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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,765 records · Page 98
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Robotically Assisted Sonic Therapy (RAST) for Noninvasive Hepatic Ablation in a Porcine Model: Mitigation of Body Wall Damage with a Modified Pulse Sequence

Purpose: Robotically assisted sonic therapy (RAST) is a nonthermal, noninvasive ablation method based on histotripsy. Prior animal studies have demonstrated the ability to create hepatic ablation zones at the focal point of an ultrasound therapy transducer; however, these treatments resulted in thermal damage to the body wall within the path of ultrasound energy delivery. The purpose of this study was to evaluate the efficacy and safety of a pulse sequence intended to mitigate prefocal body wall injury. Materials and Methods: Healthy swine (n = 6) underwent hepatic RAST (VortxRx software version 1.0.1.3, HistoSonics, Ann Arbor MI) in the right hepatic lobe. A 3.0 cm spherical ablation zone was prescribed for each. Following treatment, animals underwent MRI which was utilized for ablation zone measurement, evaluation of prefocal injury, and assessment of complications. Each animal was euthanized, underwent necropsy, and the tissue was processed for histopathologic analysis of the ablation zone and any other sites concerning for injury. Results: No prefocal injury was identified by MRI or necropsy in the body wall or tissues overlying the liver. Ablation zones demonstrated uniform cell destruction, were nearly spherical (sphericity index = 0.988), and corresponded closely to the prescribed size (3.0 × 3.1 × 3.4 cm, p = 0.70, 0.36, and 0.01, respectively). Ablation zones were associated with portal vein (n = 3, one occlusive) and hepatic vein thrombosis (n = 4, one occlusive); however, bile ducts remained patent within ablation zones (n = 2). Conclusions: Hepatic RAST performed with a modified ultrasound pulse sequence in a porcine model can mitigate prefocal body wall injuries while maintaining treatment efficacy. Further study of hepatic RAST appears warranted, particularly in tumor models.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

Cost-Effectiveness Analysis of Chemoradiation Therapy Versus Transoral Robotic Surgery for Human Papillomavirus–Associated, Clinical N2 Oropharyngeal Cancer

Purpose: To perform a cost-effectiveness analysis of primary chemoradiation therapy (CRT) versus transoral robotic surgery (TORS) for clinical N2, human papillomavirus (HPV)-positive oropharyngeal carcinoma. Methods and Materials: We developed a Markov model to describe the health states after treatment with CRT or TORS, followed by adjuvant radiation therapy or CRT in the presence of high-risk pathology (positive margins or extracapsular extension). Outcomes, toxicities, and costs were extracted from the literature. One-way sensitivity analyses (SA) were performed over a wide range of parameters, as were 2-way SA between the key variables. Probabilistic SA and value of information studies were performed over key parameters. Results: The expected quality-adjusted life years (QALYs)/total costs for CRT and TORS were 7.31/$50,100 and 7.29/$62,200, respectively, so that CRT dominated TORS. In SA, primary CRT was almost always cost-effective up to a societal willingness-to-pay of $200,000/QALY, unless the locoregional recurrence risk after TORS was 30% to 50% lower, at which point it became cost effective at a willingness-to-pay of $50-100,000/QALY. Probabilistic SA confirmed the importance of locoregional recurrence risk, and the value of information in precisely knowing this parameter was more than $7M per year. If the long-term utility after TORS was 0.03 lower than CRT, CRT was cost-effective over nearly any assumption. Conclusions: Under nearly all assumptions, primary CRT was the cost-effective therapy for HPV-associated, clinical N2 OPC. However, in the hypothetical event of a large relative improvement in LRR with surgery and equivalent long-term utilities, primary TORS would become the higher-value treatment, arguing for prospective, comparative study of the 2 paradigms.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2025

Automated Nanocrystal Synthesis: Lessons from 25 Years of Robots, Microfluidics, and Machine Learning

Here, this perspective highlights the evolution of techniques for automating the synthesis of colloidal nanocrystals. Over the past 25 years, microfluidic reactors and robotic workflows have been developed to enhance the reproducibility of nanocrystal synthesis, facilitate rapid screening of reaction conditions, optimize material properties, and perform multistep syntheses of high-quality nanoparticles with complex heterostructures. Modern automated systems are now valued for their ability to generate robust data sets for validating physical models, supporting chemical mechanisms, training machine learning models, and for directing autonomous experimentation. We discuss the early challenges and limitations of these technologies and present key lessons for effectively utilizing automated and ML-guided tools to accelerate nanocrystal discovery for the next 25 years.

Nanocrystals↗
DOE OSTI2026

A Robotic High-Throughput Grid-Search Platform for Mapping Phase Behavior in Triblock Copolymer–Homopolymer Blends

We present a high-throughput experimental investigation of the phase behavior in triblock copolymers (PS-b-PB-b-PS and PS-b-PI-b-PS) and polystyrene (PS) homopolymer blends as a function of homopolymer molecular weight (MW) and blend ratio. Using a robotic thin-film processing platform (NOVA) integrated with Grazing Incidence Small-Angle X-ray Scattering (GISAXS) and Atomic Force Microscopy (AFM), we systematically mapped the order–disorder transition (ODT) boundaries and domain spacing evolution across a broad MW range (4.0–101.3 kDa) with varying homopolymer loadings (10% to 90%). The results reveal three distinct regimes: low-MW homopolymers, corresponding to the wet-brush regime produced only gradual domain swelling before disordering at high blend ratios (weight fraction); medium-MW homopolymers, corresponding to thedry-brush regime induced significant domain spacing increase up to 80% followed by earlier disordering, while high-MW homopolymers led to macrophase separation with minimal changes in domain spacing. Additionally, coarse-grained molecular dynamics simulations confirmed our experimental finding that in the low-MW region, the PS homopolymer uniformly distributed in the PS domain. These findings demonstrate that homopolymer molecular weight critically governs both the extent of domain swelling and the onset of disorder in triblock copolymer systems. This high-throughput platform enables the rapid mapping of composition–morphology relationships and can be integrated with AI/ML tools for designing next-generation nanostructured polymers.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Robotic pendant drop: containerless liquid for μs-resolved, AI-executable XPCS

Abstract The dynamics and structure of mixed phases in a complex fluid can significantly impact its material properties, such as viscoelasticity. Small-angle X-ray Photon Correlation Spectroscopy (SA-XPCS) can probe the spontaneous spatial fluctuations of the mixed phases under various in situ environments over wide spatiotemporal ranges (10 −6 –10 3 s /10 −10 –10 −6 m). Tailored material design, however, requires searching through a massive number of sample compositions and experimental parameters, which is beyond the bandwidth of the current coherent X-ray beamline. Using 3.7-μs-resolved XPCS synchronized with the clock frequency at the Advanced Photon Source, we demonstrated the consistency between the Brownian dynamics of ~100 nm diameter colloidal silica nanoparticles measured from an enclosed pendant drop and a sealed capillary. The electronic pipette can also be mounted on a robotic arm to access different stock solutions and create complex fluids with highly-repeatable and precisely controlled composition profiles. This closed-loop, AI-executable protocol is applicable to light scattering techniques regardless of the light wavelength and optical coherence, and is a first step towards high-throughput, autonomous material discovery.

36 MATERIALS SCIENCE↗
DOE OSTI2018

High-throughput discovery of organic cages and catenanes using computational screening fused with robotic synthesis

Supramolecular synthesis is a powerful strategy for assembling complex molecules, but to do this by targeted design is challenging. This is because multicomponent assembly reactions have the potential to form a wide variety of products. High-throughput screening can explore a broad synthetic space, but this is inefficient and inelegant when applied blindly. Here we fuse computation with robotic synthesis to create a hybrid discovery workflow for discovering new organic cage molecules, and by extension, other supramolecular systems. A total of 78 precursor combinations were investigated by computation and experiment, leading to 33 cages that were formed cleanly in one-pot syntheses. Comparison of calculations with experimental outcomes across this broad library shows that computation has the power to focus experiments, for example by identifying linkers that are less likely to be reliable for cage formation. Screening also led to the unplanned discovery of a new cage topology—doubly bridged, triply interlocked cage catenanes.

Science & Technology - Other Topics↗
DOE OSTI2024

An integrated high-throughput robotic platform and active learning approach for accelerated discovery of optimal electrolyte formulations

Solubility of redox-active molecules is an important determining factor of the energy density in redox flow batteries. However, the advancement of electrolyte materials discovery has been constrained by the absence of extensive experimental solubility datasets, which are crucial for leveraging data-driven methodologies. In this study, we design and investigate a highly automated workflow that synergizes a high-throughput experimentation platform with a state-of-the-art active learning algorithm to significantly enhance the solubility of redox-active molecules in organic solvents. Our platform identifies multiple solvents that achieve a remarkable solubility threshold exceeding 6.20 M for the archetype redox-active molecule, 2,1,3-benzothiadiazole, from a comprehensive library of more than 2000 potential solvents. Significantly, our integrated strategy necessitates solubility assessments for fewer than 10% of these candidates, underscoring the efficiency of our approach. Our results also show that binary solvent mixtures, particularly those incorporating 1,4-dioxane, are instrumental in boosting the solubility of 2,1,3-benzothiadiazole. Beyond designing an efficient workflow for developing high-performance redox flow batteries, our machine learning-guided high-throughput robotic platform presents a robust and general approach for expedited discovery of functional materials.

25 ENERGY STORAGE↗
DOE OSTI2026

High-throughput methods leveraging robotics and computer vision for the development of therapeutic phage cocktails

We present the high-throughput automated screening techniques that are being used to develop bacteriophage-based therapeutic products currently under investigation in human clinical trials to combat urinary tract infections. By integrating modern liquid handling robotics, standardized phenotypic assays, and computer vision-based enumeration, we established a platform capable of reproducibly screening large collections of phages against clinically derived bacterial strain panels. This approach enabled systematic assessment of phage-bacteria interactions at scale, facilitating the identification and optimization of phage cocktails with broad in vitro activity. Although bacteriophage therapy has long been investigated as a strategy for treating bacterial infections, few frameworks exist for developing phage combinations in a reproducible and scalable manner. The methods outlined here address this gap and aim to support the broader development of therapeutic assets available to combat antibiotic resistance.

Penke, Taylor J. R. [Locus Biosciences, Morrisvill↗
DOE OSTI2024

Enabling high-throughput enzyme discovery and engineering with a low-cost, robot-assisted pipeline

Abstract As genomic databases expand and artificial intelligence tools advance, there is a growing demand for efficient characterization of large numbers of proteins. To this end, here we describe a generalizable pipeline for high-throughput protein purification using small-scale expression in E. coli and an affordable liquid-handling robot. This low-cost platform enables the purification of 96 proteins in parallel with minimal waste and is scalable for processing hundreds of proteins weekly per user. We demonstrate the performance of this method with the expression and purification of the leading poly(ethylene terephthalate) hydrolases reported in the literature. Replicate experiments demonstrated reproducibility and enzyme purity and yields (up to 400 µg) sufficient for comprehensive analyses of both thermostability and activity, generating a standardized benchmark dataset for comparing these plastic-degrading enzymes. The cost-effectiveness and ease of implementation of this platform render it broadly applicable to diverse protein characterization challenges in the biological sciences.

36 MATERIALS SCIENCE↗
DOE OSTI2018

A mathematical model to systematically align superconducting radio frequency cavities employing the serial robot kinematic theory

In Superconducting Radio Frequency (SRF) cryomodules, precise alignment of cavities is necessary to ensure high beam quality and to increase the overall energetic efficiency. In the SSR1 (Single Spoke Resonator 1) cryomodule, the cavities are aligned using a system of seven screws which allows to control five Degree of Freedoms (DOFs). The relation between the rotation of each screw and the movement of the cavity is non-linear, thus the aligning process, currently based on a trial-and-error procedure, can be time consuming and affected by human error. In this paper the design of an alignment mathematical model, based on the serial robot kinematic, is described and tested on a SSR1 cavity. Furthermore, the goal of the proposed model is to give a step by step operational procedure that bring the SSR1 cavity to a desired location reducing the uncertainties related to the current operator-driven alignment process.

43 PARTICLE ACCELERATORS↗
DOE OSTI2016

Robotic path-finding in inverse treatment planning for stereotactic radiosurgery with continuous dose delivery

Purpose: Continuous dose delivery in radiation therapy treatments has been shown to decrease total treatment time while improving the dose conformity and distribution homogeneity over the conventional step-and-shoot approach. The authors develop an inverse treatment planning method for Gamma Knife® Perfexion™ that continuously delivers dose along a path in the target. Methods: The authors’ method is comprised of two steps: find a path within the target, then solve a mixed integer optimization model to find the optimal collimator configurations and durations along the selected path. Robotic path-finding techniques, specifically, simultaneous localization and mapping (SLAM) using an extended Kalman filter, are used to obtain a path that travels sufficiently close to selected isocentre locations. SLAM is novelly extended to explore a 3D, discrete environment, which is the target discretized into voxels. Further novel extensions are incorporated into the steering mechanism to account for target geometry. Results: The SLAM method was tested on seven clinical cases and compared to clinical, Hamiltonian path continuous delivery, and inverse step-and-shoot treatment plans. The SLAM approach improved dose metrics compared to the clinical plans and Hamiltonian path continuous delivery plans. Beam-on times improved over clinical plans, and had mixed performance compared to Hamiltonian path continuous plans. The SLAM method is also shown to be robust to path selection inaccuracies, isocentre selection, and dose distribution. Conclusions: The SLAM method for continuous delivery provides decreased total treatment time and increased treatment quality compared to both clinical and inverse step-and-shoot plans, and outperforms existing path methods in treatment quality. It also accounts for uncertainty in treatment planning by accommodating inaccuracies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

WE-DE-BRA-11: A Study of Motion Tracking Accuracy of Robotic Radiosurgery Using a Novel CCD Camera Based End-To-End Test System

Purpose: A novel end-to-end test system using a CCD camera and a scintillator based phantom (XRV-124, Logos Systems Int’l) capable of measuring the beam-by-beam delivery accuracy of Robotic Radiosurgery (CyberKnife) was developed and reported in our previous work. This work investigates its application in assessing the motion tracking (Synchrony) accuracy for CyberKnife. Methods: A QA plan with Anterior and Lateral beams (with 4 different collimator sizes) was created (Multiplan v5.3) for the XRV-124 phantom. The phantom was placed on a motion platform (superior and inferior movement), and the plans were delivered on the CyberKnife M6 system using four motion patterns: static, Sine- wave, Sine with 15° phase shift, and a patient breathing pattern composed of 2cm maximum motion with 4 second breathing cycle. Under integral recording mode, the time-averaged beam vectors (X, Y, Z) were measured by the phantom and compared with static delivery. In dynamic recording mode, the beam spots were recorded at a rate of 10 frames/second. The beam vector deviation from average position was evaluated against the various breathing patterns. Results: The average beam position of the six deliveries with no motion and three deliveries with Synchrony tracking on ideal motion (sinewave without phase shift) all agree within −0.03±0.00 mm, 0.10±0.04, and 0.04±0.03 in the X, Y, and X directions. Radiation beam width (FWHM) variations are within ±0.03 mm. Dynamic video record showed submillimeter tracking stability for both regular and irregular breathing pattern; however the tracking error up to 3.5 mm was observed when a 15 degree phase shift was introduced. Conclusion: The XRV-124 system is able to provide 3D and 4D targeting accuracy for CyberKnife delivery with Synchrony. The experimental results showed sub-millimeter delivery in phantom with excellent correlation in target to breathing motion. The accuracy was degraded when irregular motion and phase shift was introduced.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

nanoPOTS robot

In conjunction with other nanoPOTS related IP, we are disclosing the robotic platform including specific parts used to construct the nanopipetting instrument.

Zhu, Ying↗
DOE OSTI2026

Robot-Alignment

Fermilab's SRF Robotics group's automated alignment program. FERMILAB-CODE-2026-03-TD

Giffen, Nickolas [Northern Illinois Univ., DeKalb,↗
DOE OSTI2021

Adapting a Low-Cost and Open-Source Commercial Pipetting Robot for Nanoliter Liquid Handling

Nanoliter liquid handling capabilities in bioanalytical workflows can reduce reagent costs and improve sample processing efficiency. Here we report the successful modification of a low-cost commercially available pipetting robot, the Opentrons 1 (OT1), using inexpensive 3D-printed parts to accommodate low-nanoliter volumes. The pipetting accuracy and precision of the modified OT1 for 50 nL volumes of water was 0.2% and 2%, respectively. The accuracy and precision at 20 nL was 1% and 3.8%, respectively. The platform was successfully applied to the preparation of low-nanogram proteomic samples for liquid chromatography-mass spectrometry analysis. The modified OT1 is thus an effective platform for nanoliter liquid handling and, at a total cost of less than $6000 including the commercial liquid handler and all modifications, is far less expensive and more versatile than other platforms with similar capabilities, placing this technology within reach of a far broader scientific community.

47 OTHER INSTRUMENTATION↗
DOE OSTI2018

Robot deployable air sampling development suite

Many areas exist within the DOE EM complex where it is desired to obtain a better understanding of the environment through the use of sensors. Many of these areas are hazardous and/or inaccessible to humans requiring the development of capabilities and technologies to remotely access these areas for monitoring. Often it is desired to understand the air quality and basic environmental parameters of these inaccessible areas. The focus this LDRD was to identify and procure air and environmental sampling sensors of common interest to DOE facilities such as pH, Nitric Acid Concentration (NOx), humidity, temperature, and air velocity. Additionally, it was desired to procure a robotic platform as a basis developing a remotely deployable air sampling suite.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Development of a Visualization Concept for Robotic Operations to Consolidate Commercial Spent Nuclear Fuel

Sandia and NAC are advancing a new conceptual initiative associated with integrating the back end of the nuclear fuel cycle. Sandia has robust capability in robotics and spent fuel disposal science and engineering. NAC has demonstrated rod consolidation packaging technology that potentially enables more efficient nuclear fuel cycle back end integration. NAC also has a robust capability in spent fuel packaging.

Freeze, Geoffrey↗