and Scanning Electron Microscopy, which confirmed that the alloy produced through Alloy mixing exhibits a microstructure similar to that of the alloy with the same composition produced through conventional melting of pure elements

Interest in high entropy alloy thermoelectric materials is predicated on achieving ultralow lattice thermal conductivity $κ\sub{L}$ through large compositional disorder. However, here we show that for a given mechanism, such as mass contrast phonon scattering, $κ\sub{L}$ will be minimized along the binary alloy with the highest mass contrast, such that adding an intermediate-mass atom to increase atomic disorder can increase thermal conductivity. Only when each component adds an independent scattering mechanism (such as adding strain fluctuation to an existing mass fluctuation) is there a benefit. In addition, both charge carriers and heat-carrying phonons are known to experience scattering due to alloying effects, leading to a trade-off in thermoelectric performance. We apply analytic transport models, based on perturbation and effective medium theories, to predict how alloy scattering will affect the thermal and electronic transport across the full compositional range of several pseudo-ternary and pseudo-quaternary alloy systems. To do so, we demonstrate a multicomponent extension to both thermal and electronic binary alloy scattering models based on the virtual crystal approxima

A multi-stimuli cooling cycle can be used to increase the cyclic caloric performance of multicaloric materials like Ni-Mn-In Heusler alloys. However, the use of a uniaxial compressive stress as an additional external stimulus to a magnetic field requires good mechanical stability. Improvement of mechanical stability and strength by doping has been shown in several studies. However, doping is always accompanied by grain refinement and a change in transition temperature. This raises the question of the extent to which mechanical strength is related to grain refinement, transition temperature, or precipitates. This study shows a direct comparison between a single-phase Ni-Mn-Sn and a two-phase Gd-doped Ni-Mn-In alloy with the same transition temperature and grain size. It is shown that the excellent magnetocaloric properties of the Ni-Mn-In matrix are maintained with doping. The isothermal entropy change and adiabatic temperature change are reduced by only 15% in the two-phase Ni-Mn-In-Heusler alloy compared to the single-phase alloy, which is resulting from a slight increase in thermal hysteresis and the width of the transition. Due to the same grain size and transition temperature,

Metal chalcogenide is a promising material for studying novel underlying physical phenomena and nanoelectronics applications. Here, we systematically investigate the crystal structure and electronic properties of the AlSe surface alloy on Al (111) using scanning tunneling microscopy, angle-resolved photoelectron spectrometer, and first-principle calculations. We reveal that the AlSe surface alloy possesses a hexagonal closed-packed structure. The AlSe surface alloy comprises two atomic sublayers (Se sublayer and Al sublayer) with 1.16 A along the z direction. The dispersion shows two hole-like bands for AlSe surface alloy located at about -2.2 eV, far below the Fermi level, which is sharply different from other metal chalcogenide and binary alloys. These two bands mainly derive from the in-plane orbital of AlSe (px and py). These results provide implications for related Al-chalcogen interface. Meanwhile, AlSe alloy have an advantage of large-scale atomic flatness and a wide band gap near the Fermi level in serving as an interface for two-dimensional materials.

In this work we introduce a metal-oxide bond-energy model for alloy oxides based on pure-phase bond energies and bond synergy factors that describe the effect of alloying on the bond energy between cations and oxygen, an important quantity to understand formation and stability of passive films. This model is parameterized for binary cation-alloy oxides using density-functional theory energies and is shown to be directly transferable to multi-component alloy oxides. We parameterized the model for alloy oxide energies with metal cations that form the basis of corrosion resistant alloys, including Fe, Ni, Cr, Mo, Mn, W, Co, and Ru. We find that isoelectronic solutes allow quantification of pure-phase bond energies in oxides and that the calculated bond energy values give sensible results compared to common experience, including the role of Cr as the passive-layer former in Fe-Ni-Cr alloys for corrosion applications. Additionally, the bond synergy factors give insights into the mutual strengthening and weakening effects of alloying on cation-oxygen bonds and can be related to enthalpy of mixing and charge neutrality constraints. We demonstrate how charge neutrality can be identified an

We describe a first-principles statistical mechanics method to calculate the free energies of crystalline alloys that depend on temperature, composition, and strain. The approach relies on an extension of the alloy cluster expansion to include an explicit dependence on homogeneous strain in addition to site occupation variables that track the degree of chemical ordering. The method is applied to the Si-Ge binary alloy and is used to calculate free energies that describe phase stability under arbitrary epitaxial constraints. We find that while the incoherent phase diagram (in which coexisting phases are not affected by coherency constraints) hosts a miscibility gap, coherent phase equilibrium predicts ordering and negative enthalpies of mixing. Instead of chemical instability, the chemo-mechanical free energy exhibits instabilities along directions that couple the composition of the alloy with a volumetric strain order parameter. This has fundamental implications for phase field models of spinodal decomposition as it indicates the importance of gradient energy coefficients that couple gradients in composition with gradients in strain.

Fe-based shape memory alloys (Fe-SMAs) belong to smart metallic materials that can memorize or restore their preset shape after experiencing a substantial amount of deformation under heat, stress, or magnetic stimuli. Fe-SMAs have remarkable thermomechanical properties and have attracted significant interest because of their potential merits, such as cost-effective alloying elements, superior workability, weldability, a stable superelastic response, and low-temperature dependence of critical stress required for stress-induced martensitic transformation. Therefore, Fe-SMAs can be an intriguing and economical alternative to other SMAs. The recent advancements in fabrication methods of conventional metals and SMAs are helping the production of customized powder composition and then customized geometries by additive manufacturing (AM). The technology in these areas, i.e., fabrication techniques, experimental characterization, and theoretical formulations of Fe-SMAs for conventional and AM has been rapidly advancing and is lacking a comprehensive review. This paper provides a critical review of the recent developments in Fe-SMAs-related research. The conventional and AM-based methods of

Predicting the structural response of advanced multiphase alloys and understanding the underlying microscopic mechanisms that are responsible for it are two critically important roles modeling plays in alloy development. An alloys demonstration of superior properties, such as high strength, creep resistance, high ductility, and fracture toughness, is not sufficient to secure its use in widespread application. Still, a good model is needed, to take measurable alloy properties, such as microstructure and chemical composition, and forecast how the alloy will perform in specified mechanical deformation conditions, including temperature, time, and rate. In this bulletin, we highlight recent achievements by multiscale modeling in elucidating the coupled effects of alloying, microstructure, and the dynamics of mechanisms on the mechanical properties of polycrystalline alloys. Much of the understanding gained by these efforts relied on integration of computational tools that varied over many length and time scales, from first principles density functional theory, atomistic simulation methods, dislocation and defect theory, micromechanics, phase field modeling, single crystal plasticity, an

In this progress report we present a new approach to the ab-initio guided bottom up design of beta-Ti alloys for biomedical applications using a quantum mechanical simulation method in conjunction with experiments. Parameter-free density functional theory calculations are used to provide theoretical guidance in selecting and optimizing Ti-based alloys with respect to three constraints: (i) the use of non-toxic alloy elements; (ii) the stabilization of the body centered cubic beta phase at room temperature; (iii) the reduction of the elastic stiffness compared to existing Ti-based alloys. Following the theoretical predictions, the alloys of interest are cast and characterized with respect to their crystallographic structure, microstructure, texture, and elastic stiffness. Due to the complexity of the ab initio calculations, the simulations have been focused on a set of binary systems of Ti with two different high melting bcc metals, namely, Nb and Mo. Various levels of model approximations to describe mechanical and thermodynamic properties are tested and critically evaluated. The experiments are conducted both, on some of the binary alloys and on two more complex engineering alloy