Materials manufacturing science is focused on discovery, innovation, and maturation of manufacturing innovations to facilitate agile, adaptive, mobile processing and manufacturing capabilities to enable superior performance and implementation of cost-reduction methodologies.
Flexible Hybrid Electronics
ARL's flexible hybrid electronics work focuses on developing the capability to integrate high-performance electronics with challenging form factors to enable new system functionalities by virtue of additive manufacturing.
Dr. Eric Forsythe firstname.lastname@example.org 301-394-0606
Additive Manufacturing Research
Additive Manufacturing (AM) technologies are perceived as processing methods to engage new performance capability from materials. The processes offer substantial manufacturing flexibility while enabling new approaches from material synthesis to hybridization and structural design engineering. Readily available material supply tends to be focused less on high-performance structural applications and is limited by commercial machine sources and well-defined process strategies. Recently, AM fabricated solutions have been explored for the automotive, aerospace, and defense markets with promising results. However, the military performance standards need to be achieved before AM parts can be certified and qualified for high-tech arenas. The certification and qualification procedures for single-manufacture single-product processes remain a significant unknown. Holistic process optimization through in-situ characterization and feedback, and simulated manufacturing will decrease the time of delivery for future product enabling rapid laboratory to field solutions. ARL enables new generations of performance through innovative materials and open architecture equipment, allowing full control of design and processing parameters in the manufacturing process. Ongoing research includes: material synthesis, design optimization, cold-sprayed particle dynamics and high-fidelity depositions, and in-situ process monitoring. Results are supported with robust characterization tools to enable strategic design with a full suite of AM technologies.
Mr. Kyu Cho email@example.com 410-306-0820
Metals in Additive Manufacturing
This research area is focused on closing the gap between AM of metals for prototyping and AM of certified/qualified structural components for the Army. Databases need to be developed to establish microstructure/processing/property relations for a wide range of metallic alloys to enable process optimization for improved part performance and to enable development of machine-learning algorithms for AM, which can greatly reduce process-parameter development time for new materials; thus, expediting transition to the Warfighter. New feedstocks are required for AM of metals that are suitable for Army operating conditions. Current areas of effort include: alloy design and development for AM processing, thermal-mechanical process modeling; modeling of evolution of AM microstructures; micromechanical modeling of AM material performance, including high strain-rate failure mechanisms; AM process characterization and development, including melt and nonmelt-based processes; AM of indigenous materials; design for AM, including topological optimization algorithm development; certification and qualification of AM components; and process and property enhancement via energy coupled to matter (ECM).
Dr. Brandon McWilliams firstname.lastname@example.org 410-306-2237
Energy Coupled to Matter
Energy coupled to matter (ECM) is an emerging technology that goes beyond the traditional process optimization factors of scale, composition, temperature, and pressure. It holds great promise in facilitating the realization of transformal materials through the aid of externally applied fields. The application of fields may alter phase transformation pathways, create new microstructures, shift equilibrium favoring new metastable alloys, align phases, manipulate and shape nanoscale architectures, and produce materials with revolutionary structural and multifunctional properties otherwise unattainable by conventional processing and production methods. The application of external fields, or combinations thereof, which include electric, magnetic, acoustic, microwave, radiation, and others, offers the unique opportunity to direct the architecture of materials features across atomic, molecular, micro, meso, and continuum levels. These fields may either be used to induce a permanent material property improvement or to selectively activate enhanced time-dependent properties via dynamic stimulation.
As technical challenges are overcome through basic research, a fundamental understanding of the mechanisms influencing field-material interactions and the phenomena that control manipulation of applied fields will be realized. This will be aided by the discovery of in-situ characterization methods for analyzing materials under high-energy fields, the development of predictive models for simulating the influence of applied fields on various materials, and a combination of additional experimental, modeling, and characterization efforts that have yet to be explored.
Technological advancements in the ECM discipline will have a significant impact on Army capabilities in the near and distant future for a number of key areas that include, but are not limited to: (1) novel materials with tailored microstructures to produce unprecedented physical and mechanical properties, (2) enhanced processing and manufacturing capabilities for rapid-rate production of net-shape components in extreme environments, and (3) adaptive/responsive protection and lethality applications that can be controlled/activated in real-time and used in-theater.
Additive Manufacturing, Direct Write, and Hybrid Manufacturing
Advances in materials and manufacturing science will enable expanded capabilities for Soldiers, especially at the point-of-need. AM allows Soldiers to produce a product as close to the point-of-need as possible. However, it is unlikely that every AM technology will be able to be deployed. To expand the operational envelope of in-field manufacturing units, it is necessary to develop manufacturing technologies that are material-agnostic and adaptive to the Soldier’s need. Hybrid manufacturing research at ARL encompasses multi-material manufacturing of structural and functional devices through the mixture of AM, subtractive manufacturing, direct write, and other techniques. Hybrid manufacturing offers the capability to mix materials on demand, and also provides a path to go beyond layer-by-layer fabrication with the goal of achieving true 3-D printing. The assembly concepts achieved by hybrid manufacturing methods result in new levels of performance being attained through design, material, and process optimization strategies. Hybrid manufacturing of materials is achieved in a facility with great versatility and technical capability, expanding the performance envelope for materials which enhance the comfort, protection, and lethality of the Warfighter.
Mr. Marc Pepi, email@example.com 410-306-0848
Predictive Analytics for Additively Manufactured Part Performance
For its versatility, additive manufacturing (AM) is the method of choice for prototyping, customized design, complex geometry, and part production. Significant research challenges remain in order to fully utilize this capability to produce metallic components on-demand and at the point-of-need which will meet Army mission requirements at the tactical edge. Reliability and reproducibility of commercial metal AM systems are still generally quite low. Robust and high-confidence performance prediction is needed to certify individual parts as they are produced. Additionally, materials development specifically for metals AM processes is in its infancy. Material and process parameter development for these new materials is currently an entirely empirical process which requires substantial time and expense to develop. Alternate methodologies using data analytics combined with in situ sensing techniques are sought to expedite this process in order to put new capabilities into the hands of the Soldier in shorter time frames at reduced costs. Research challenges for collaboration include:
- Sensing, data analytics, and machine learning algorithms to quantify/certify in situ part quality and machine abnormalities using forward, inverse, and feedback uncertainty quantification methodologies;
- Machine learning algorithms for expedited process parameter development for novel metallic alloy feedstocks;
- Multiscale models to simulate heterogeneous microstructure evolution and performance through the AM build process;
- Forward, inverse, and feedback uncertainty quantification methodologies throughout the AM build process to articulate final part performance confidence level.
Mr. Joseph South firstname.lastname@example.org 410-278-9077