Materials research and analysis

Nature CommunicationsResearch article

Strong yet ductile heat-resistant aluminum alloy by additive manufacturing

A nanoscale boundary network turns rapid solidification into a heat-resistant architecture.

Alloy design Read analysis ↗

doi:10.1038/s41467-026-71926-7

Nature CommunicationsResearch article

Strong 3D-printed aluminium reinforced with ductile-transformable eutectic nano-skeleton

A continuous eutectic skeleton strengthens aluminium without behaving like a brittle ceramic cage.

Alloy design Read analysis ↗

doi:10.1038/s41467-026-72256-4

Nature CommunicationsResearch article

Machine learning driven discovery of low modulus biomedical titanium alloys for additive manufacturing

Machine learning, CALPHAD and print validation converge on a low-modulus β-titanium alloy.

Machine learning Read analysis ↗

doi:10.1038/s41467-026-71927-6

Nature CommunicationsResearch article

Intrinsic attraction driving the high temperature performance of additively manufactured aluminum alloys

Solute–vacancy and solute–dislocation attraction is used as an explicit alloy-design variable.

Alloy design Read analysis ↗

doi:10.1038/s41467-026-71390-3

Nature CommunicationsResearch article

Intrinsic edge dislocations promote high-temperature strength and ductility in additively manufactured refractory high-entropy alloys

As-built dislocations are retained as useful architecture rather than erased as processing damage.

High-entropy alloys Read analysis ↗

doi:10.1038/s41467-026-71995-8

Nature CommunicationsResearch article

3D-printed NiTi alloys for elastocaloric cooling

Defect control and bimodal grains reconcile cooling output with multi-million-cycle durability.

Functional alloys Read analysis ↗

doi:10.1038/s41467-026-71399-8

Nature CommunicationsResearch article

Operando X-ray scattering reveals ordering-mediated solidification in additive manufacturing

The melt is shown to carry short-range order that helps decide which grains form.

Operando science Read analysis ↗

doi:10.1038/s41467-026-73647-3

Nature CommunicationsResearch article

Bubble explosion induced melt pool instabilities in electron beam melting of aluminum alloy

Vapour bubbles are observed as active drivers of instability, not passive pore remnants.

Process physics Read analysis ↗

doi:10.1038/s41467-026-71118-3

Nature CommunicationsResearch article

Electric current-driven heterogeneous microstructures in dual-phase titanium alloys

Millisecond electrical processing creates a deliberately multiscale, multiphase titanium architecture.

Titanium Read analysis ↗

doi:10.1038/s41467-026-70561-6

Nature CommunicationsResearch article

Dynamic plastic deformation delocalization in FCC solid solution metals

A narrow stacking-fault-energy window distributes plasticity through competing slip and twinning.

Deformation Read analysis ↗

doi:10.1038/s41467-026-69046-3

Nature CommunicationsResearch article

Hierarchical heterogeneous ordering enables wide-temperature strength-ductility synergy in additively manufactured medium-entropy alloys

Grain, cell and ordered-precipitate hierarchies sustain performance from cryogenic to hot conditions.

Medium-entropy alloys Read analysis ↗

doi:10.1038/s41467-026-72261-7

Nature CommunicationsResearch article

Increasing fatigue resistance in ordered intermetallic alloys with multi-element symbiosis

Disordered nanolayers at ordered grain boundaries redirect fatigue damage away from brittle failure.

Intermetallics Read analysis ↗

doi:10.1038/s41467-026-70838-w

Nature CommunicationsResearch article

Ductile and scalable 3 GPa steel via a hierarchical microstructural architecture

A metre-scale maraging steel reaches the 3 GPa class without collapsing into near-brittle elongation.

Steel Read analysis ↗

doi:10.1038/s41467-026-74216-4

Nature CommunicationsResearch article

Parametrically upscaled model-based predictive platform for fatigue with location-specific microstructural linkages

Microstructure-sensitive fatigue prediction is transferred from small volumes to component locations.

Fatigue Read analysis ↗

doi:10.1038/s41467-026-72037-z

International Journal of Extreme ManufacturingResearch article

Interpretable machine learning integrated with physicochemical feature for developing additively manufactured ultra-high strength and ductility steel

Physicochemical descriptors make the ML model both useful and metallurgically interrogable.

Machine learning Read analysis ↗

doi:10.1088/2631-7990/ae5006

International Journal of Extreme ManufacturingCritical review

Machine learning-assisted process-structure-property correlation in laser metal additive manufacturing: a critical review

The useful unit of AM intelligence is the complete process–structure–property chain.

Machine learning Read analysis ↗

doi:10.1088/2631-7990/ae5297

International Journal of Extreme ManufacturingPerspective

Alloy design paradigms in additive manufacturing: a new era of material innovation

AM alloy design is mapped from adapting legacy grades toward closed-loop autonomous discovery.

Alloy design Read analysis ↗

doi:10.1088/2631-7990/ae45de

MRS BulletinPerspective

Additive manufacturing as a material machine: Designing geometry, microstructure, and behavior at once

AM is reframed as local material writing rather than shape production from a uniform feedstock.

Material architecture Read analysis ↗

doi:10.1557/s43577-026-01108-9

MRS BulletinReview article

Microstructure development and design in deformation-based metal additive manufacturing

Solid-state AM opens microstructure spaces that fusion processes cannot reach.

Solid-state AM Read analysis ↗

doi:10.1557/s43577-026-01075-1

MRS BulletinReview article

Targeted microstructural authoring through additive manufacturing of metals

Local thermal history is treated as a writable instruction for grain structure and phase state.

Microstructure Read analysis ↗

doi:10.1557/s43577-026-01070-6

Nature CommunicationsResearch article

Powder-size driven facile microstructure control in powder-fusion metal additive manufacturing processes

Powder size becomes a practical control variable for switching between coarse near-monocrystalline and fine equiaxed solidification structures.

Additive manufacturing Read analysis ↗

doi:10.1038/s41467-024-47257-w

Nature CommunicationsResearch article

In situ phase engineering during additive manufacturing enables high-performance soft-magnetic medium-entropy alloys

Rapid solidification is used to engineer phase constitution and magnetic performance directly during the build.

Additive manufacturing Read analysis ↗

doi:10.1038/s41467-024-54133-0

Nature CommunicationsResearch article

A strong fracture-resistant high-entropy alloy with nano-bridged honeycomb microstructure intrinsically toughened by 3D-printing

A nanoscale honeycomb architecture distributes damage and bridges cracks instead of relying on a uniformly hardened microstructure.

High-entropy alloys Read analysis ↗

doi:10.1038/s41467-024-45178-2

Nature CommunicationsResearch article

Additive manufacturing of an ultrastrong, deformable Al alloy with nanoscale intermetallics

A dense nanoscale intermetallic population raises aluminium strength beyond 700 MPa while preserving useful deformation.

Alloy design Read analysis ↗

doi:10.1038/s41467-024-48693-4

Research signals

Cross-study findings

Recurring directions across the papers, stated cautiously and tied to the underlying evidence.

Processes are becoming design variables.

Composition, feedstock, thermal history and deformation route are increasingly engineered together rather than treated separately.

Heterogeneity is being used deliberately.

Gradients, interfaces, metastable phases and controlled defects are being tuned to distribute deformation and damage.

Data-led research is moving closer to experiment.

The strongest studies connect prediction with physical constraints, experiments and validation.

Environmental assessment is becoming route-specific.

Composition, process route, recycling quality and system boundaries materially change life-cycle conclusions.

Nature MaterialsResearch article

Harnessing instability for work hardening in multi-principal element alloys

Controlled phase instability sustains work hardening at a strength level where conventional alloys usually lose ductility.

Alloy design Read analysis ↗

doi:10.1038/s41563-024-01871-7

Nature MaterialsResearch article

Quantifying short-range order using atom probe tomography

Atom probe tomography is developed from a compositional map into a quantitative probe of chemical short-range order.

Microstructure Read analysis ↗

doi:10.1038/s41563-024-01912-1

Nature CommunicationsResearch article

Generative learning facilitated discovery of high-entropy ceramic dielectrics for capacitive energy storage

A generative model searches a sparse high-entropy ceramic space and directs experiments toward dielectric compositions with stronger energy-storage performance.

Machine learning Read analysis ↗

doi:10.1038/s41467-024-49170-8

NatureResearch article

Machine-learning design of ductile FeNiCoAlTa alloys with high strength

Machine learning narrows a multicomponent alloy space toward compositions that preserve ductility while strengthening through controlled phase formation.

Machine learning Read analysis ↗

doi:10.1038/s41586-025-09160-2

npj Computational MaterialsResearch article

Application of machine learning to assess the influence of microstructure on twin nucleation in Mg alloys

A grain-resolved model separates the effects of orientation, size and neighbourhood on deformation-twin nucleation in magnesium.

Machine learning Read analysis ↗

doi:10.1038/s41524-024-01212-x

Nature CommunicationsPerspective

Materials design for hypersonics

Hypersonic materials must be designed as coupled thermal, chemical, mechanical and manufacturing systems rather than ranked by a single high-temperature property.

High-temperature Read analysis ↗

doi:10.1038/s41467-024-46753-3

NatureResearch article

A generative model for inorganic materials design

MatterGen generates candidate crystal structures conditioned on chemistry and target properties rather than screening only known databases.

Machine learning Read analysis ↗

doi:10.1038/s41586-025-08628-5

npj Computational MaterialsPerspective

Foundation models for materials discovery – current state and future directions

Foundation models can connect language, structures, spectra and simulation, but materials-specific evaluation and uncertainty remain underdeveloped.

Machine learning Read analysis ↗

doi:10.1038/s41524-025-01538-0

Nature Machine IntelligenceResearch article

A framework to evaluate machine learning crystal stability predictions

Crystal-stability models are evaluated under a common framework that exposes leakage, unrealistic splits and the difference between ranking and discovery.

Machine learning Read analysis ↗

doi:10.1038/s42256-025-01055-1

Nature Machine IntelligenceResearch article

Leveraging large language models for predictive chemistry

Language-model embeddings provide competitive chemical property prediction, particularly where labelled data are limited.

Machine learning Read analysis ↗

doi:10.1038/s42256-023-00788-1

Nature Machine IntelligenceResearch article

A multimodal large language model for materials science

MatterChat aligns crystal structures with language so researchers can query, compare and reason across geometric and textual materials information.

Machine learning Read analysis ↗

doi:10.1038/s42256-026-01214-y

Nature SynthesisResearch article

Navigating phase diagram complexity to guide robotic inorganic materials synthesis

Phase-diagram knowledge is converted into robotic experiment choices for complex inorganic synthesis.

Autonomous discovery Read analysis ↗

doi:10.1038/s44160-024-00502-y

Nature CommunicationsResearch article

Accelerated discovery of perovskite solid solutions through automated materials synthesis and characterization

Machine-learning screening, robotic synthesis and rapid characterization are joined into a closed experimental loop for perovskite solid solutions.

Autonomous discovery Read analysis ↗

doi:10.1038/s41467-024-50884-y

npj Computational MaterialsResearch article

Fine-tuning foundation models of materials interatomic potentials with frozen transfer learning

A frozen foundation potential can be adapted to new chemical domains with a fraction of the data required for training from scratch.

Machine learning Read analysis ↗

doi:10.1038/s41524-025-01727-x

Nature CommunicationsResearch article

Machine learning assisted composition design of high-entropy Pb-free relaxors with giant energy-storage

Machine learning guides high-entropy relaxor composition toward a rare combination of energy density, efficiency and breakdown strength.

Machine learning Read analysis ↗

doi:10.1038/s41467-025-56443-3

Nature CommunicationsResearch article

A foundation machine learning potential with polarizable long-range interactions for materials modelling

A foundation interatomic potential incorporates polarization and long-range interactions instead of restricting learning to local atomic neighbourhoods.

Machine learning Read analysis ↗

doi:10.1038/s41467-025-65496-3

Nature CommunicationsResearch article

Non-contact ultrasound to assist laser additive manufacturing

Air-coupled ultrasound modifies melt dynamics and grain development without placing a sonotrode in the build environment.

Additive manufacturing Read analysis ↗

doi:10.1038/s41467-025-62803-w

Nature CommunicationsResearch article

Oxide-dispersion-enabled laser additive manufacturing of high-resolution copper

Oxide dispersion changes laser absorption and microstructure sufficiently to print fine copper features without surrendering strength.

Additive manufacturing Read analysis ↗

doi:10.1038/s41467-025-58373-6

Nature CommunicationsResearch article

Harnessing metastability for grain size control in multiprincipal element alloys during additive manufacturing

Phase metastability interrupts epitaxial columnar growth and offers composition-based grain refinement during additive manufacturing.

Additive manufacturing Read analysis ↗

doi:10.1038/s41467-025-56616-0

Additive ManufacturingResearch article

A highly efficient computational approach for fast scan-resolved microstructure predictions in metal additive manufacturing on the scale of real parts

Scan-resolved thermal and microstructure simulation is accelerated to centimetre-scale Ti–6Al–4V parts within practical engineering times.

Additive manufacturing Read analysis ↗

doi:10.1016/j.addma.2024.104380

Research architecture

From composition to industrial performance

A practical reading structure for connecting fundamental mechanisms to manufacturing decisions and system-level consequences.

Composition

Alloy and materials design

Chemistries and formulations built around process conditions, service context and performance targets.

Process

Manufacturing physics

Solidification, deformation, heat flow, in-process control and route-specific process windows.

Structure

Microstructure and interfaces

Grains, phases, boundaries, porosity, defects and engineered heterogeneity.

Performance

Properties and life

Strength, ductility, fatigue, reliability, functional response and environmental resistance.

Systems

Qualification, LCA and data

Validation, life-cycle evidence, data infrastructure and industrial adoption.

Additive ManufacturingResearch article

Machine learning prediction of mechanical properties in metal additive manufacturing

A curated literature dataset is used to predict mechanical properties while exposing the process and material variables that drive model decisions.

Machine learning Read analysis ↗

doi:10.1016/j.addma.2024.104320

Additive ManufacturingResearch article

Interpretable machine learning approach for exploring process-structure-property relationships in metal additive manufacturing

Gaussian-process models and error-guided experiments expose a usable process window rather than returning only a property prediction.

Machine learning Read analysis ↗

doi:10.1016/j.addma.2024.104187

Additive ManufacturingResearch article

Multi-scale microstructure manipulation of an additively manufactured CoCrNi medium entropy alloy for superior mechanical properties and tunable mechanical anisotropy

Heat treatment and multiscale structural control convert print-induced texture from a fixed liability into a tunable mechanical variable.

Additive manufacturing Read analysis ↗

doi:10.1016/j.addma.2024.104104

Acta MaterialiaResearch article

Harnessing additive manufacturing-induced microstructure and solute heterogeneities for the design of precipitation-strengthened alloys

Print-induced solute and defect heterogeneity is retained and used to improve subsequent precipitation strengthening.

Additive manufacturing Read analysis ↗

doi:10.1016/j.actamat.2025.121423

CIRP AnnalsKeynote review

Sustainable machining: Recent technological advances

Sustainable machining is evaluated across energy, tooling, lubrication, digital control and production quality rather than reduced to coolant substitution.

Sustainability & LCA Read analysis ↗

doi:10.1016/j.cirp.2024.06.001

Journal of Cleaner ProductionResearch article

Incorporating composition into life cycle assessment of steel grades

Treating all steel as a single inventory can conceal large environmental differences caused by alloying composition and production route.

Sustainability & LCA Read analysis ↗

doi:10.1016/j.jclepro.2024.143538

Resources, Conservation and RecyclingResearch article

Simulation-based life cycle assessment of secondary materials from recycling of lithium-ion batteries

Process simulation is used to compare recycled battery intermediates with primary production under explicit allocation choices.

Sustainability & LCA Read analysis ↗

doi:10.1016/j.resconrec.2023.107384

Renewable and Sustainable Energy ReviewsReview article

Life cycle assessment in energy-intensive industries: Cement, steel, glass, plastic

A cross-industry review shows that methodological fragmentation can matter as much as the technology being compared.

Sustainability & LCA Read analysis ↗

doi:10.1016/j.rser.2024.115245

Sustainable Production and ConsumptionResearch article

An environmental assessment framework for circular steel products

Material-flow analysis and LCA are combined so that circular steel strategies are judged by both resource circulation and environmental consequence.

Sustainability & LCA Read analysis ↗

doi:10.1016/j.spc.2024.05.031

Resources, Conservation and RecyclingResearch article

Global stagnation and regional variations in steel recycling

Global recycled iron input has stagnated near 30%, while national systems range from very low to very high recycling dependence.

Sustainability & LCA Read analysis ↗

doi:10.1016/j.resconrec.2025.108363

Sustainable Production and ConsumptionReview article

Environmental and economic sustainability of additive manufacturing: A systematic literature review

Environmental and economic claims for additive manufacturing are tested against system boundaries, utilization, feedstock, energy and product-level consequences.

Sustainability & LCA Read analysis ↗

doi:10.1016/j.spc.2024.10.012