Dynamic Structure Discovery and Ion Transport in Liquid Battery Electrolytes

The lithium-ion battery (LIB), the realisation of which earned the Nobel Prize in Chemistry 2019, has since its 1991 commercialisation become the dominant energy storage technology first for cell phones and other mobile electronics, then for power tools and other domestic appliances, and currently for electric cars and other vehicles. However, many applications would still benefit from higher power and energy densities, longer life-lengths and safer batteries. Such improvements would for example accelerate the electrification of transport, lower the pollution and the greenhouse gas emissions. Electrolytes are extremely crucial for the operation of the LIBs, yet they have so far changed surprisingly little the last 25 years. Further improvement can be made by novel electrolyte concepts. Highly concentrated electrolytes (HCEs) may enable higher energy and power densities, as well as improved thermal, chemical and electrochemical stabilities as compared to the current state-of-the-art, while also being more flexible in their composition. They also have more complex structures and ion transport mechanisms. I here present a novel method for studying both more standard electrolytes and HCEs by analysing molecular dynamics simulation trajectories. This method automatically detects the time-dependent structures present and characterises them by statistical physics, giving an extraordinarily detailed view of the structure and dynamics. I describe the theory and implementation of this method as well as its application to several HCEs and the ubiquitous LP30 electrolyte. These studies enhance the picture of ion transport conveyed previously and future application should add substantially to the design of battery electrolytes and beyond.The lithium-ion battery (LIB), the realisation of which earned the Nobel Prize in Chemistry 2019, has since its 1991 commercialisation become the dominant energy storage technology first for cell phones and other mobile electronics, then for power tools and other domestic appliances, and currently for electric cars and other vehicles. However, many applications would still benefit from higher power and energy densities, longer life-lengths and safer batteries. Such improvements would for example accelerate the electrification of transport, lower the pollution and the greenhouse gas emissions. Electrolytes are extremely crucial for the operation of the LIBs, yet they have so far changed surprisingly little the last 25 years. Further improvement can be made by novel electrolyte concepts. Highly concentrated electrolytes (HCEs) may enable higher energy and power densities, as well as improved thermal, chemical and electrochemical stabilities as compared to the current state-of-the-art, while also being more flexible in their composition. They also have more complex structures and ion transport mechanisms. I here present a novel method for studying both more standard electrolytes and HCEs by analysing molecular dynamics simulation trajectories. This method automatically detects the time-dependent structures present and characterises them by statistical physics, giving an extraordinarily detailed view of the structure and dynamics. I describe the theory and implementation of this method as well as its application to several HCEs and the ubiquitous LP30 electrolyte. These studies enhance the picture of ion transport conveyed previously and future application should add substantially to the design of battery electrolytes and beyond

A Smooth Binary Mechanism for Efficient Private Continual Observation

In privacy under continual observation we study how to release differentially private estimates based on a dataset that evolves over time. The problem of releasing private prefix sums of $x_1,x_2,x_3,\dots \in\{0,1\}$ (where the value of each $x_i$ is to be private) is particularly well-studied, and a generalized form is used in state-of-the-art methods for private stochastic gradient descent (SGD). The seminal binary mechanism privately releases the first $t$ prefix sums with noise of variance polylogarithmic in $t$. Recently, Henzinger et al. and Denisov et al. showed that it is possible to improve on the binary mechanism in two ways: The variance of the noise can be reduced by a (large) constant factor, and also made more even across time steps. However, their algorithms for generating the noise distribution are not as efficient as one would like in terms of computation time and (in particular) space. We address the efficiency problem by presenting a simple alternative to the binary mechanism in which 1) generating the noise takes constant average time per value, 2) the variance is reduced by a factor about 4 compared to the binary mechanism, and 3) the noise distribution at each step is identical. Empirically, a simple Python implementation of our approach outperforms the running time of the approach of Henzinger et al., as well as an attempt to improve their algorithm using high-performance algorithms for multiplication with Toeplitz matrices.Comment: Appeared at NeurIPS 202

Dynamic Structure Discovery Applied to the Ion Transport in the Ubiquitous Lithium-ion Battery Electrolyte LP30

The electrolytes of the today omnipresent lithium-ion batteries (LIBs) have for more than 25 years been based upon 1 M LiPF6 in a 50:50 EC:DMC mixture-commonly known as LP30. The success of the basic design of the LP30 electrolyte, with many variations and additions made over the years, is unchallenged. Yet, some molecular level fundamentals of LP30 are surprisingly elusive: the structure of the first solvation shell of the Li+ cation is still a topic of current debate; the details of the dynamics are not fully understood; the interpretation of structural and dynamic properties is highly dependent on the analysis methods used; the contributions by different species to the ion transport and the energetics involved are not established. We here apply dynamic structure discovery analysis as implemented in CHAMPION to molecular dynamics simulation trajectories to bring new light on the structure and dynamics within LP30 and especially the (Li+) ion transport to rationalize further development of LIB electrolytes

Klimatoptimal biogasanvändning i Trelleborgs kommun

Att minska energiförbrukningens klimatpåverkan handlar om att göra energieffektiviseringar och att ersätta fossil energi med icke-fossil. Olika icke-fossila energilösningar ger olika klimatpåverkan sett ur ett livscykelperspektiv, och därför är valet av icke-fossila energilösningar av betydelse för klimatet. Biogas kan användas både för värme- och elproduktion samt som drivmedel. Detta examensarbete är en utredning av vilken användning av biogas som ur klimatperspektiv bör prioriteras i området Trelleborgs kommun. De användningsområden som jämförs är värme och drivmedel. Användning av biogas för elproduktion har inte beaktats eftersom det finns god tillgång till fossilfri el i Sverige och att fossilfri elförbrukning kan uppnås genom att teckna ett fossilfritt elavtal. I studien har klimatnyttan av biogas jämförts med klimatnyttan av andra etablerade icke-fossila alternativ inom både värme och drivmedel. Om andra alternativ ger större klimatnytta än biogas inom ett användningsområde bör dessa alternativ prioriteras för att optimera klimatnyttan i energisystemet. Klimatpåverkan från de icke-fossila alternativen har beräknats baserat på indata från befintliga livscykelanalyser. Beräkningarna har skett med hänsyn till lokala förutsättningar, såsom vilka råvaror som bör användas och vilken typ av mark som odling av energigrödor bör ske på. Klimatnyttan med varje icke-fossilt alternativ har beräknats som den utsläppsreduktion (i %) som uppstår när alternativet ersätter de fossila bränslen som används i Trelleborg. Studiens antaganden kring t ex råvaror för bränsle- och värmeproduktion utgår från bl a statistik och potentialutredningar, vilket gör att beräkningarna medför osäkerheter. Därför har resultat beräknats både för olika basfall och med känslighetsanalyser där antaganden och förutsättningar för beräkningarna varierats, vilket visar hur resultaten skulle kunna variera. På drivmedelssidan har resultaten visat att biogas ger störst klimatnytta av de undersöka drivmedlen. Om biogasen produceras av minst 50 % restprodukter (vilket är de klimatmässigt bästa råvarorna) ger biogasen den största utsläppsreduktionen. Biogas är också det enda drivmedlet som uppnår över 90 % utsläppsreduktion. Känslighetsanalyserna visar att de andra icke-fossila drivmedelsalternativen endast kan uppnå 90 % utsläppsreduktion om klimatmässigt mycket optimistiska förutsättningar antas, sett till hur dagens produktionssystem ser ut. På värmesidan har resultaten visat att det finns ett flertal icke-fossila alternativ som ger över 90 % utsläppsreduktion. Biogas är inte det bästa värmealternativet även vid en råvarutillförsel med endast restprodukter. Känslighetsanalyser visar dock att biogas kan vara det bästa alternativet om man antar att biogasen inte uppgraderas. Uppgradering av biogas är inte nödvändigt om den ska användas för värme lokalt eller via ett nät endast för biogas. Samtidigt visar känslighetsanalyserna att de övriga alternativen med hög klimatnytta håller sig kvar på över 90 % utsläppsreduktion även om man antar klimatmässigt sämre förutsättningar. De visar även att biogas med uppgradering, oavsett råvarumix, inte är det bästa alternativet även om klimatmässigt sämre förutsättningar antas för övriga alternativ. Slutsatsen är att biogas ur klimatsynpunkt bör användas som drivmedel i Trelleborgs kommun. Anledningen är dels att biogas är det drivmedel som ger bäst klimatnytta och att övriga drivmedel inte uppnår ”likvärdig” klimatnytta eller över 90 % utsläppsreduktion, dels att det för värme finns ett flertal ”likvärdiga” alternativ (med över 90 % utsläppsreduktion), eller t o m bättre alternativ beroende på vilka förutsättningar som antas för biogasproduktionen.Reducing climate impact from energy consumption is a matter of improving energy efficiency and replacing fossil energy with non-fossil. Different non-fossil energy alternatives cause different climate impact in a life-cycle perspective and, therefore, the choices between non-fossil energy alternatives have an impact on the climate performance. Biogas can be used for both heat- and electricity production and as a vehicle fuel. This master thesis is an investigation about which type of biogas use in the area of Trelleborg municipality that is preferable in a climate perspective, in which the usage of biogas for heat production and vehicle fuel is compared. Usage of biogas for electricity production has not been included in the study since there is a large supply of non-fossil electricity in Sweden and that non-fossil electricity consumption can be obtained through signing a non-fossil electricity contract. In this study, the climate benefit of biogas has been compared to the climate benefit of other established non-fossil alternatives within both heat production and vehicle fuels. If other alternatives give higher climate benefit than biogas within one type of usage, these alternatives should be prioritized to minimize the climate impact of the energy system. The climate impact of the non-fossil alternatives has been calculated based on existing life cycle assessments. The calculations have been made with respect to local conditions, such as which raw materials that are likely to be used and what type of land that is used for cultivation of energy crops. The climate impact of the non-fossil alternatives has been calculated as the emission reduction (in %) that occurs when the alternative replaces the fossil fuels that are used in Trelleborg. The assumptions of the study considering e g biomass resources for fuel- and heat production are based on e g statistics and production potential investigations, which means that the calculations include different uncertainties. Therefore, results have been calculated both in base-cases and sensitivity analyses, where assumptions and conditions for the calculations have been varied, which displays how the results could vary. For replacing fossil vehicle fuels, the results show that biogas give the highest climate benefit. If the biogas is produced from at least 50% residues (which gives the lowest climate impact), the biogas gives the highest emission reduction. Biogas is also the only vehicle fuel that reaches over 90% emission reduction. The sensitivity analyses show that the other vehicle fuel alternatives can reach 90% emission reduction only if very optimistic conditions are assumed, compared to how today’s productions systems are designed. For heat production, the results show that there are several non-fossil alternatives that give over 90% emission reductions. Biogas is not the best heat production alternative even assuming a raw material supply of 100% residues. The sensitivity analyses show, however, that biogas can be the best alternative assuming biogas without upgrading. Upgrading of biogas is not necessary for heat production locally or with distribution through a network only for biogas. At the same time, the sensitivity analyses show that several other alternatives still have over 90% emission reduction when assuming less optimal conditions from a climate perspective. Upgraded biogas is, regardless of the raw material supply, not the best alternative even if less optimal conditions from a climate perspective are assumed for the other alternatives. The conclusion is that biogas, from a climate perspective, should be used as a vehicle fuel in Trelleborg municipality. The reason is that biogas shows the best performance and that the other non-fossil fuels do not reach the same climate benefit (or over 90% emission reduction) and that there for heat production are several comparable alternatives (with over 90% emission reduction) or even better alternatives, depending on which conditions that are assumed for the biogas production

Novel Multi-Scale Modeling Framework for Structure and Transport in Complex Battery Electrolytes

Affordable high energy rechargeable batteries are crucial for further electrification of the transport sector, which is necessary in order to contribute to limit our CO2 emissions to acceptable levels. While today’s lithium-ion batteries (LIBs) have indeed initiated the electrification of the transportation section successfully, electric vehicles are still expensive and typically have ranges limited to ca. 100-500 km depending on price class. There are also safety concerns with LIBs and limited abundance of necessary materials why new chemistries, and especially new electrolytes, need to be explored. Emerging classes of electrolytes, such as highly concentrated electrolytes, have more complex structures than conventional electrolytes, with implications for the ion transport mechanism. This complexity necessitates a multi-scale modeling approach starting at the atomic level to gain further fundamental understanding. This thesis outlines a framework where ab initio molecular dynamics initially is used to simulate small periodic systems (∼100 - 1000 atoms) over relatively short time spans (∼1 ps) to obtain trajectories that subsequently are used to train the parameters of a classical force field by force matching. This optimization is performed over all parameters simultaneously by a genetic algorithm. The force fields developed are then used to simulate larger systems (∼1000 - 100 000 atoms) over longer time scales classically (∼1 ns - 1μs). The resulting trajectories are used to collect statistics for a hierarchical analysis, which resolves the structure in terms of dynamic clusters, and quantifies the life-time distribution, population dynamics, and transport properties of identified clusters and non-covalent bonds. The method is ultimately to be of general use to both qualitatively and quantitatively elucidate the ion transport mechanism in novel types of electrolytes as a function of composition

Global and Local Structure of Lithium Battery Electrolytes: Origin and Onset of Highly Concentrated Electrolyte Behavior

Highly concentrated electrolytes (HCEs), created simply by increasing the lithium salt concentration from the conventional 1 M to 3-5 M, have been suggested as a path towards safer and more stable lithium batteries. Their higher thermal and electrochemical stabilities and lower volatilities are usually attributed to the unique solvation structure of HCEs with not enough solvent available to fully solvate the Li+ ions—but much remains to be understood. Here the structural features that characterize the behavior of electrolytes in general and HCEs in particular, and especially the transition from conventional to highly concentrated behavior, are reported for lithium bis(trifluoromethanesulfonyl)imide (LiTFSI) in acetonitrile (ACN), a common HCE system. We analyze four different salt concentrations using ab initio molecular dynamics (AIMD) and the CHAMPION software, to obtain trends in global and local structure, as well as configurational entropy, to elucidate what truly sets apart the highly concentrated regime

Ion Transport Mechanisms via Time-Dependent Local Structure and Dynamics in Highly Concentrated Electrolytes

Highly concentrated electrolytes (HCEs) are attracting interest as safer and more stable alternatives to current lithium-ion battery electrolytes, but their structure, solvation dynamics and ion transport mechanisms are arguably more complex. We here present a novel general method for analyzing both the structure and the dynamics, and ultimately the ion transport mechanism(s), of electrolytes including HCEs. This is based on automated detection of bonds, both covalent and coordination bonds, including how they dynamically change, in molecular dynamics (MD) simulation trajectories. We thereafter classify distinct local structures by their bond topology and characterize their physicochemical properties by statistical mechanics, giving both a qualitative and quantitative description of the structure, solvation and coordination dynamics, and ion transport mechanism(s). We demonstrate the method by in detail analyzing an ab initio MD simulation trajectory of an HCE consisting of the LiTFSI salt dissolved in acetonitrile at a 1:2 molar ratio. We find this electrolyte to form a flexible percolating network which limits vehicular ion transport but enables the Li+\ua0ions to move between different TFSI coordination sites along with their first solvation shells. In contrast, the TFSI anions are immobilized in the network, but often free to rotate which further facilitates the Li+\ua0hopping mechanism.Highly concentrated electrolytes (HCEs) are attracting interest as safer and more stable alternatives to current lithium-ion battery electrolytes, but their structure, solvation dynamics and ion transport mechanisms are arguably more complex. We here present a novel general method for analyzing both the structure and the dynamics, and ultimately the ion transport mechanism(s), of electrolytes including HCEs. This is based on automated detection of bonds, both covalent and coordination bonds, including how they dynamically change, in molecular dynamics (MD) simulation trajectories. We thereafter classify distinct local structures by their bond topology and characterize their physicochemical properties by statistical mechanics, giving both a qualitative and quantitative description of the structure, solvation and coordination dynamics, and ion transport mechanism(s). We demonstrate the method by in detail analyzing an ab initio MD simulation trajectory of an HCE consisting of the LiTFSI salt dissolved in acetonitrile at a 1:2 molar ratio. We find this electrolyte to form a flexible percolating network which limits vehicular ion transport but enables the Li+\ua0ions to move between different TFSI coordination sites along with their first solvation shells. In contrast, the TFSI anions are immobilized in the network, but often free to rotate which further facilitates the Li+\ua0hopping mechanism.Highly concentrated electrolytes (HCEs) are attracting interest as safer and more stable alternatives to current lithium-ion battery electrolytes, but their structure, solvation dynamics and ion transport mechanisms are arguably more complex. We here present a novel general method for analyzing both the structure and the dynamics, and ultimately the ion transport mechanism(s), of electrolytes including HCEs. This is based on automated detection of bonds, both covalent and coordination bonds, including how they dynamically change, in molecular dynamics (MD) simulation trajectories. We thereafter classify distinct local structures by their bond topology and characterize their physicochemical properties by statistical mechanics, giving both a qualitative and quantitative description of the structure, solvation and coordination dynamics, and ion transport mechanism(s). We demonstrate the method by in detail analyzing an ab initio MD simulation trajectory of an HCE consisting of the LiTFSI salt dissolved in acetonitrile at a 1:2 molar ratio. We find this electrolyte to form a flexible percolating network which limits vehicular ion transport but enables the Li+\ua0ions to move between different TFSI coordination sites along with their first solvation shells. In contrast, the TFSI anions are immobilized in the network, but often free to rotate which further facilitates the Li+\ua0hopping mechanism

CHAMPION: Chalmers hierarchical atomic, molecular, polymeric and ionic analysis toolkit

We present CHAMPION (Chalmers hierarchical atomic, molecular, polymeric, and ionic analysis toolkit): a software developed to automatically detect time-dependent bonds between atoms based on their dynamics, classify the local graph topology around them, and analyze the physicochemical properties of these topologies by statistical physics. In stark contrast to methodologies where bonds are detected based on static conditions such as cut-off distances, CHAMPION considers pairs of atoms to be bound only if they move together and act as a bound pair over time. Furthermore, the time-dependent global bond graph is possible to split into dynamically shifting connected components or subgraphs around a certain chemical motif and thereby allow the physicochemical properties of each such topology to be analyzed by statistical physics. Applicable to condensed matter and liquids in general, and electrolytes in particular, this allows both quantitative and qualitative descriptions of local structure, as well as dynamical processes such as speciation and diffusion. We present here a detailed overview of CHAMPION, including its underlying methodology, implementation, and capabilities