Measurements and simulation of liquid films during drainage displacements and snap-off in constricted capillary tubes
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Transport Test Problems for Radiation Detection Scenarios
Modeling forms an important component of radiation detection development, allowing for testing of new detector designs, evaluation of existing equipment against a wide variety of potential threat sources, and assessing operation performance of radiation detection systems. This can, however, result in large and complex scenarios which are time consuming to model. A variety of approaches to radiation transport modeling exist with complementary strengths and weaknesses for different problems. This variety of approaches, and the development of promising new tools (such as ORNL’s ADVANTG) which combine benefits of multiple approaches, illustrates the need for a means of evaluating or comparing different techniques for radiation detection problems. This report presents a set of 9 test problems for comparing different types of radiation transport calculations, identifying appropriate tools for classes of problems, and testing and guiding the development of new methods. Cases are drawn primarily from existing or previous calculations with a preference for cases which include experimental data, or otherwise have results with a high level of confidence, are non-sensitive, and represent problem sets of interest to NA-22. From a technical perspective, cases are chosen to span a range of difficulty and to include gamma transport, neutron transport, or both and represent different important physical processes and a range of sensitivity to angular or energy fidelity. Following test case identification, existing information about geometry, measurements, and previous calculations were assembled. Monte Carlo results (MCNP decks) were reviewed or created and re-run in order to attain accurate computational times and to verify agreement with experimental data, when present. Test case information was then conveyed to ORNL in order to guide testing and development of hybrid calculations. The results of those ADVANTG calculations were then sent to PNNL for compilation. This is a report describing the details of the selected test cases and results from available transport codes. Additional results from other transport codes will be added during the next year, along with additional cases if needed for software testing. Future work will extend the test problems to include more extensive cross-code comparisons as well as more refined metrics for evaluating the tradeoffs between operator time, computational time, and solution accuracy, to assemble a formalized benchmark set.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Mobility assessment of the BCC and carbide phases in the C-Nb, C-U and Nb-U systems
Uranium carbides with refractory metal additions are considered for Gen IV nuclear reactors and nuclear thermal propulsion as fuels for their high-temperature and corrosion resistant properties. Understanding kinetic effects that dictate microstructural evolution during fabrication and operating conditions is essential to advance technological development of these fuels. This work presents the development of an atomic mobility database for C-Nb-U systems based off available experimental data supported with ab-initio methods. The mobility assessments and uncertainty quantification (using Markov chain Monte Carlo) were conducted in the Kawin software. Carbon diffusion is considered dominant, as metal diffusion is much slower, with niobium diffusion being even slower and rate limiting than uranium metal. We provide a comprehensive and self-consistent thermo-kinetic database that is validated by diffusion couple simulations through Kawin. In conclusion, this enables prediction of microstructural and phase evolution critical for the development and lifetime assessment of next generation nuclear fuels.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
TH-E-18A-01: Developments in Monte Carlo Methods for Medical Imaging
Monte Carlo simulation methods are widely used in medical physics research and are starting to be implemented in clinical applications such as radiation therapy planning systems. Monte Carlo simulations offer the capability to accurately estimate quantities of interest that are challenging to measure experimentally while taking into account the realistic anatomy of an individual patient. Traditionally, practical application of Monte Carlo simulation codes in diagnostic imaging was limited by the need for large computational resources or long execution times. However, recent advancements in high-performance computing hardware, combined with a new generation of Monte Carlo simulation algorithms and novel postprocessing methods, are allowing for the computation of relevant imaging parameters of interest such as patient organ doses and scatter-to-primaryratios in radiographic projections in just a few seconds using affordable computational resources. Programmable Graphics Processing Units (GPUs), for example, provide a convenient, affordable platform for parallelized Monte Carlo executions that yield simulation times on the order of 10{sup 7} xray/ s. Even with GPU acceleration, however, Monte Carlo simulation times can be prohibitive for routine clinical practice. To reduce simulation times further, variance reduction techniques can be used to alter the probabilistic models underlying the x-ray tracking process, resulting in lower variance in the results without biasing the estimates. Other complementary strategies for further reductions in computation time are denoising of the Monte Carlo estimates and estimating (scoring) the quantity of interest at a sparse set of sampling locations (e.g. at a small number of detector pixels in a scatter simulation) followed by interpolation. Beyond reduction of the computational resources required for performing Monte Carlo simulations in medical imaging, the use of accurate representations of patient anatomy is crucial to the virtual generation of medical images and accurate estimation of radiation dose and other imaging parameters. For this, detailed computational phantoms of the patient anatomy must be utilized and implemented within the radiation transport code. Computational phantoms presently come in one of three format types, and in one of four morphometric categories. Format types include stylized (mathematical equation-based), voxel (segmented CT/MR images), and hybrid (NURBS and polygon mesh surfaces). Morphometric categories include reference (small library of phantoms by age at 50th height/weight percentile), patient-dependent (larger library of phantoms at various combinations of height/weight percentiles), patient-sculpted (phantoms altered to match the patient's unique outer body contour), and finally, patient-specific (an exact representation of the patient with respect to both body contour and internal anatomy). The existence and availability of these phantoms represents a very important advance for the simulation of realistic medical imaging applications using Monte Carlo methods. New Monte Carlo simulation codes need to be thoroughly validated before they can be used to perform novel research. Ideally, the validation process would involve comparison of results with those of an experimental measurement, but accurate replication of experimental conditions can be very challenging. It is very common to validate new Monte Carlo simulations by replicating previously published simulation results of similar experiments. This process, however, is commonly problematic due to the lack of sufficient information in the published reports of previous work so as to be able to replicate the simulation in detail. To aid in this process, the AAPM Task Group 195 prepared a report in which six different imaging research experiments commonly performed using Monte Carlo simulations are described and their results provided. The simulation conditions of all six cases are provided in full detail, with all necessary data on material composition, source, geometry, scoring and other parameters provided. The results of these simulations when performed with the four most common publicly available Monte Carlo packages are also provided in tabular form. The Task Group 195 Report will be useful for researchers needing to validate their Monte Carlo work, and for trainees needing to learn Monte Carlo simulation methods. In this symposium we will review the recent advancements in highperformance computing hardware enabling the reduction in computational resources needed for Monte Carlo simulations in medical imaging. We will review variance reduction techniques commonly applied in Monte Carlo simulations of medical imaging systems and present implementation strategies for efficient combination of these techniques with GPU acceleration. Trade-offs involved in Monte Carlo acceleration by means of denoising and “sparse sampling” will be discussed. A method for rapid scatter correction in cone-beam CT (<5 min/scan) will be presented as an illustration of the simulation speeds achievable with optimized Monte Carlo simulations. We will also discuss the development, availability, and capability of the various combinations of computational phantoms for Monte Carlo simulation of medical imaging systems. Finally, we will review some examples of experimental validation of Monte Carlo simulations and will present the AAPM Task Group 195 Report. Learning Objectives: Describe the advances in hardware available for performing Monte Carlo simulations in high performance computing environments. Explain variance reduction, denoising and sparse sampling techniques available for reduction of computational time needed for Monte Carlo simulations of medical imaging. List and compare the computational anthropomorphic phantoms currently available for more accurate assessment of medical imaging parameters in Monte Carlo simulations. Describe experimental methods used for validation of Monte Carlo simulations in medical imaging. Describe the AAPM Task Group 195 Report and its use for validation and teaching of Monte Carlo simulations in medical imaging.
60 APPLIED LIFE SCIENCES↗
Direct observation of ice nucleation events on individual atmospheric particles
Heterogeneous ice nucleation is a physical chemistry process of critical relevance to a range of topics in the fundamental and applied sciences and technologies. Heterogeneous ice nucleation remains insufficiently understood, partially due to the lack of experimental methods capable of obtaining in situ microscopic details of ice formation over nucleating substrates or particles. Here, we present microscopic observations of ice nucleation events on kaolinite particles at the nanoscale and demonstrate the capability of direct tracking and micro-spectroscopic characterization of individual ice nucleating particles (INPs) in an authentic atmospheric sample. Furthermore, this approach utilizes a custom-built ice nucleation cell, interfaced with an Environmental Scanning Electron Microscope (IN-ESEM platform) operated at temperatures and relative humidities relevant for heterogeneous ice nucleation. The IN-ESEM platform allows dynamic observations of individual ice formation events over particles in isobaric and isothermal experiments. Isothermal experiments on individual kaolinite particles demonstrate that ice crystals preferably nucleate at the edges of the stacked kaolinite platelets, rather than on their basal planes. Finally, these experimental observations of the location of ice nucleation provide direct information for further theoretical chemistry predictions of ice formation on kaolinite.
54 ENVIRONMENTAL SCIENCES↗
Dealloying, Microstructure and the Corrosion/Protection of Cast Magnesium Alloys
The purpose of this project was to develop a greater understanding of micro-galvanic corrosion effects in cast magnesium alloys using both experimental and computational methods. Experimental accomplishments have been made in the following areas of interest: characterization, aqueous free-corrosion, atmospheric corrosion, ionic liquid dissolution, rate kinetics of oxide dissolution, and coating investigation. Commercial alloys (AZ91D, AM60, and AZ31B), binary-phase alloys (αMg-2at.%Al, αMg-5at.%Al, and Mg-8at.%Al), and component phases (Mg, Al, β-Mg, β-1%Zn, MnAl3) were obtained and characterized using energy dispersive spectroscopy (EDS), X-ray diffraction (XRD), and scanning electron microscopy (SEM). Full immersion in aqueous chloride was used to characterize the corrosion behavior of alloys. Rotating disc electrodes (RDEs) were used to observe accelerated long-term corrosion behavior. Al surface redistribution for freely corroded samples was analyzed using SEM, EDS, and lithium underpotential deposition (Li UPD). Atmospheric corrosion was observed using contact angle evolution, overnight pH monitoring, and surface pH evolution studies. Ionic liquid corrosion characterization was performed using linear sweep voltammetry and potentiostatic dissolution in 150° choline chloride-urea (cc-urea). Two surface coatings were investigated: (1) Li-carbonate and (2) cc-urea. Li-carbonate coatings were characterized using X-ray photoelectron spectroscopy (XPS), SEM, and aqueous free corrosion potential monitoring. Hydrophobic cc-urea coatings were characterized using contact angle measurements and electrochemical impedance spectroscopy. Oxide dissolution rate kinetics were studied using inductively coupled plasma mass spectroscopy (ICP-MS). Computational accomplishments have been made through the development of Kinetic Monte Carlo (KMC) simulations which model time- and composition-dependent effects on the microstructure due to spatial redistribution of alloying elements during corrosion.
36 MATERIALS SCIENCE↗
Accurate Ultrasonic Thickness Measurement for Arbitrary Time-Variant Thermal Profile
Ultrasonic thickness measurement of mechanical structures is one of the most popular and commonly used nondestructive methods for various kinds of process control and corrosion monitoring. With ultrasonic propagation speed being temperature-dependent, the thickness measurement can be performed reliably only when the thermal profile is completely known. Most conventional techniques assume the temperature of the test structure is uniform and at room temperature across its thickness. Such assumptions may lead to large errors in the thickness measurement, especially when there are significant temperature variations across the thickness. State-of-the-art techniques use external temperature measurements or implement iterative methods to compensate for the unknown thermal profiles. However, such techniques produce unsatisfactory results when the heat distribution is complex or varies rapidly with time. In this work, we propose a two-sensors technique, using both compressive and shear excitations, with a non-iterative rapid data processing method for accurate thickness measurement under arbitrary time-variant thermal profile. The independent behavior of shear and compressive waves is used to formulate a real-time thickness estimation technique. The developed technique is experimentally validated on a steel plate with fixed acoustic sensors. Test results show that the error in thickness estimation can be reduced by up to 98% compared to conventional thickness gauging methods.
36 MATERIALS SCIENCE↗
Prototype tests of the electromagnetic particle injector-2 for fast time response disruption mitigation in tokamaks
Predicting and controlling disruptions is an important and urgent issue for ITER. Some disruptions with a short warning time may be unavoidable. For these cases, a fast time response disruption mitigation method is essential. Experimental tests on a prototype system of a novel, rapid time-response disruption mitigation system being developed for tokamak-based reactors and as a backup option for ITER, referred to as the electromagnetic particle injector (EPI), have been able to verify the primary advantages of the concept. These are its ability to meet short warning time scales of <10 ms while attaining the projected high velocities for deep radiative payload penetration in reactor-scale plasmas. The EPI relies on an electromagnetic propulsion system. A metallic sabot is accelerated electromagnetically to the required velocities (>1 km s -1 ) within 2 ms, at which point it releases a radiative payload consisting of a shell pellet or well-defined microspheres. Initial experimental tests from the prototype system show attainment of over 600 m s -1 in about 1 ms. Finally, essential aspects of payload separation from the sabot and sabot capture have also been demonstrated at 200 m s -1 , and the method can be extended to over 2 km s -1 .
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Soft X-ray measurements of transport and MHD activity in the core and edge NSTX plasma (Final Technical Report)
A comprehensive suite of innovative diagnostic instrumentation and techniques has been developed by the Johns Hopkins collaboration for measurements of transport and MHD activity in the core and edge of the National Spherical Torus Experiment (NSTX) at the Princeton Plasma Physics Laboratory (PPPL). These include ultrafast multi-energy poloidal soft X-ray arrays, high spatial resolution multi-energy tangential soft X-ray arrays, high spectral resolution transmission grating imaging VUV spectrometers and ultrafast bolometric arrays, which measure over a broad range of spatial, spectral, and temporal scales the emission from ohmic, RF, and beam driven NSTX plasmas. The instrumentation was designed to fulfill the specific measurement needs of the Spherical Torus (ST) magnetic fusion concept and is accompanied by a comprehensive set of numerical tools for data analysis and modeling, aimed at determining as many as possible plasma parameters and at extracting as much as possible physics information from NSTX experiments. The Johns Hopkins diagnostics have been and continue to be instrumental for essentially all the NSTX experiments. In addition, our own research and experiments using these diagnostics has led over the years to fundamental conclusions for the ST fusion physics, such as the establishment of near neoclassical impurity transport in the NSTX core and edge plasma, and the critical role of the Global Alfven Eigenmode (GAE) MHD activity for the ST core electron thermal transport. The Johns Hopkins Diagnostics continue to be operational on the upgraded NSTX-U and will provide key plasma information in its upcoming high field, current and power experimental campaigns. The present report summarizes the main technical characteristics and measurement capabilities of the diagnostic instrumentation and methods developed within our research and describes a key physics result achieved during this research. Success in our research was made possible also by the excellent support and cooperation of the NSTX research team and of PPPL researchers, who are warmly acknowledged here.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
“Inverting” X-ray Absorption Spectra of Catalysts by Machine Learning in Search for Activity Descriptors
The rapid growth of methods emerging in the past decade for synthesis of “designer” catalysts—ranging from the size and shape-selected nanoparticles to mass-selected clusters, to precisely engineered bimetallic surfaces, to single site and pair site catalysts—has opened opportunities for tailoring the catalyst structure for the desired activity and selectivity. It has also sharpened the need for developing approaches to the operando characterization, ones that identify the catalytic active sites and follow their evolutions in reaction conditions. Commonly used methods for determination of the activity descriptors in the nanocatalysts, based on the correlation between the changes in catalyst performance and evolution of its structural and electronic properties, are hampered by the paucity of experimental techniques that can detect such properties with high accuracy and in reaction conditions. Out of many such techniques, X-ray absorption spectroscopy (XAS) stands out as an element-specific method that is very sensitive to the local geometric and electronic properties of the metal atoms and their surroundings and, therefore, is able to track catalyst structure modifications in operando conditions. Despite the vast amount of structure-specific information (such as, e.g., the charge states and radial distribution function of neighbors of selected atomic species) stored in the XAS data of catalysts, extracting it from the spectra is challenging, especially in the conditions of low metal weight loading, nanoscale dimensions, heterogeneous size and composition distributions, and harsh reaction environment. In this Perspective, we discuss the recent developments in XAS data analysis achieved by employing supervised and unsupervised machine learning (ML) methods for structural characterization of catalysts. By benefiting from the sensitivity of ML methods to subtle variations in experimental data, a previously “hidden” relationship between the X-ray absorption spectrum and descriptors of material’s structure and/or composition can be found, as illustrated on representative examples of mono-, hetero-, and nonmetallic catalysts. In the case of supervised ML, the experimental spectra can be rapidly “inverted”, and the structure of the catalyst can be tracked in real time and in reaction conditions. Finally, emerging opportunities for catalysis research that the ML methods enable, such as high-throughput data analysis, and their applications to other experimental probes of catalyst structure are discussed.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Area 2. Use Of Engineered Nanoparticle-Stabilized CO 2 Foams To Improve Volumetric Sweep Of CO 2 EOR Processes
The goal of this project was to develop a new CO 2 injection enhanced oil recovery (CO 2 -EOR) process using engineered nanoparticles with optimized surface coatings that has better volumetric sweep efficiency and a wider application range than conventional CO 2 -EOR processes. The main objectives of this project were to (1) identify the characteristics of the optimal nanoparticles that generate extremely stable CO 2 foams in situ in reservoir regions without oil; (2) develop a novel method of mobility control using “self-guiding” foams with smart nanoparticles; and (3) extend the applicability of the new method to reservoirs having a wide range of salinity, temperatures, and heterogeneity. Concurrent with our experimental effort to understand the foam generation and transport processes and foam-induced mobility reduction, we also developed mathematical models to explain the underlying processes and mechanisms that govern the fate of nanoparticle-stabilized CO 2 foams in porous media and applied these models to (1) simulate the results of foam generation and transport experiments conducted in beadpack and sandstone core systems, (2) analyze CO 2 injection data received from a field operator, and (3) aid with the design of a foam injection pilot test. Our simulator is applicable to near-injection well field-scale foam injection problems and accounts for the effects due to layered heterogeneity in permeability field, foam stabilizing agents effects, oil presence, and shear-thinning on the generation and transport of nanoparticle-stabilized C/W foams. This report presents the details of our experimental and numerical modeling work and outlines the highlights of our findings.
54 ENVIRONMENTAL SCIENCES↗
Machine learning assisted bayesian inference of mix and hot-spot conditions in NIF implosions
Experiments on the National Ignition Facility (NIF) have provided clear evidence of ablator material mixing into the Hot-Spot, leading to degraded performance. However, inferring the amount of mix and Hot-Spot conditions from typical experimental observations (e.g. x-ray spectra and images) is highly challenging. Here, we have developed an analysis method that utilizes machine learning assisted Bayesian inference to find the probability distributions of the Hot-Spot and mix conditions. This approach uses a neural network, trained on an idealized 2-dimensional representation of the Hot-Spot and mix distribution, and Bayesian inference to find the statistical distributions of Hot-Spot conditions that provide a match with observations. We have tested this method with synthetic data from simulations.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Modeling shock-induced void collapse in single-crystal Ta systems at the mesoscales
Understanding the role of microstructural heterogeneities on the shock wave propagation and defect evolution behavior is essential to predicting the dynamic response of metals. Heterogeneities, such as voids, provide challenges to understanding the wave propagation behavior as the shock-void interaction can collapse the void and result in large plastic strains and significant heating (hot spot formation) in the metal. Accurate modeling of this phenomenon requires predicting the void collapse mechanisms and the related heat generation and dissipation mechanisms (hotspot formation) that determine the microstructure evolution. While molecular dynamics (MD) simulations can model the void collapse behavior, the time/length scale capabilities pose a challenge to connect with continuum models or the experimental scales. Here, this study presents the capability of the newly developed quasi-coarse-grained dynamics (QCGD) method that extends the MD simulations to larger system sizes and longer times to model this phenomenon. This study uses QCGD simulations to investigate the mechanisms of shock wave interactions with pre-existing voids in single-crystal Ta microstructures for variations in shock pressures, void size, and loading orientations. For a given orientation, the plasticity contributions and rates of void collapse are observed to vary with shock pressures and void size. The larger void sizes and higher pressures result in increased temperatures (hot spots) and faster void collapse rates and unravel the variations in the plasticity contributions. In addition, QCGD simulations investigate the post-collapse microstructure evolution as a release wave travels through the hot spot region. The simulations reveal that the reduction in temperatures due to heat dissipation initiates the dynamic recrystallization behavior in the hotspot regions.
36 MATERIALS SCIENCE↗
Delayed gamma-ray spectroscopy with lanthanum bromide detector for non-destructive assay of nuclear material
High-energy delayed γ-ray spectroscopy is a potential technique for directly assaying spent fuel assemblies and achieving the safeguards goal of quantifying nuclear material inventories for spent fuel handling, interim storage, reprocessing facilities, repository sites, and final disposal. Requirements for the γ-ray detection system, up to ~6 MeV, can be summarized as follows: high efficiency at high γ-ray energies, high energy resolution, good linearity between γ-ray energy and output signal amplitude, ability to operate at very high count rates, and ease of use in industrial environments such as nuclear facilities. High Purity Germanium Detectors (HPGe) are the state of the art and provide excellent energy resolution but are limited in their count rate capability. Lanthanum Bromide (LaBr 3 ) scintillation detectors offer significantly higher count rate capabilities at lower energy resolution. Thus, LaBr 3 detectors may be an effective alternative for nuclear spent-fuel applications, where count-rate capability is a requirement. This paper documents the measured performance of a 2” (length) × 2” (diameter) of LaBr3 scintillation detector system, coupled to a negatively biased PMT and a tapered active high voltage divider, with count-rates up to ~3 Mcps. An experimental methodology was developed that uses the average current from the PMT’s anode and a dual source method to characterize the detector system at specific very high count rate values. Delayed γ-ray spectra were acquired with the LaBr 3 detector system at the Idaho Accelerator Center, Idaho State University, where samples of ~3g of 235 U were irradiated with moderated neutrons from a photo-neutron source. Results of the spectroscopy characterization and analysis of the delayed γ-ray spectra acquired indicate the possible use of LaBr3 scintillation detectors when high count rate capability may outweigh the lower energy resolution.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Tuning domain size and crystallinity in isoindigo/PCBM organic solar cells via solution shearing
Despite having achieved the long sought-after performance of 10% power conversion efficiency, high performance organic photovoltaics (OPVs) are still mostly constrained to lab scale devices fabricated by spin coating. Efforts to produce printed OPVs lag considerably behind, and the sensitivity to different fabrication methods highlights the need to develop a comprehensive understanding of the processing-morphology relationship in printing methods. Here we present a systematic experimental investigation of a model low bandgap polymer/fullerene system, poly-isoindigo thienothiophene/PC 61 BM, using a lab-scale analogue to roll-to-roll coating as the fabrication tool in order to understand the impact of processing parameters on morphological evolution. We report that domain size and polymer crystallinity can be tuned by a factor of two by controlling the temperature and coating speed. Lower fabrication temperature simultaneously decreased the phase separation domain size and increased the relative degree of crystallinity in those domains, leading to improved photocurrent. We conclude that domain size in isoindigo/PCBM is dictated by spontaneous phase separation rather than crystal nucleation and growth. Moreover we present a model to describe the temperature dependence of domain size formation in our system, which demonstrates that morphology is not necessarily strictly dependent on the evaporation rate, but rather on the interplay between evaporation and diffusion during the printing process.
14 SOLAR ENERGY↗
Metasurface holographic optical traps for ultracold atoms
We propose metasurface holograms as a novel platform to generate optical trap arrays for cold atoms with high quality, efficiency, and thermal stability. We developed design and fabrication methods to create dielectric, phase-only metasurface holograms based on titanium dioxide. We experimentally demonstrated optical trap arrays of various geometries, including periodic and aperiodic configurations with dimensions ranging from 1D to 3D and up to a few hundred trap sites. We characterized the performance of the holographic metasurfaces in terms of the positioning accuracy, size and intensity uniformity of the generated traps, and power handling capability of the dielectric metasurfaces. Our proposed platform has great potential for enabling fundamental studies of quantum many-body physics, and quantum simulation and computation tasks. The compact form factor, passive nature, good power handling capability, and scalability of generating high-quality, large-scale arrays also make the metasurface platform uniquely suitable for realizing field-deployable devices and systems based on cold atoms.
42 ENGINEERING↗
Controlling internal degrees: general discussion
Temperature is a very important concept in ion spectroscopy and its control has seen tremendous advances in recent years. Cryogenic ion traps are now found in many experiments and serve as thermostats, reaction vessels, clustering sources and spectroscopic sample chambers. The control over internal degrees of freedom provides routes to forming ions that are relevant at cryogenic temperatures such as in the interstellar medium and to control and lock-in conformations. It also provides a condensing environment and allows weakly bound clusters to be formed, which in turn provides new routes to action spectroscopy. This session will discuss the most recent developments in cryogenic spectroscopy and the research it enables and how new theoretical methods allow the prediction of experimental spectra as a function of temperature. The main discussion topics will cover: the best cooling methods; how temperature can be used to form exotic clusters and weakly interacting systems; and the possibilities for probing conformational locking and metastable structures.
Ahmed, Musahid↗