Company
Portfolio Data
Back to Company SearchX-Wave Innovations, Inc.
UEI: EDJ3MSJR9NK7
Number of Employees: 11
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
SBIR/STTR Involvement
Year of first award: 2012
71
Phase I Awards
21
Phase II Awards
29.58%
Conversion Rate
$10,405,975
Phase I Dollars
$20,118,698
Phase II Dollars
$30,524,673
Total Awarded
Awards
High-Temperature Ultrasonic Transducer Array System for Particulate Agglomeration in Molten Salt Solutions
Amount: $206,500 Topic: C60-29cc
High-temperature molten salt solutions are a valuable medium for heat transfer and storage in advanced nuclear reactors and other high-temperature systems. However, insoluble oxides and metallic particulates can accumulate within the molten salt during synthesis, operation, and post-operation treatment, leading to performance degradation. Current filtration techniques, such as mesh or screen filtration and centrifugal separation, struggle to capture particles smaller than 5 microns. These limitations contribute to inefficiencies, increased maintenance costs, and reduced system reliability. To address the DOE’s need for improved filtration in molten salt solutions, X-wave Innovations, Inc. (XII) proposes a high-temperature ultrasonic transducer array (HTUTA) system specifically designed to agglomerate fine particles for improved collection. Ultrasonic agglomeration offers a promising solution by using acoustic waves to cluster fine particles, making them easier to capture through conventional filtration systems. The proposed HTUTA leverages high-frequency standing wave fields to apply acoustic forces that drive fine metallic and oxide particles to pressure nodes, promoting their agglomeration into collectable clusters. This innovative approach avoids ultrasonic cavitation, commonly associated with deagglomeration, by operating at carefully calibrated frequencies and power levels optimized for agglomeration In Phase I, X-Wave Innovations (XII) will design and develop a HTUTA prototype, focusing on characterizing its efficiency in agglomerating particulates and improving filtration performance. Our Phase I efforts will focus on the design and demonstration of a prototype HTUTA system, modelling the agglomeration process to finetune optimal frequency and power levels for the transducers, evaluating our system through a mock test-setup using solutions of similar characteristics to molten salt, demonstrating the effectiveness of our proposed solution through image analysis of filtering results, and modelling the agglomeration system’s effectiveness in actual high temperature molten salt applications. The proposed HTUTA system enhances filtration efficiency in molten salt solutions, improving overall system performance. While primarily designed for high-temperature applications like nuclear reactors, HTUTA is versatile and can agglomerate particles in various liquid mediums. Its key advantage lies in the ability to optimize frequency and power output based on the specific solution, making it adaptable for a wide range of filtration applications.
Tagged as:
SBIR
Phase I
2025
DOE
Ultrasonic Multipoint Waveguide Temperature Sensor for Divertor Diagnostics in Fusion Power Plants
Amount: $206,500 Topic: C59-21b
Diagnosing long pulse and steady-state operation in a Fusion Power Plant (FPP) presents significant challenges due to the extreme environment, which includes high neutron irradiation, increased heat and particle flux, thermomechanical stresses, and relativistic effects. Conventional diagnostics such as Langmuir probes, infrared imaging, and thermocouples are not suitable due to the extreme conditions, including higher heat and particle flux than those in ITER. Langmuir probes are expected to have a short lifespan due to heavy erosion, infrared imaging system windows cannot withstand neutron irradiation and thermal expansion, and thermocouples suffer from material transmutation. To address this critical need, X-wave Innovations, Inc. (XII), in collaboration with Idaho National Laboratory (INL), proposes to develop an ultrasonic multipoint waveguide temperature sensor (UMWTS) for divertor diagnostics in Fusion Power Plants. For this effort, XII and INL will leverage our experience in design and development in ultrasonic waveguide sensors and radiation-resilient magnetostrictive transducers to ensure its accuracy and long operation life to determining the strike point and x-point positions of plasma in fusion power plants. The success of the proposed effort will result in a novel sensor system for reliable monitoring of harsh conditions in core environments. Our main objective of the Phase I program is to prototype and demonstrate the feasibility of the proposed UMWTS system. Based upon XII’s experience and success in this area, our Phase I efforts will focus on the design and prototyping of the proposed ultrasonic waveguide sensor to enable efficient generation and detection of ultrasonic signals, and data interpretation/reporting of temperatures at multi-points of the waveguide with selective reflectors. By the end of Phase I, we will demonstrate the feasibility of the developed waveguide sensor system for multi-point temperature measurements. The proposed UMWTS system aims to provide accurate temperature profile measurements for the fusion power plant (FPP) divertor diagnostics and plasma control. Apart from its direct use in FPP, the proposed UMWTS system can find may applications in nuclear industry in general, as well as other commercial sectors. With all the advantages of ultrasonic thermometry, the UMWTS allows multiple temperature at different location along the length of a waveguide, and due to its design and choice of materials it can offer long term operation in nuclear and harsh conditions for extended period of time. X-wave Innovations, Inc. proposes to develop a novel ultrasonic multipoint temperature sensor that is critical for improving the fusion power plant efficiency and operation safety.
Tagged as:
SBIR
Phase I
2025
DOE
Detect3C: Advancing the Assessment of Concrete Chloride Content Through Non-Destructive Techniques
Amount: $1,499,996 Topic: 24-FH3
Chloride infiltration causes corrosion in steel reinforcements, compromising concrete structures’ integrity and longevity. Traditional assessments using invasive core sampling and laboratory testing are time-consuming, disrupt traffic, and offer limited spatial insight, hindering effective maintenance strategies. X-wave Innovations, Inc., in collaboration with the University of Nebraska-Lincoln, is developing Detect3C for rapid, non-destructive concrete chloride assessment. This technique accurately profiles chloride content, significantly reducing field work and resource demands, while providing comprehensive data across and through entire bridge deck with minimal traffic disruptions. Phase I demonstrated the feasibility of our approach and Detect3C’s effectiveness. In Phase II, we will develop a fully-functional Detect3C prototype and further validate its capability for rapid, non-invasive, comprehensive assessment of bridge deck chloride content.
Tagged as:
SBIR
Phase II
2025
DOT
Linear Array of Magnetostrictive Accelerometers (LAMA) for Distributed Acceleration Sensing on Aircraft Structures
Amount: $140,000 Topic: N242-093
X-wave Innovations, Inc. (XII) proposes a distributed acceleration sensor based on a linear array of magnetostrictive accelerometers (LAMA). A sensing element in LAMA consists of thin magnetostrictive (MS) ribbon fixed at both ends, two permanent magnets, a pickup coil and Hall sensors. The magnets fixed at the center of the ribbon serves dual purpose; magnetizing the MS ribbon and also functioning like a proof mass. Changes in the force experienced by the proof mass cause a strain in the ribbon, altering the relative permeability of the MS ribbon and the flux flowing through it. This change in flux induces a voltage in the pickup coils wrapped around the ribbon. No voltage is measured across the coil when the force is constant. Additional Hall sensors will be used to track the position of the magnets, enabling the measurement of static force. Each sensor element will include a signal amplifier and ADC ICs, and multiple sensors will be connected to form an array (LAMA) in a daisy-chain configuration for distributed sensing. In Phase I, XII will design and develop a prototype LAMA sensing element. Design phase will be aided by analytical and simulation methods. The prototype will be used to demonstrate the feasibility of the proposed technology. In Phase II, XII will refine the sensing element, develop an array of sensing elements (LAMA) and the related electronics, and demonstrate the technology to DON.
Tagged as:
SBIR
Phase I
2025
DOW
NAVY
EddyGraph: A Modular, Precision Swept Frequency Eddy Current Based Graphite Inspection System
Amount: $200,000 Topic: C60-29c
The development of advanced inspection technologies for graphite components in High Temperature Gas Reactors (HTGRs) and Molten Salt Reactors (MSRs) is crucial for improving the safety, efficiency, and longevity of next-generation nuclear reactors. Graphite components play vital roles in neutron moderation and structural support but are subject to degradation from molten salt erosion, thermal stress, and surface wear. In-situ, high-resolution nondestructive evaluation (NDE) technologies, such as visual and eddy current systems with up to 500-micron resolution, are essential to assess these components' condition under extreme conditions, ensuring the safe operation and growth of the U.S. nuclear industry. The EddyGraph system aims to address the challenge of efficiently inspecting graphite components in nuclear reactors, particularly in High Temperature Gas-cooled Reactors (HTGRs) and Molten Salt Reactors (MSRs), where traditional methods struggle with complex geometries and harsh environments. The system will consist of multiple specially designed eddy current (EC) sensors housed inside stainless-steel housing integrated into an articulating arm, enabling rapid scanning of the entire fuel channel bore. A machinelearning-based inversion model will be used for the interpretation of eddy current data measured on curved surfaces, capable of identifying and locating the presence of multiple damage mechanisms. First, a high-fidelity finite-element model of a representative HTGR graphite reflector block will be developed which will include typical damages expected in such components. Second, this model will be used to optimize the eddy current coil parameters to ensure sensitivity to typical damage types anticipated. Third, the simulated eddy current data will be used to train a machine-learning model for inversion. Fourth, the forward model along with the machine learning-based inversion model will be used to demonstrate the feasibility of the proposed technique. Fifth, a basic prototype of the proposed system will be developed to demonstrate the capability of the proposed technology on a simple curved graphite block. In phase II, a fully functional prototype with radiation-hardened hardware and related software will be developed and tested on irradiated graphite components. The results will be used to refine the prototype and inversion model. In Phase III, a commercial version of the system will be developed. The proposed technology can also be used for rapid inspection of critical graphite structures in various industries like aerospace, manufacturing, and semiconductors.
Tagged as:
SBIR
Phase I
2025
DOE
A Novel Process-Structure-Property Evaluation Package for Large Scale Electron Beam Additive Manufacturing
Amount: $986,742 Topic: N23B-T033
The U.S. Navy is interested in developing optimized wire-fed directed energy deposition (DED) electron beam additive manufacturing (EBAM) process for large-size, geometrically complex, high-criticality components for ALRE. In EBAM, its wire-based mode has natural advantage to produce dense structures, while the high vacuum forming environment can prevent the oxidation during additive manufacturing (AM) process. The EBAM process is also suitable for the fabrication of large-sized parts that cannot be fabricated by powder methods. The quality of the feed wire and machine parameters have direct effect on the finished product. Currently the research in EBAM in fabrication of alloys is still at the initial stage and lack of systematic understanding. To address this critical need, X-wave Innovations, Inc. (XII) teams up with Sciaky Inc., and Edison Welding Institute (EWI), proposes to develop a novel Process-Structure-Property Evaluation (PSPE) package for enabling the evaluation of fabrication parameters and prediction of component properties for large scale EBAM components. The PSPE approach is built upon Sciaky and EWI’s advanced EBAM fabrication know-how, which includes machine parameter adjustment techniques for high-complexity structures. Additionally, XII contributes its advanced machine learning-based process-structure-property (PSP) model for metal AM parts. In the Phase I program, we successfully prototyped the PSPE package and demonstrated the feasibility of our proposed technology. In Phase II, we will complete PSPE prototype development by modifying and fine-tuning the prototype models and algorithms, and utilizing this technology for correlate the EBAM process parameters to mechanical properties, and provide a digital twin model for EBAM process. At the end of Phase II program, the PSPE package is expected to be ready for transitioning into production applications.
Tagged as:
SBIR
Phase II
2025
DOW
NAVY
Machine Learning-Based Laser Powder Bed Fusion In-Situ Monitoring Package
Amount: $100,000 Topic: 6
Additive Manufacturing (AM) is a modern and increasingly popular manufacturing process for metallic components, but it suffers from well-known problems of inconsistent quality of the finished product. As such, develop an in-situ monitoring technology for metal AM components is critically important. The developed technology must be able to perform real-time monitoring, and close-loop machine feedback, and enable the commercial machine integration. To address this critical need, X-wave Innovations, Inc. (XII) and Johns Hopkins University Applied Physics Laboratory (JHU/APL) propose to develop an advance machine learning-based in-situ monitoring (ML-ISM) package for powder bed fusion processes. This technology provides a real-time laser powder bed fusion (LPBF) process monitoring and machine learning solution to produce high-quality metallic end products. The technology development involved in-situ monitoring and advanced machine learning correlation algorithms. Upon completion, this technology is expected to be applicable to powder bed fusion AM processes for improved productivity and reduced rejected components due to inferior quality. In Phase I program, XII will demonstrate the feasibility of the machine learning-based in-situ monitoring package. In Phase II program, we will integrate the ML-ISM suite into commercial LPBF system, and accompanying software tools for operation of the ML-ISM system.
Tagged as:
SBIR
Phase I
2025
DOC
NIST
A Low-Cost, Handheld Ultrasonic Pressure Sensor for Non-Invasive, Rapid, and Accurate Measurement of Helium Pressure in Composite Overwrapped Pressure Vessels of Airborne Fuel Flow
Amount: $2,010,000 Topic: MDA242-D009
To address the need of Missile Defense Agency (MDA) Terminal High Altitude Area Defense (THAAD) Missile Product Office’s (THR) for an accurate, non-invasive, and non-destructive means of measuring the helium pressure within the Composite Overwrapped Pressure Vessel (COPV) upon Divert and Attitude Control System (DACS) installation and whenever missile rounds (MRs) are returned for Stockpile Reliability Testing (SRT), X-wave Innovations, Inc. (XII) with support from Lockheed Martin Corp. (LMC) proposes to develop a low-cost, handheld ultrasonic pressure sensor. The proposed solution is based on XII-developed ultrasonic sensor technologies for non-invasive measurements of helium pressure in spent nuclear fuel dry-storage canisters and large flow rate measurements of hydrogen gas in a pipeline. As part of the Phase I-like effort, we demonstrated the feasibility of the proposed ultrasonic sensor technology for non-invasive measurements of helium pressure inside a metallic canister and the use of artificial intelligence or machine learning (AI/ML) to significantly increase the accuracy of ultrasonic flow rate measurements. In the Phase II program, we will first refine the ultrasonic sensor design and assemble an integrated ultrasonic sensor head for testing. We will then implement a machine learning algorithm for data analysis. Subsequently, we will miniaturize and package the readout electronics and display into a handheld device. Finally, we will conduct verification and validation testing and commercialize the developed product. Approved for Public Release | 25-MDA-12052 (27 Mar 25)
Tagged as:
SBIR
Phase II
2025
DOW
MDA
An Adjacent Inductive Coil Sensor (AICS) System for Structural Health Monitoring of the Restraint Layer
Amount: $850,000 Topic: H5
For long-duration missions, one of the primary concerns is the potential for structural material failure of the inflatable softgoods restraint layer due to creep. Creep is a phenomenon where deformation occurs under sustained loading. Structural health monitoring (SHM) of the restraint layer in inflatable systems is essential to ensure the safety of crew members and the continued operation of NASA missions. To address this issue, there is a need to develop a new SHM approach to accurately and actively measure creep of the restraint layer. The current methods include adhesive foil strain gages, fiber optics, accelerometers, and acoustic sensors which all have their potential drawbacks and require extensive wiring which must survive deployment. To address this critical need, X-wave Innovations, Inc. (X-wave) proposes to develop an Adjacent Inductive Coil Sensor (AICS) system to monitor the creep of the restraint layer in multilayer systems. The proposed AICS system improves upon the current state of the art sensors by not requiring any electrical cabling or wiring to the restraint layer. The proposed sensor system is also advantageous over other types of SHM sensors such as fiber optics or other flexible materials in that the proposed sensor does not need to withstand significant elongation during deployment or while in operation. The AICS system will use non-contact interrogation of the restraint layer from the interior of the inflatable softgoods structure, therefore interference from the thin metallic depositions of the outer layer will have no effect on the performance of the sensor system. The AICS system will include a prognostication algorithm that will predict the creep behavior of the restraint layer and notify the crew members of any anticipated failures.
Tagged as:
SBIR
Phase II
2025
NASA
A Novel Machine Learning Based Additive Manufacturing Printability Assessment Software Package
Amount: $146,497 Topic: N23B-T032
The U.S. Navy is interested in developing an artificial intelligence tool to analyze technical data and assess the suitability of components for additive manufacturing (AM). This technology should be able to provide a binary printability assessment of a part based on its technical data, and provide a ōCan Print/ Should Printö analysis for a higher yield of impactful AM candidates. The technology package should also include printability evaluation labels for parts based on design, material, fabrication cost, and other technical data. To address this critical need, X-wave Innovations, Inc. (XII) is partnering with Lockheed Martin Inc. and Pennsylvania State University to propose the development of a novel machine learning-based AM printability (ML-AMP) assessment software package for rapidly evaluate printability on large technical datasets, and provide decision recommendations based on the ōCan Print/ Should Printö analysis. The ML-AMP technology will employ both unsupervised and supervised machine learning algorithms to assess AM printability. Upon completion, the ML-AMP technology is expected to be applicable for intelligent, rapid and efficient printability assessment of both 3D and 2D technical data. We will work closely with our partners to actively transition and commercialize this technology for Navy engineering analysis applications and industry software applications.
Tagged as:
STTR
Phase I
2024
DOW
NAVY