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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 37 records · Page 2

The anisotropic nature of singlet fission in single crystalline organic semiconductors

The escalating global energy predicament implores for a revolutionary resolution—one that converts sunlight into electricity—holding the key to supreme conversion efficiency. This comprehensive review embarks on the exploration of the principle of generating multiple excitons per absorbed photon, a captivating concept that possesses the potential to redefine the fundamental confines of conversion efficiency, albeit its application remains limited in photovoltaic devices. At the nucleus of this phenomenon are two principal processes: multiple exciton generation (MEG) within quantum-confined environments, and singlet fission (SF) inside molecular crystals. The process of SF, characterized by the cleavage of a single photogenerated singlet exciton into two triplet excitons, holds promise to potentially amplify photon-to-electron conversion efficiency twofold, thereby laying the groundwork to challenge the detailed balance limit of solar cell efficiency. Our discourse primarily dissects the complex nature of SF in crystalline organic semiconductors, laying special emphasis on the anisotropic behavior of SF and the diffusion of the subsequent triplet excitons in single-crystalline polyacene organic semiconductors. We initiate this journey of discovery by elucidating the principles of MEG and SF, tracing their historical genesis, and scrutinizing the anisotropy of SF and the impact of quantum decoherence within the purview of functional mode electron transfer theory. We present an overview of prominent techniques deployed in investigating anisotropic SF in organic semiconductors, including femtosecond transient absorption microscopy and imaging as well as stimulated Raman scattering microscopies, and highlight recent breakthroughs linked with the anisotropic dimensions of Davydov splitting, Herzberg–Teller effects, SF, and triplet transport operations in single-crystalline polyacenes. Through this comprehensive analysis, our objective is to interweave the fundamental principles of anisotropic SF and triplet transport with the current frontiers of scientific discovery, providing inspiration and facilitating future ventures to harness the anisotropic attributes of organic semiconductor crystals in the design of pioneering photovoltaic and photonic devices.

Chemistry↗

Best practices for first-principles simulations of epitaxial inorganic interfaces

Abstract At an interface between two materials physical properties and functionalities may be achieved, which would not exist in either material alone. Epitaxial inorganic interfaces are at the heart of semiconductor, spintronic, and quantum devices. First principles simulations based on density functional theory (DFT) can help elucidate the electronic and magnetic properties of interfaces and relate them to the structure and composition at the atomistic scale. Furthermore, DFT simulations can predict the structure and properties of candidate interfaces and guide experimental efforts in promising directions. However, DFT simulations of interfaces can be technically elaborate and computationally expensive. To help researchers embarking on such simulations, this review covers best practices for first principles simulations of epitaxial inorganic interfaces, including DFT methods, interface model construction, interface structure prediction, and analysis and visualization tools.

Physics↗

Overview of ST40 results and future: expanding the physics basis of high-field spherical tokamaks

The goal of the ST40 programme is to explore the physics of high-field spherical tokamaks (STs), to validate empirical and theoretical models and, hence, to build confidence in predictions required to support the design of future generations of STs. ST40 is a compact high-field ST that has achieved the following parameters: R 0 = 0.4–0.55 m, I p = 0.20–0.85 MA, B t (R= 0.4 m) = 0.7–2.1 T, κ ⩽ 1.9, and A = 1.6–1.9. Highlights of recent experimental results include (i) H-mode and confinement studies at B t ⩽ 2.1 T, (ii) observation of bifurcation of the scrape-off-layer power fall-off width, λ q , into a ‘wide’ branch that follows existing H-mode scalings and a ‘narrow’ branch that exhibits λ q values that are up to 10 times lower than the predictions of established scalings, (iii) development of high-performance scenarios with plasma current, I p , up to 0.85 MA, (iv) development of highly non-inductive scenarios with high β p , and (v) the first ST40 experiments utilising the newly commissioned impurity powder dropper. The work on all these topics has been supported by a number of advancements in ST40 hardware and software, from plasma control to data analysis and interpretation. At the end of 2025, ST40 embarked on a major upgrade to further expand its capabilities by introducing, among other improvements, all-metal plasma-facing components, 1 MW of electron cyclotron heating, a pellet injector, and a pair of lithium evaporators for wall conditioning.

confinement↗

A use-case-driven approach for demonstrating the added value of digitalisation in wind energy

Digitalisation is one of the key drivers for reducing the costs and risks of wind energy. When considering whether to embark on a digitalisation initiative, two key questions arise. The first is what business or operational opportunities might feasibly be addressed and the second is which of the many potential aspects of digitalisation are relevant to those opportunities. In this work, we show how these questions can be answered with a use-case-driven approach, based around a survey aiming to collect and collate the main "pain points" (or everyday challenges) of people in the wind energy sector. Although the relatively low number of participants of the survey (46) means that the results should only be used indicatively, it is still possible to make some general recommendations for priorities for digitalisation efforts in the wind energy sector. Firstly, digitalisation efforts should focus both on supporting people carrying out cross-lifecycle tasks, in particular sharing data, managing data, undertaking general data analyses and accessing data. Tools to do this should deal with varying data formats and naming conventions, make metadata more accessible, define data and metadata standards, make more data publicly available and improve the quality of data. Secondly, efforts should also focus on supporting people in the wind farm operational phase, in particular with failure detection, fault diagnosis, failure rate modelling and predictive maintenance. Solutions to do this should focus on accessible and validated tools for fault detection, cloud or other data pipeline solutions for SCADA data and tools for exhaustive data documentation. Finally, digitalisation efforts should focus on better communicating and helping people become aware of existing solutions and tools, as well as on helping people to exert a stronger influence on possible solutions.

17 WIND ENERGY↗

Techno-economic assessment of electricity market potential for co-located hydro-floating PV systems

Abstract—Harnessing renewable energy from diverse sources is paramount for sustainable power systems. Recently, co-located floating PV (FPV) systems present an intriguing prospect in this context. These hybrid systems, blending hydro and solar power, may offer a more consistent electricity output and potential economic advantages. Yet, assessing their actual potential requires a comprehensive techno-economic assessment. In addition, probabilistic price forecasting has recently gained attention in electricity market because decisions based on such predictions can yield significantly higher profits than those made with point forecasts alone. To this end, this paper embarks on a journey to elucidate the electricity market potential of co-located hydro-FPV systems in a probabilistic fashion to investigate the technological merits and economic viability of co-located hydro-FPV under different market structures. Our preliminary findings suggest that LCOE and payback metrics are sensitive not only to different markets but also to different solar incentives. Concurrently, we also observe that the payback period is generally faster with a production tax credit (PTC) than an investment tax credit (ITC). This assessment serves as a cornerstone for understanding the future prospects of co-located hydro-FPV systems in modern electricity markets.

13 HYDRO ENERGY↗

Building Energy Systems as Behind-the-Meter Resources for Grid Services: Intelligent load control and transactive control and coordination

To mitigate the impacts of climate change, significant reductions in emissions from all sectors of the economy are needed. The electricity generation sector has embarked on an ambitious plan to include renewable generation as part of its decarbonization efforts, and many cities and states are mandating all-electric buildings. While renewable resources will reduce emissions, they are not dispatchable, they vary temporally, and their generation is uncertain. Under these conditions, traditional approaches to managing grid reliability, where supply follows demand, will not be efficient and may not be cost-effective. Further, there is a more efficient alternative for balancing the supply–demand imbalance and for absorbing variability and uncertainty of renewable energy using distributed energy resources (DERs) as opposed to reserve generation. Because buildings consume more than 75% of total U.S. annual electricity consumption, behind-the-meter (BTM) DERs have a load flexibility of 77 GW of power and 90 GWh of virtual energy storage capacity nationwide (Kalsi, 2017). Therefore, some portion of the supply–demand imbalance can be met by these DERs at a lower cost compared to business-as-usual solutions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Reconfigurable Intelligent Surfaces in Action for Nonterrestrial Networks

Next-generation communication technology will be made possible by cooperation between terrestrial networks with nonterrestrial networks (NTNs) composed of high-altitude platform stations (HAPSs) and satellites. Further, as humanity embarks on the long road to establish new habitats on other planets, the cooperation between NTNs and deep-space networks (DSNs) will be necessary. In this regard, we propose the use of reconfigurable intelligent surfaces (RISs) to improve coordination between these networks given that RISs perfectly match the size, weight, and power (SWaP) restrictions of operating in space. Here, a comprehensive framework of RIS-assisted nonterrestrial and interplanetary communications is presented that pinpoints challenges, use cases, and open issues. Furthermore, the performance of RIS-assisted NTNs under environmental effects, such as solar scintillation and satellite drag, is discussed in light of simulation results.

42 ENGINEERING↗

Primordial nucleosynthesis with non-extensive statistics

The conventional Big Bang model successfully anticipates the initial abundances of 2 H(D), 3 He, and 4 He, aligning remarkably well with observational data. However, a persistent challenge arises in the case of 7 Li, where the predicted abundance exceeds observations by a factor of approximately three. Despite numerous efforts employing traditional nuclear physics to address this incongruity over the years, the enigma surrounding the lithium anomaly endures. In this context, we embark on an exploration of Big Bang nucleosynthesis (BBN) of light element abundances with the application of Tsallis non-extensive statistics. A comparison is made between the outcomes obtained by varying the non-extensive parameter q away from its unity value and both observational data and abundance predictions derived from the conventional big bang model. Here, a good agreement is found for the abundances of 4 He, 3 He and 7 Li, implying that the lithium abundance puzzle might be due to a subtle fine-tuning of the physics ingredients used to determine the BBN. However, the deuterium abundance deviates from observations.

Bertulani, Carlos A.↗

Procedure for locating oil and gas wells in the Appalachian Basin

Locating undocumented (or poorly documented) oil and gas wells for environmental assessment is often difficult. Remnant features that confirm the presence of a well (intact casing/wellhead, well bore, etc.) are typically less than a meter in size and often are obscured from direct observation on the ground or from the air (by dense vegetation, for example). To efficiently find such features, it is useful to first systematically compile publicly available digital data at progressively smaller scales prior to embarking on field campaigns. Further, the information presented here describes the procedure developed and used by the U.S. Department of Energy's National Energy Technology Laboratory to locate potential oil and gas well sites for follow-up field verification and characterization. Digital data are first compiled from national and state resources such as well location/production databases, historical topographic maps, historical aerial photographs, and LiDAR data. Although each data set is likely to be incomplete or inaccurate to some extent, combining the data resources using geographic information system technology can generate potential well site targets with a higher degree of confidence, which improves the efficiency of fieldwork activities. This workflow was developed in the Appalachian Basin region, and although certain aspects may be unique, the general process would be applicable to locating undocumented wells in other regions.

54 ENVIRONMENTAL SCIENCES↗

Explosive Yield Estimation Using Regional Seismic Moment Tensors

Here, we use the Pasyanos and Chiang (2022) data set to calculate the seismic moment M 0 for each explosion and use the measured explosive yield W to validate the W~M 0 relationship in Denny and Johnson (1991; hereafter, DJ91). The M 0 is corrected by transforming to a potency tensor and applying more appropriate near-source geophysical parameter values in the moment estimate. The mean residual between observed and predicted yield is near zero; however, the standard deviation of the residuals results in an F-value (a 95% confidence factor) of about 5. We re-estimate the coefficients in the DJ91 model and find similar values and only a slight improvement in the F-value. Next, we embark on a similar model selection process as DJ91, allowing for non-cube-root yield scaling and other plausible near-source elastic moduli. As was found by DJ91, the yield dependence is not significantly different from unity, and a cube root assumption is valid. Therefore, we yield scale the seismic moment and test the significance of all plausible explanatory variables. Isotropic moment performs better in the response variable than total moment. The preference for isotropic moment could be due to its relationship to volume change, which would be more directly affected by explosive yield. Surprisingly, we find that the overburden pressure, which is a function of depth, is not a significant parameter in the model. We hypothesize that this is due to the competing depth effects on source asymmetry and the incorporation of depth in the Green’s functions used to calculate the seismic moment tensors. Importantly, this emphasizes that only seismic moment tensor-derived moments should be used in these models. After removing insignificant model parameters, we are left with a simple model to predict explosive yield $\widehat{W}$ in kt from isotropic moment M I in N·m, $\widehat{W}$=κ –1.4132 10 0.035626GP M I , in which κ and GP are the near-source bulk modulus and gas porosity in Pa and %, respectively. The F-value for this model is approximately 3.

58 GEOSCIENCES↗

End-Use Load Profiles for the U.S. Building Stock: Methodology and Results of Model Calibration, Validation, and Uncertainty Quantification

The United States is embarking on an ambitious transition to a 100% clean energy economy by 2050, which will require improving the flexibility of electric grids. One way to achieve grid flexibility is to shed or shift demand to align with changing grid needs. To facilitate this, it is critical to understand how and when energy is used. High- quality end-use load profiles (EULPs) provide this information, and can help cities, states, and utilities understand the time-sensitive value of energy efficiency, demand response, and distributed energy resources. Publicly available EULPs have traditionally had limited application because of age and incomplete geographic representation (Frick, Eckman, and Goldman 2017; Frick 2019). To help fill this gap, the U.S. Department of Energy (DOE) funded a three-year project - End-Use Load Profiles for the U.S. Building Stock - that culminated in the release of a publicly available dataset1 of simulated EULPs representing residential and commercial buildings across the contiguous United States. The motivation for this work is further detailed in a November 2019 report: Market Needs, Use Cases, and Data Gaps (Mims Frick et al. 2019). This Methodology and Results report provides detailed descriptions of how the dataset was developed, intended for an audience of dataset and model users interested in the technical details. These details include descriptions of all of the model improvements made for calibration and the final comparisons to empirical data sources. A companion report, End-Use Load Profiles for the U.S. Building Stock: Applications and Opportunities, will be published subsequently and will describe example applications and considerations for using the dataset, intended for an audience of general dataset users.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE COVID-19 Data Curation Effort: Overview of Initial Data Collection Coverage (March - June 2020)

During the COVID-19 pandemic of 2020, major case reporting outlets quickly coalesced around two or three primary vendors. Johns Hopkins University and The New York Times were among the more prominent, and all were of great value to the nation, particularly during the uncertain early stages of the pandemic. They primarily focused on three major attributes: number of new cases, deaths, and recovery, but only at the state level. Recognizing that many states were reporting very detailed data sets (e.g., hospital beds) at a count level or finer, the ORNL Pandemic Modeling team embarked on a major data curation effort from March to June 2020 for the purpose of capturing this wealth of detailed data. The challenge of curating this data was daunting. The number of attributes reported by the states grew on almost on a weekly basis. States were routinely shifting their web tool strategies away from easily parsable HTML-based formatting to new Tableau and ArcGIS content. This growth in the sheer number of attributes combined with the unpredictable shifts in data format meant an aggressive and agile combination of automated scripting and manual scraping was required to capture new daily streams. To keep up, the team had to scale up staff and widen its approach for capture and storage. The DOE COVID-19 data collection effort resulted in over 11 million data points being collected, covering over 13,000 unique geographies and over 2,000 unique attributes that spanned predominantly from early March through the end of June 2020.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Model-Form Epistemic Uncertainty Quantification for Modeling with Differential Equations: Application to Epidemiology

Modeling real-world phenomena to any degree of accuracy is a challenge that the scientific research community has navigated since its foundation. Lack of information and limited computational and observational resources necessitate modeling assumptions which, when invalid, lead to model-form error (MFE). The work reported herein explored a novel method to represent model-form uncertainty (MFU) that combines Bayesian statistics with the emerging field of universal differential equations (UDEs). The fundamental principle behind UDEs is simple: use known equational forms that govern a dynamical system when you have them; then incorporate data-driven approaches – in this case neural networks (NNs) – embedded within the governing equations to learn the interacting terms that were underrepresented. Utilizing epidemiology as our motivating exemplar, this report will highlight the challenges of modeling novel infectious diseases while introducing ways to incorporate NN approximations to MFE. Prior to embarking on a Bayesian calibration, we first explored methods to augment the standard (non-Bayesian) UDE training procedure to account for uncertainty and increase robustness of training. In addition, it is often the case that uncertainty in observations is significant; this may be due to randomness or lack of precision in the measurement process. This uncertainty typically manifests as “noisy” observations which deviate from a true underlying signal. To account for such variability, the NN approximation to MFE is endowed with a probabilistic representation and is updated using available observational data in a Bayesian framework. By representing the MFU explicitly and deploying an embedded, data-driven model, this approach enables an agile, expressive, and interpretable method for representing MFU. In this report we will provide evidence that Bayesian UDEs show promise as a novel framework for any science-based, data-driven MFU representation; while emphasizing that significant advances must be made in the calibration of Bayesian NNs to ensure a robust calibration procedure.

97 MATHEMATICS AND COMPUTING↗

DOE-NOAA Marine Cloud Brightening (Workshop Report 2022)

Marine Cloud Brightening (MCB) refers to the deliberate injection of aerosol particles into marine clouds to increase their reflection of solar radiation to temporarily cool the planet while decarbonization efforts are pursued. A workshop was conducted to assess the state of knowledge in the field of MCB, and to provide a possible research path toward reducing unknowns in key components of the underlying physical science. This three-day workshop took place in April 2022 and was jointly sponsored by Department of Energy (DOE)’s Atmospheric System Research (ASR) program and the National Oceanic and Atmospheric Administration (NOAA). The workshop focused on identifying key physical science knowledge gaps necessary to answer the following driving questions: 1) Is MCB feasible over sufficiently large regions and is implementation practicable for long-enough durations to avert the worst impacts of global warming? 2) If practicable, what will be the regional impacts of such MCB interventions? 3) Do we have adequate systems in place to detect and quantify the effects of such interventions? 4) What physical and engineering science challenges must be resolved satisfactorily before we can consider embarking on MCB?

54 ENVIRONMENTAL SCIENCES↗

DOE-NOAA Marine Cloud Brightening Workshop

Marine Cloud Brightening (MCB) refers to the deliberate injection of aerosol particles into marine clouds to increase their reflection of solar radiation to temporarily cool the planet while decarbonization efforts are pursued. A workshop was conducted to assess the state of knowledge in the field of MCB, and to provide a possible research path toward reducing unknowns in key components of the underlying physical science. This three-day workshop took place in April 2022 and was jointly sponsored by Department of Energy (DOE)’s Atmospheric System Research (ASR) program and the National Oceanic and Atmospheric Administration (NOAA). The workshop focused on identifying key physical science knowledge gaps necessary to answer the following driving questions: 1. Is MCB feasible over sufficiently large regions and is implementation practicable for long-enough durations to avert the worst impacts of global warming? 2. If practicable, what will be the regional impacts of such MCB interventions? 3. Do we have adequate systems in place to detect and quantify the effects of such interventions? 4. What physical and engineering science challenges must be resolved satisfactorily before we can consider embarking on MCB?

54 ENVIRONMENTAL SCIENCES↗

First Ever Field Pilot on Alaska's North Slope to Validate the Use of Polymer Floods for Heavy Oil EOR a.k.a Alaska North Slope Field Laboratory (ANSFL)

Alaska’s high viscosity oil resources that range between 20–30+ billion barrels represent about a third of known North Slope original oil in place (OOIP). These resources are primarily concentrated in the Schrader Bluff formation (also called West Sak on the Western North Slope) and Ugnu reservoirs and are categorized as “viscous oils” and “heavy oils” owing to their in-situ viscosities between 5–10,000 cP and up to a million+ cP respectively. The viscous oil deposits are relatively deeper (2,000 – 5,000 ft), whereas the heavy oils are somewhat shallower (2,000 – 4,000 ft). The typically shallow depths and the proximity to the continuous permafrost results in relatively lower formation temperatures and pressures, and consequently higher viscosities. The vertical depth vs. viscosity delineated in Paskvan et al. (2016) differentiates the viscous and heavy oils. As depicted in Paskvan et al. (2016), currently the main focus (referred to as “developing”) is on the viscous oils in the Schrader Bluff formation in the Milne Point Unit (MPU). Notwithstanding this Alaska North Slope (ANS) specific categorization, we use the industry adopted, all-inclusive term “heavy oil” for all high viscosity oils. Resource characterization and additional details can be found in topical publications of Paskvan et al. (2016) and Targac et al. (2005). Despite the vast resource base, the development pace, vis-à-vis the production of heavy oils has been very slow and limited due to multiple factors such as cost, logistics, challenging arctic environment, poor waterflood sweep efficiency due to mobility contrasts, and significantly high minimum miscibility pressures (MMP). Most importantly, typical or standard thermal methods that are commonplace elsewhere (Canada, California) are inapplicable due to the continuous permafrost. As a consequence, cumulative production of heavy and viscous oils is a little over 1% of OOIP slope wide and currently, there is hardly any production from Ugnu. However, on a broader level, these unfavorable factors are outweighed by the fact that (1) these resources, within the established infrastructure, are too large to ignore because of their strategic importance to the Nation and the State of Alaska and (2) Prudhoe Bay type diluent crude oil is still available for heavy oil transport through the Trans Alaska Pipeline System (TAPS). Similarly, from a reservoir standpoint, the following factors also are important offsets: (1) favorable rock characteristics of Schrader Bluff; (2) the promise demonstrated by the initial scoping studies (Seright 2010, 2011) suggesting significant increase of heavy oil recovery using polymer flooding; (3) successful field implementation in Canada, China and elsewhere in the world, and (4) availability of the existing pairs of horizontal injector-producer in Schrader Bluff The foregoing was recognized as the best readily available opportunity for significant investment by the US Department of Energy and the field operator Hilcorp Alaska LLC to conduct the first ever field scale experiment to test the polymer flooding technology to unlock the vast heavy oil resources on ANS. With this primary goal in mind, the research team embarked on a ~4.5 years long project that focused on the field polymer pilot complemented by supporting laboratory and simulation studies. As documented in this final report, over the course of the project, many lessons have been learned and valuable field and supporting laboratory data has been collected, which also is complemented by numerical reservoir simulations. We have been able to establish the injectivity of polymer solution, evidence of significant reduction in the water cut of previously waterflooded pattern, effective propagation of a hydrolyzed polyacrylamide (HPAM), benefits of low salinity water, provide practical guidance on handling of produced fluids containing breakthrough polymer, fit-for-purpose forecast-worthy history matched simulation model, polymer EOR benefit of 700-1000 bopd over waterflood, and most importantly a low polymer utilization factor of ~1.7 lb/stb. In summary this project is deemed as a scientific, technical and economic success, having met all objectives, fulfilled deliverables and within budget, providing impetus to apply polymer EOR throughout the Milne Point Field paving the way for even heavier viscosity oils in the Ugnu area, eventually extending the economic life of TAPS.

02 PETROLEUM↗

Experiences of Member States in Building a Nuclear Security Infrastructure for New Nuclear Power Programmes

A nuclear power programme has many benefits, but it is a major undertaking that requires careful planning and preparation as well as a substantial investment in time. It also necessitates the establishment of a sustainable national infrastructure with committed and sustained financial and human resources. While nuclear power is not unique in this respect, it is different from other sources of energy because of the risks associated with the use of nuclear material, as well as the need for compliance with international legal instruments, internationally accepted nuclear safety standards, nuclear security guidance, and safeguards requirements. The IAEA’s Milestones in the Development of a National Infrastructure for Nuclear Power, IAEA Nuclear Energy Series No. NG-G-3.1 (Rev. 1), defines a phased approach that identifies 19 infrastructure issues that should be addressed in each of the three phases of the development of a nuclear infrastructure for a nuclear power programme. The publication Evaluation of the Status of National Nuclear Infrastructure Development IAEA Nuclear Energy Series NG-T-3.2 (Rev. 2) provides a methodology to determine the status of the infrastructure conditions covering all 19 issues identified in the Milestones Approach. A companion IAEA Implementing Guide, Establishing the Nuclear Security Infrastructure for a Nuclear Power Programme, IAEA Nuclear Security Series No. 19, provides guidance on the recommended actions to be taken by a State to establish an effective national nuclear security infrastructure for a nuclear power programme using the Milestones Approach. This publication is intended to provide guidance based on the experiences and good practices of Member States with embarking nuclear power programmes as well as Member States that are expanding their nuclear power programmes. The guidance is in the form of case studies, which highlight challenges, issues, and solutions identified by Member States as lessons learned for new nuclear power programmes. This TECDOC is designed to present the experiences of Member States to assist other Member States in developing a nuclear security programme. It addresses the key actions necessary to establish an effective national nuclear security infrastructure for a nuclear power programme consistent with the three phases of the IAEA Milestones Approach. The Member States that provided case studies in this document are at different stages in the development of a nuclear power programme.

42 ENGINEERING↗

Light Dark Matter (e)xperiment

In this presentation, I write on the process and procedures I have embarked on during this internship. This talks on what the experiment is for, how to conduct it, and the acclamation to tools used for data analysis in this research.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗