556 research outputs found
Constructive Preference Elicitation over Hybrid Combinatorial Spaces
Preference elicitation is the task of suggesting a highly preferred
configuration to a decision maker. The preferences are typically learned by
querying the user for choice feedback over pairs or sets of objects. In its
constructive variant, new objects are synthesized "from scratch" by maximizing
an estimate of the user utility over a combinatorial (possibly infinite) space
of candidates. In the constructive setting, most existing elicitation
techniques fail because they rely on exhaustive enumeration of the candidates.
A previous solution explicitly designed for constructive tasks comes with no
formal performance guarantees, and can be very expensive in (or unapplicable
to) problems with non-Boolean attributes. We propose the Choice Perceptron, a
Perceptron-like algorithm for learning user preferences from set-wise choice
feedback over constructive domains and hybrid Boolean-numeric feature spaces.
We provide a theoretical analysis on the attained regret that holds for a large
class of query selection strategies, and devise a heuristic strategy that aims
at optimizing the regret in practice. Finally, we demonstrate its effectiveness
by empirical evaluation against existing competitors on constructive scenarios
of increasing complexity.Comment: AAAI 2018, computing methodologies, machine learning, learning
paradigms, supervised learning, structured output
Decomposition Strategies for Constructive Preference Elicitation
We tackle the problem of constructive preference elicitation, that is the
problem of learning user preferences over very large decision problems,
involving a combinatorial space of possible outcomes. In this setting, the
suggested configuration is synthesized on-the-fly by solving a constrained
optimization problem, while the preferences are learned itera tively by
interacting with the user. Previous work has shown that Coactive Learning is a
suitable method for learning user preferences in constructive scenarios. In
Coactive Learning the user provides feedback to the algorithm in the form of an
improvement to a suggested configuration. When the problem involves many
decision variables and constraints, this type of interaction poses a
significant cognitive burden on the user. We propose a decomposition technique
for large preference-based decision problems relying exclusively on inference
and feedback over partial configurations. This has the clear advantage of
drastically reducing the user cognitive load. Additionally, part-wise inference
can be (up to exponentially) less computationally demanding than inference over
full configurations. We discuss the theoretical implications of working with
parts and present promising empirical results on one synthetic and two
realistic constructive problems.Comment: Accepted at the Thirty-Second AAAI Conference on Artificial
Intelligence (AAAI-18
Density Functional Theory screening of gas-treatment strategies for stabilization of high energy-density lithium metal anodes
To explore the potential of molecular gas treatment of freshly cut lithium
foils in non-electrolyte based passivation of high energy-density Li anodes,
density functional theory (DFT) has been used to study the decomposition of
molecular gases on metallic lithium surfaces. By combining DFT geometry
optimization and Molecular Dynamics, the effects of atmospheric (N2, O2, CO2)
and hazardous (F2, SO2) gas decomposition on Li(bcc) (100), (110), and (111)
surfaces on relative surface energies, work functions, and emerging electronic
and elastic properties are investigated. The simulations suggest that exposure
to different molecular gases can be used to induce and control reconstructions
of the metal Li surface and substantial changes (up to over 1 eV) in the work
function of the passivated system. Contrary to the other considered gases,
which form metallic adlayers, SO2 treatment emerges as the most effective in
creating an insulating passivation layer for dosages <= 1 mono-layer. The
substantial Li->adsorbate charge transfer and adlayer relaxation produce marked
elastic stiffening of the interface, with the smallest change shown by
nitrogen-treated adlayers
Assessing n‐type organic materials for lithium batteries: A techno‐economic review
The high demand for critical minerals such as lithium, copper, nickel, and cobalt, required for lithium-ion batteries, has raised questions regarding the feasibility of maintaining a steady and affordable supply of raw materials for their production. In the last years, researchers have shifted their attention toward organic materials, which are potentially more widely available, affordable, and sustainable due to the ubiquitous presence of the constituent organic elements. The n-type materials have a redox mechanism analogous to that of lithium-ion cathodes and anodes, hence they are suitable for a meaningful comparison with the state-of-the-art technology. While many reviews have evaluated the properties of organic materials at the material or electrode level, herein, the properties of n-type organic materials are assessed in a complex system, such as a full battery, to evaluate the feasibility and performance of these materials in commercial-scale battery systems. The most relevant cathode materials for organic batteries are reviewed, and a detailed cost and performance analysis of n-type material-based battery packs using the BatPaC 5.0 software is presented. The analysis considers the influence of electrode design choices, such as the conductive carbon content, active material mass loading, and electrode density, on energy density and cost. The potential of n-type organic materials as a low-cost and sustainable solution for energy storage applications is highlighted, while emphasizing the need for further advancements of organic materials for energy storage applications
ZnO-Based Conversion/Alloying Negative Electrodes for Lithium-Ion Batteries: Impact of Mixing Intimacy
Conversion/alloying materials, such as transition metal (TM)‐doped ZnO, are showing superior performance over pure ZnO due to the presence of the TM, enabling the reversible formation of LiO due to the enhanced electronic conductivity within the single particle once being reduced to the metallic state upon lithiation. Herein, the impact of introducing Co as representative TM at the atomic level in ZnO compared with mixtures of nano‐ and microsized CoO and ZnO is investigated. While even rather simple mixtures provide higher capacities than pure ZnO, an intimate mixing of nanoparticulate CoO and ZnO leads to a further increase due to the more homogeneous dispersion of Co. Nonetheless, the “atomic mixing” via doping still provides the highest capacities—for both nano‐ and microparticles, thus highlighting the importance of the very fine distribution of Co (and generally the TM) for realizing effective electron conduction pathways to enable the reversible formation of LiO
Optical and chemical properties of molten salt mixtures for use in high temperature power systems
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Nuclear Science and Engineering, 2010.Cataloged from PDF version of thesis.Includes bibliographical references (p. 92-94).A future, robust energy portfolio will include, together with fossil fuel technologies and nuclear systems, a mix of renewable energy systems. Within each type of system there will also be variants used to strengthen a nation's baseload and/or peak power requirements. Among renewable energies, solar thermal systems are particularly promising in terms of their capability of contributing to the base-load power generation by providing enough thermal storage for continuous operation. In particular, direct volumetric absorption of the solar heat into molten salts seems to be a promising technology, in terms of efficiency and greenhouse gases emission reduction, which combines the good properties of molten salts as heat storage media with high operating temperatures. Accordingly, the selection of molten salts for this application required knowledge of the salts chemical behavior as well as optical properties. The molten salt selection and characterization was the objective of this Thesis. The light attenuation coefficient of two reagent grade molten salt mixtures (KNO 3 - NaNO 3, 40- 60 wt% and NaCI-KCI, 50-50 wt%) was measured and characterized over the wavelength range 400nm- 800nm and for different operating temperature ranges: 250*C-5000C for the nitrate mixture and 700*C- 8000C for the chloride mixture. The measurements were performed using a unique custom built experimental apparatus based on the transmission technique which combines high accuracy and flexibility in terms of experimental conditions and temperatures with simple layout, use of common lab materials and low cost. The experimental apparatus was validated using published data for both a room temperature fluid (water) as well as a high temperature fluid (a nitrate/nitrate mixture presenting a well known absorption edge shifting with temperature). No previous experimental works characterized molten salts in terms of light attenuation coefficient as a function of temperature and wavelength and under this point of view the obtained results represent unique and direct optical measurement for such a class of fluids. Furthermore, the obtained results are coherent to general theory on molten salts, described as semi-transparent liquids in the visible range and characterized by absorption edges in the ultra-violet and far-infrared regions. About 90% of the solar light emitted in the wavelength range 400nm-800nm is attenuated by 2m of nitrate salt, while about 80% of the solar light emitted in the wavelength range 400nm-800nm is attenuated by 2m of chloride salt. In addition, the chemical stability and material compatibility of molten salt mixtures (including nitrate/nitrite, chloride and carbonate salt mixtures) with common materials of interests were assessed partially through dedicated material compatibility tests and more extensively using a thermodynamic chemistry software, able to predict the equilibrium composition of systems of specified composition at different temperatures. The preliminary melting and material compatibility tests resulted in some of the previously identified salt mixture candidates to be discarded because of undesirable reactions with structural materials or air that made them not suitable for the CSPonD design project.by Stefano Passerini.S.M
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