SEARCH · Engineering Papers

Results for “High precision control”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 271 records · Page 15

All sources NASA NTRS DOE OSTI

DOE OSTI2020

Toward fusion plasma scenario planning for NSTX-U using machine-learning-accelerated models

One of the most promising devices for realizing power production through nuclear fusion is the tokamak. To maximize performance, it is preferable that tokamak reactors achieve advanced operating scenarios characterized by good plasma confinement, improved magnetohydrodynamic (MHD) stability, and a largely non-inductively driven plasma current. Such scenarios could enable steady-state reactor operation with high \emph{fusion gain} --- the ratio of produced fusion power to the external power provided through the plasma boundary. Precise and robust control of the evolution of the plasma boundary shape as well as the spatial distribution of the plasma current, density, temperature, and rotation will be essential to achieving and maintaining such scenarios. The complexity of the evolution of tokamak plasmas, arising due to nonlinearities and coupling between various parameters, motivates the use of model-based control algorithms that can account for the system dynamics. In this work, a learning-based accelerated model trained on data from the National Spherical Torus Experiment Upgrade (NSTX-U) is employed to develop planning and control strategies for regulating the density and temperature profile evolution around desired trajectories. The proposed model combines empirical scaling laws developed across multiple devices with neural networks trained on empirical data from NSTX-U and a database of first-principles-based computationally intensive simulations. The reduced execution time of the accelerated model will enable practical application of optimization algorithms and reinforcement learning approaches for scenario planning and control development. An initial demonstration of applying optimization approaches to the learning-based model is presented, including a strategy for mitigating the effect of leaving the finite validity range of the accelerated model. The approach shows promise for actuator planning between experiments and in real-time.

machine learning↗

DOE OSTI2022

High-Precision Mapping of Diamond Crystal Strain Using Quantum Interferometry

Crystal-strain variation imposes significant limitations on many quantum sensing and information applications for solid-state defect qubits in diamond. Thus, the precision measurement and control of diamond crystal strain is a key challenge. Here, we report diamond strain measurements with a unique set of capabilities, including micron-scale spatial resolution, a millimeter-scale field of view, and a 2-order-of-magnitude improvement in volume-normalized sensitivity over previous work, reaching 5(2)×10 -8 /√Hzμm -3 (with spin-strain coupling coefficients representing the dominant systematic uncertainty). We use strain-sensitive spin-state interferometry on ensembles of nitrogen-vacancy (N-V) color centers in single-crystal bulk diamond with low strain gradients. This quantum interferometry technique provides insensitivity to magnetic-field inhomogeneity from the electronic and nuclear spin bath, thereby enabling long N-V–ensemble electronic spin dephasing times and enhanced strain sensitivity, as well as broadening the potential applications of the technique beyond isotopically enriched or high-purity diamond. We demonstrate the strain-sensitive measurement protocol first on a confocal scanning laser microscope, providing quantitative measurement of sensitivity as well as three-dimensional strain mapping; and second on a wide-field-imaging quantum diamond microscope. Our strain-microscopy technique enables fast, sensitive characterization for diamond material engineering and nanofabrication; as well as diamond-based sensing of strains applied externally, as in diamond anvil cells or embedded diamond stress sensors, or internally, as by crystal damage due to particle-induced nuclear recoils.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2020

Ambient Ion Trapping and Separations for High Throughput Structurally Selective Material Deposition

While ion mobility coupled to mass spectrometry (IMS/MS) has been increasingly adapted to biological analysis, the structural and molecular specificity offered by IMS/MS has untapped potential for creating novel materials (for energy, catalysis, biomolecular switches etc.) with rationally tailored properties by precisely controlling the chemical structure and composition of these materials. While electrochemical and catalytic properties of the bulk material are understood by mass-selective ion-soft-landing, different structures of one molecule can exhibit distinct properties from the bulk. Many biological phenomenon occur at interfaces and are highly structurally specific. IMS/MS offers means to separate molecules in a sample (which is first ionized and released to gas phase from the condensed phase) based on mass and structure. Species thus separated can potentially be deposited onto surfaces with molecular and structural specificity, to perform fundamental investigations for understanding critical interfacial phenomenon. Key performance metrics for IMS/MS analysis are resolution of separations and sensitivity. Recently developed Structures for Lossless Ion Manipulations (SLIM)4 enabled unprecedented resolution in IMS separations. In addition, high sensitivity was enabled in SLIM due to lossless confinement of ions using radio frequency fields. Thus, SLIM enabled extremely long path length separations (up to 0.1 km thus far) providing efficient separation of molecular ions never before achieved (e.g. isotopologues, D&L amino acids). While SLIM has unprecedented analytical separations power/utility, the use of SLIM platform for depositing mobility and mass selected molecular ions has two specific technological challenges: (a) Pulsed nature of IMS separations and their low duty cycle and (b) the need for a low vacuum of ~4 torr for lossless ion confinement. These limitations lead to long deposition times due to loss of ions generated from the sample. Enabling ion confinement at atmospheric pressure will be path-breaking contribution to the fundamental understanding of ion manipulations and separations and will also enable novel science currently precluded due to the inability of the present technologies to confine ions under ambient conditions. Traditionally used radio frequency fields are ineffective in confining ions at high pressures due to ion/neutral collisions. To address these, we propose to (a) develop methods for confining and manipulating ions for lossless IMS separations at atmospheric pressure enabling high sensitivity and throughput and (b) use the high specificity of IMS/MS and high throughput from ambient ion confinement to perform mobility and mass selective ion deposition at atmospheric pressure. Our goal is to enable the study of the fundamental properties of energy/catalysis materials and biomolecules. This project paves the way for high-throughput, mass and structure selective material deposition for highly specific surface creation/functionalization (discussed in Section 2 of the report). Further, the developments reported continue to push the boundaries of this process to ambient conditions (discussed in Section 3 of the report). We conclude with a list of specific intellectual property and publications which have been the outcome of this funded project.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Data-Enabled Fusion Technology (Final Scientific/Technical Report)

Advancing Scientific Understanding in Fusion Energy and Machine Learning This research represented a significant step forward in machine learning (ML) applications for fusion energy experiments. The project integrated advanced data-driven modeling, optimization techniques, and artificial intelligence to enhance the predictive capabilities and operational efficiency of plasma-based fusion systems. Specifically, tasks focused on ML-enhanced diagnostics, operator guidance tools, and predictive modeling helped improve the ability to interpret complex fusion experiments. Key areas of advancement included: 1) data-driven plasma control, i.e., using ML algorithms to optimize experimental conditions and classify plasma behaviors based on historical data; 2) spectroscopy and diagnostics, i.e., applying AI models to extract previously inaccessible insights from experimental spectroscopy data; and 3) configuration mapping and operator guidance, i.e., developing a predictive framework to assist scientists in identifying the most effective experimental parameters, reducing reliance on manual adjustments. By refining these ML-driven techniques, the project contributed to the broader scientific community’s understanding of plasma dynamics and fusion energy viability. Technical Effectiveness and Economic Feasibility The methods investigated demonstrated high technical effectiveness, as reflected in milestones assessing the predictive accuracy, performance, and optimization of fusion configurations. The development of an Operator Guidance Tool (OGT), for example, led to more precise control of plasma conditions by learning from experimental data and offering real-time adjustments. From an economic standpoint, DeFT provided: 1) the ability to reduce trial-and-error experimentation, which lowered operational costs; 2) improved data interpretation methods, which enabled more efficient resource allocation in large-scale fusion research projects; and 3) the automation of key diagnostic tasks, which reduced manual labor and human error, increasing overall efficiency. 13 The final assessments of predictive models and optimization strategies demonstrated that these approaches were scalable and could be implemented across multiple fusion energy research programs. Public Benefit and Societal Impact This project contributed directly to the broader goal of achieving sustainable and commercially viable fusion energy, which had profound implications for clean energy production and climate change mitigation. The integration of AI-driven solutions into fusion research: 1) sped up scientific discovery, accelerating progress towards achieving energy breakthroughs; 2) reduced the cost of experimentation, making fusion research more accessible; and 3) provided a framework for future AI applications in high-energy physics, benefiting adjacent fields like space exploration, material science, and renewable energy. Additionally, by fostering collaborations between AI researchers and plasma physicists, this project promoted interdisciplinary innovation that could lead to broader applications beyond fusion research.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2020

High-performance and cost-effective membrane electrode assemblies for advanced proton exchange membrane water electrolyzers: Long-term durability assessment

In this work, improved activity and durability performance of a two-cell (86 cm 2 ) proton exchange membrane water electrolyzer (PEMWE) stack is reported for the first time. Both membrane electrode assemblies (MEAs) contain one order of magnitude lower platinum group metal (PGM) loadings compared to the state-of-the-art PEMWEs and incorporate novel Pt recombination layers. The high-performance and cost-effective MEAs are fabricated by the unique reactive spray deposition technology (RSDT). This advanced methodology allows for one-step fabrication of MEAs and ensures precise control and distribution of the catalyst composition and loading. The RSDT-fabricated MEAs contain only 0.2 and 0.3 mg PGM cm –2 loading in the cathode and anode electrodes, respectively, and demonstrate excellent activity and durability for over 3000 h of operation at industrially-relevant operating conditions without showing significant loss in performance. This novel work shows that a significant cost reduction for PEMWEs is achieved while maintaining excellent durability, high catalysts activities, and low hydrogen cross-over.

Proton exchange membrane water electrolyzer↗

DOE OSTI2025

Tuning the Conformations of an M4L4 Cage and Their Impact on Catalysis

Enzymes catalyze chemical reactions with remarkable rate enhancements and selectivity. Supramolecular catalysis seeks to understand and emulate these outcomes, leveraging noncovalent interactions, electric fields, and controlled active site microenvironments to enhance catalysis in an enzyme-like fashion. The effects of conformational dynamics on supramolecular catalysts and assemblies are, however, relatively unexplored, despite their crucial role in enzyme rate enhancement. Here, we elucidate the conformational landscape of a model M4L4 supramolecular host through a rational approach: stabilizing a high-energy conformer through distal ligand modification and a transient intermediate state through symmetry-matched guest encapsulation, as well as tuning the conformer distribution through same-charge metal exchange at the host vertices. Each of these structural modifications induces a substantial shift in the host's conformational landscape, offering insights into the rational design of conformationally dynamic cages and enzymes. Although the thermodynamic properties of the dynamic Ga4L412- cage can be influenced by temperature, solvent, and guest binding, we find that conformational change occurs on a time scale that renders it rate-limiting in a model catalytic reaction, precluding rate enhancement through conformational selection. This concept is illustrated by locking the catalytically inactive conformer to a high-energy conformer that is catalytically competent. These findings demonstrate that precise modulation of the conformational landscape of supramolecular hosts provides an effective strategy for controlling their catalytic activity and binding.

Catalysis↗

DOE OSTI2023

Growth of Nanometer-Thick γ-InSe on Si(111) 7 × 7 by Molecular Beam Epitaxy for Field-Effect Transistors and Optoelectronic Devices

γ-InSe is a semiconductor that holds promising potential in high-performance field-effect transistors and optoelectronic devices. Large-scale, single-phase γ-InSe deposition has proven challenging because of the difficulty in precise control of stoichiometry and the coexistence of different indium selenide phases. In this study, we demonstrate the wafer-scale combinatorial approach to map out the growth window as functions of the Se/In ratio and growth temperature for γ-InSe on the Si(111) 7 × 7 substrate in molecular beam epitaxy. X-ray diffraction (XRD) was used to identify the indium selenide phases, while atomic force microscopy revealed four distinct surface morphologies of γ-InSe, enabling a discussion of the growth mechanisms associated with each morphology. Cross-sectional atomic resolution scanning transmission electron microscopy confirmed that the film was of high crystalline quality and had nearly single-phase γ-InSe. In conclusion, our comprehensive study elucidates the In–Se phase map for thin film growth parameters, providing invaluable landmarks for the reproducible synthesis of high-quality γ-InSe layers.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Electrically Reconfigurable Liquid Metal Nanophotonic Platform for Color Display and Imaging

Dynamically tunable optical materials and device architectures are essential for future photonic technologies, yet conventional solid metals lack the intrinsic tunability required for advanced functionalities. Gallium-based liquid metals (LMs) present an appealing alternative thanks to their distinctive mechanical and optical properties; however, their practical integration in tunable photonic elements remains largely unexplored. Here, in this study, an electrochemically controlled nanophotonic platform is demonstrated that integrates a dynamically reconfigurable LM ground plane with gold nanoantenna arrays within a microfluidic system, enabling precise and reversible modulation of optical resonances across the visible to mid-infrared spectral ranges. By employing moderate operational voltages (1.5–3.0 V), real-time tuning of high-resolution structural color patterns is achieved through nanoscale control of the interfacial gap between the LM and Au nanoantennas. This innovative platform facilitates electrically programmable, high-contrast color patterns suitable for dynamic optical displays, secure anti-counterfeiting labels, and imaging applications. Additionally, this platform enables tunable mid-infrared spectral responses, which may be utilized for chemical and biological sensing applications. This versatile integrated LM-based nanophotonic platform opens new paths toward multifunctional, actively tunable/reconfigurable photonic device and system technologies.

Imaging↗

DOE OSTI2025

Gain characterization of LGAD sensors with beta particles and 28-MeV protons

Low Gain Avalanche Diodes, also known as LGADs, are widely considered for fast-timing applications in high energy physics, nuclear physics, space science, medical imaging, and precision measurements of rare processes. Such devices are silicon-based and feature an intrinsic gain due to a p + -doped layer that allows the production of a controlled avalanche of carriers, with multiplication on the order of 10–100. This technology can provide time resolution on the order of 20–30 ps, and variants of this technology can provide precision tracking too. The characterization of LGAD performance has so far primarily been focused on the interaction of minimum ionizing particles for high energy and nuclear physics applications. This article expands the study of LGAD performance to highly-ionizing particles, such as 28-MeV protons, which are relevant for several future scientific applications, e.g. in biology and medical physics, among others. These studies were performed with a beam of 28-MeV protons from a tandem Van de Graaff accelerator at Brookhaven National Laboratory and beta particles from a ^90Sr source; these were used to characterize the response and the gain of an LGAD as a function of bias voltage and collected charge. Here, the experimental results are also compared to TCAD simulations.

47 OTHER INSTRUMENTATION↗

DOE OSTI2020

Fermi Gases in Bichromatic Superlattices

The purpose of the program is the broad study of designer materials made of ultra-cold atoms and light, which provides new paradigms for emulating exotic layered systems. Bichromatic superlattices enable control and study of both dimensionality and dispersion in layered, strongly correlated Fermi gases, to model high-temperature superfluidity/superconductivity. Most layered materials are quasi-two-dimensional, neither two-dimensional, like a sheet, nor three-dimensional, like a gas, but somewhere in between. In quasi-2D layers with an unequal number of spin-up and spin-down electrons, particularly strong attraction between pairs of electrons with opposite spins is predicted to achieve the highest possible superconducting transition temperatures. To understand these materials, we emulate them with a layered, ultra-cold Fermi gas of 6Li atoms, magnetically tuned near a collisional (Feshbach) resonance, where precise control of the attraction, spin-composition, dimensionality and dispersion provides new tests of theory. The primary goals are of the program are: (1) Elucidation of the effects of dimensionality and confining potential shape on the enhancement of high-temperature superfluidity in a layered, strongly correlated Fermi gases; (2) Control of dispersion and the study of tunable Dirac points in one dimension.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Low‐Loss Far‐Infrared Surface Phonon Polaritons in Suspended SrTiO 3 Nanomembranes

Phonon polaritons (PhPs), excitations arising from the coupling of light with lattice vibrations, enable light confinement and local field enhancement, which is essential for various photonic and thermal applications. To date, PhPs with high confinement and low loss are mainly observed in the mid-infrared regime and mostly in manually exfoliated flakes of van der Waals (vdW) materials. In this work, the existence of low-loss, thickness-tunable phonon polaritons in the far-infrared regime within transferable freestanding SrTiO 3 membranes synthesized through a scalable approach, achieving high figures of merit is demonstrated, which are comparable to the previous record values from the vdW materials. Leveraging atomic precision in thickness control, large dimensions, and compatibility with mature oxide electronics, functional oxide membranes present a promising large-scale 2D platform alternative to vdW materials for on-chip polaritonic technologies in the infrared regime.

functional oxide membranes↗

DOE OSTI2022

Fluorescence-coupled micropipette aspiration assay to examine calcium mobilization caused by red blood cell mechanosensing

Abstract Mechanical stimuli such as tension, compression, and shear stress play critical roles in the physiological functions of red blood cells (RBCs) and their homeostasis, ATP release, and rheological properties. Intracellular calcium (Ca 2+ ) mobilization reflects RBC mechanosensing as they transverse the complex vasculature. Emerging studies have demonstrated the presence of mechanosensitive Ca 2+ permeable ion channels and their function has been implicated in the regulation of RBC volume and deformability. However, how these mechanoreceptors trigger Ca 2+ influx and subsequent cellular responses are still unclear. Here, we introduce a fluorescence-coupled micropipette aspiration assay to examine RBC mechanosensing at the single-cell level. To achieve a wide range of cell aspirations, we implemented and compared two negative pressure adjusting apparatuses: a homemade water manometer (− 2.94 to 0 mmH 2 O) and a pneumatic high-speed pressure clamp (− 25 to 0 mmHg). To visualize Ca 2+ influx, RBCs were pre-loaded with an intensiometric probe Cal-520 AM, then imaged under a confocal microscope with concurrent bright-field and fluorescent imaging at acquisition rates of 10 frames per second. Remarkably, we observed the related changes in intracellular Ca 2+ levels immediately after aspirating individual RBCs in a pressure-dependent manner. The RBC aspirated by the water manometer only displayed 1.1-fold increase in fluorescence intensity, whereas the RBC aspirated by the pneumatic clamp showed up to threefold increase. These results demonstrated the water manometer as a gentle tool for cell manipulation with minimal pre-activation, while the high-speed pneumatic clamp as a much stronger pressure actuator to examine cell mechanosensing directly. Together, this multimodal platform enables us to precisely control aspiration and membrane tension, and subsequently correlate this with intracellular calcium concentration dynamics in a robust and reproducible manner.

Wang, Haoqing↗

DOE OSTI2025

Selective Oxidation and Cr Segregation in High-Entropy Oxide Thin Films

High-entropy oxides (HEOs) offer exceptional compositional flexibility and structural stability, making them promising materials for energy and catalytic applications. Here, in this study, we investigate Sr doping effects on B-site cation oxidation states, local composition, and structure in epitaxial La 1–x Sr x (Cr 0.2 Mn 0.2 Fe 0.2 Co 0.2 Ni 0.2 )O 3 thin films. X-ray spectroscopies reveal that Sr doping preferentially promotes Cr oxidation from Cr 3+ to Cr 6+ , partially oxidizes Co and Ni, while leaving Mn 4+ and Fe 3+ unchanged. Atomic-resolution scanning transmission electron microscopy with energy-dispersive X-ray spectroscopy shows pronounced Cr segregation, with depletion at the interface and enrichment at the surface, along with partial amorphization in heavily Sr-doped samples. This segregation is likely driven by oxidation-induced migration of smaller, high-valence Cr cations during growth. These findings highlight the critical interplay between charge compensation, local strain, and compositional fluctuations in HEOs, indicating that precise control over growth conditions is critical for tuning their surface composition and electronic structure toward more robust electrocatalyst design.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Application of Koopman operator for model-based control of fracture propagation and proppant transport in hydraulic fracturing operation

This work explores the application of the recently developed Koopman operator approach for model identification and feedback control of a hydraulic fracturing process. Controlling fracture propagation and proppant transport with precision is a challenge due in large part to the difficulty of constructing approximate models that accurately capture the characteristic moving boundary and highly-coupled dynamics exhibited by the process. Koopman operator theory is particularly attractive here as it offers a way to explicitly construct linear representations for even highly nonlinear dynamics. The method is data-driven and relies on lifting the states to an infinite-dimensional space of functions called observables where the dynamics are governed by a linear Koopman operator. Here this work considers two problems: (a) fracture geometry control, and (b) proppant concentration control. In both cases, an approximate linear model of the corresponding dynamics is constructed and used to design a model predictive controller (MPC). The manuscript shows that in the case of highly nonlinear dynamics, as observed in the proppant concentration, use of canonical functions in the observable basis fails. In such cases, a priori system knowledge can be leveraged to choose the required basis. The numerical experiments demonstrate that the Koopman linear model shows excellent agreement with the real system and successfully achieves the desired target values maximizing the oil and gas productivity. Additionally, due to its linear structure, the Koopman models allow convex MPC formulations that avoid any issues associated with nonlinear optimization.

42 ENGINEERING↗

DOE OSTI2024

Detecting defects that reduce breakdown voltage using machine learning and optical profilometry

Abstract Semiconductor wafer manufacturing relies on the precise control of various performance metrics to ensure the quality and reliability of integrated circuits. In particular, GaN has properties that are advantageous for high voltage and high frequency power devices; however, defects in the substrate growth and manufacturing are preventing vertical devices from performing optimally. This paper explores the application of machine learning techniques utilizing data obtained from optical profilometry as input variables to predict the probability of a wafer meeting performance metrics, specifically the breakdown voltage (V bk ). By incorporating machine learning techniques, it is possible to reliably predict performance metrics that cause devices to fail at low voltage. For diodes that fail at a higher (but still below theoretical) breakdown voltage, alternative inspection methods or a combination of several experimental techniques may be necessary.

42 ENGINEERING↗

DOE OSTI2024

Roadmap on basic research needs for laser technology

Motivated by the profound impact of laser technology on science, arising from an increase in focused light intensity by seven orders of magnitude and flashes so short electron motion is visible, this roadmap outlines the paths forward in laser technology to enable the next generation of science and applications. Despite remarkable progress, the field confronts challenges in developing compact, high-power sources, enhancing scalability and efficiency, and ensuring safety standards. Future research endeavors aim to revolutionize laser power, energy, repetition rate and precision control; to transform mid-infrared sources; to revolutionize approaches to field control and frequency conversion. These require reinvention of materials and optics to enable intense laser science and interdisciplinary collaboration. The roadmap underscores the dynamic nature of laser technology and its potential to address global challenges, propelling progress and fostering sustainable development. Ultimately, advancements in laser technology hold promise to revolutionize myriad applications, heralding a future defined by innovation, efficiency, and sustainability.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2022

Facet-selective etching trajectories of individual semiconductor nanocrystals

The size and shape of semiconductor nanocrystals govern their optical and electronic properties. Liquid cell transmission electron microscopy (LCTEM) is an emerging tool that can directly visualize nanoscale chemical transformations and therefore inform the precise synthesis of nanostructures with desired functions. However, it remains difficult to controllably investigate the reactions of semiconductor nanocrystals with LCTEM, because of the highly reactive environment formed by radiolysis of liquid. Here, we harness the radiolysis processes and report the single-particle etching trajectories of prototypical semiconductor nanomaterials with well-defined crystalline facets. Lead selenide nanocubes represent an isotropic structure that retains the cubic shape during etching via a layer-by-layer mechanism. The anisotropic arrow-shaped cadmium selenide nanorods have polar facets terminated by either cadmium or selenium atoms, and the transformation trajectory is driven by etching the selenium-terminated facets. LCTEM trajectories reveal how nanoscale shape transformations of semiconductors are governed by the reactivity of specific facets in liquid environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Development of X-ray Wavefront Sensing Techniques for Adaptive Optics Control at the Advanced Photon Source

The planning and construction of new and upgraded high-brightness X-ray synchrotron and free electron laser sources, such as the Advanced Photon Source upgrade project (APS-U), are driving numerous opportunities to advance X-ray science and technologies. At the same time, an increasing number of highly diverse beamline experiments demand wavefront-preserving adaptive X-ray optics with both high precision and flexibility. At the APS, significant effort has been devoted to developing next-generation adaptive and corrective optics combined with state-of-the-art at-wavelength wavefront sensing techniques and an intelligent feedback control system for the automation and self-alignment of beamline optical systems. This article reviews recent achievements in these areas at the APS. Further, these include the development of in-situ wavefront sensing, the application in active feedback control of ultra-precision deformable mirrors, and the exploration of non-invasive wavefront sensing techniques for adaptive optics and beamline diagnostics.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗