Beta Titanium Alloy Additive Manufacturing Composition
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Solution Overview
Problem
Traditional titanium-based alloys for additive manufacturing face challenges in manufacturability, mechanical performance, and microstructure stability, with limitations in hot cracking susceptibility, solidification range, and phase architecture, leading to suboptimal properties and high experimental development costs.
Innovation Solution
A titanium-based alloy composition with specific weight percentages of elements such as aluminum, vanadium, molybdenum, tin, niobium, and chromium is designed to improve manufacturability, reduce hot cracking susceptibility, and enhance mechanical properties by optimizing the martensitic start temperature and microstructure, using a computational materials modeling approach to identify optimal alloy compositions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Strength
If traditional beta titanium alloys are used for additive manufacturing, then mechanical strength can be achieved, but hot cracking susceptibility increases and manufacturability deteriorates
Solution Approach 1:
The patent applies parameter changes by modifying the alloy composition parameters within specific ranges (Al: 3.0-7.0%, V: 3.0-10.0%, Mo: 3.0-10.0%, etc.) and satisfying the mathematical relationship 0.027V+0.178Fe+0.055(Mo+0.5W)+0.016Zr+0.044Cr+0.033(Nb+Ta)+0.053Sn>1.0. This systematic parameter optimization resolves the contradiction by achieving both improved manufacturability (reduced hot cracking susceptibility) and maintained mechanical strength through controlled compositional adjustments.
2Object-affected harmful factors
If alloy composition is optimized for reduced solidification range, then hot cracking susceptibility decreases, but alloy design complexity increases
Solution Approach 1:
The patent uses parameter changes by defining specific compositional ranges and a mathematical constraint (0.027V+0.178Fe+0.055(Mo+0.5W)+0.016Zr+0.044Cr+0.033(Nb+Ta)+0.053Sn>1.0) that directly controls solidification range and hot cracking susceptibility. This approach systematically reduces harmful factors while managing design complexity through a clear, quantifiable framework.
Solution Approach 2:
The patent employs feedback by using computational materials modeling to predict alloy behavior and guide composition optimization. The modeling provides feedback on how compositional changes affect solidification range and cracking susceptibility, enabling iterative refinement of the alloy design to achieve optimal performance.
3Reliability
If experimental development is conducted to optimize alloy properties, then material performance can be improved, but development costs increase
Solution Approach 1:
The patent replaces extensive experimental trial-and-error with computational materials modeling. This substitution of computational methods for physical experimentation significantly reduces development costs by predicting alloy behavior in silico before physical prototyping, while still achieving reliable material performance optimization.
Solution Approach 2:
The patent applies preliminary action by using computational modeling to pre-optimize alloy composition before physical manufacturing. This preliminary computational work identifies the optimal compositional range and satisfies the mathematical relationship, reducing the need for costly iterative experimental development and accelerating the path to reliable material performance.
Data Source
AI summary
A titanium-based alloy composition consisting in weight percent, of: 3.0 to 7.0% aluminium, 3.0 to 10.0% vanadium, 3.0 to 10.0% molybdenum, 2.0 to 7.0% tin, 0.0 to 6.0% zirconium, 0.0 to 5.0% niobium, 0.0 to 0.5% iron, 0.0 to 4.0% chromium, 0.0 to 2.0 tungsten, 0.0 to 0.5 % nickel, 0.0 to 0.5% tantalum, or between 0.0 to 2. tantalum when the sum of niobium and tantalum is 5.0% or less, 0.0 to 0.5% cobalt, 0.0 to 0.75% silicon, 0.0 to 0.5% boron, 0.0 to 0.5% carbon, 0.0 to 0.5% oxygen, 0.0 to 0.5% hydrogen, 0.0 to 0.5% nitrogen, 0.0 to 0.5% palladium, 0.0 to 0.5% lanthanum, 0.0 to 0.5% manganese or 0.0 to 2.5% manganese when the sum of chromium and manganese is 4.0 wt. % or less, 0.0 to 1.0% hafnium, the balance being titanium and incidental impurities which satisfies the following relationship: 0.027V+0.178Fe+0.055(Mo+0.5W)+0.016Zr+0.044Cr+0.033(Nb+Ta)+0.053Sn>1.0 where Mo, W, V, Zr, Sn, Cr, Fe, Ta and Nb represent amounts of molybdenum, tungsten, vanadium, zirconium, tin, chromium, iron, tantalum and niobium in wt. % respectively.