Cyber-Physical Environment to Evaluate Blended Attack Exercises
Explore the source record for details and available documents.
Rowland, Michael Terence↗
SEARCH · Engineering Papers
Results for “blended attack”
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Implementing an Information Security Program
The threats to information security have dramatically increased with the proliferation of information systems and the internet. Chemical, biological, radiological, nuclear, and explosives (CBRNe) facilities need to address these threats in order to protect themselves from the loss of intellectual property, theft of valuable or hazardous materials, and sabotage. Project 19 of the European Union CBRN Risk Mitigation Centres of Excellence Initiative is designed to help CBRN security managers, information technology/cybersecurity managers, and other decision-makers deal with these threats through the application of cost-effective information security programs. Project 19 has developed three guidance documents that are publically available to cover information security best practices, planning for an information security management system, and implementing security controls for information security.
blended attack↗
Refinement of Salt Dissolution Inhibitor Requirements (Final Report)
At Savannah River Site (SRS), High-Level Waste is stored in below-grade carbon steel tanks. This waste in part consists of sludge, salt cake, and/or supernate. Preparation of this waste for future processing involves dissolution of the salt cake layer. The salt dissolution process can create conditions that leave the carbon steel tanks susceptible to localized corrosion. The salt to be dissolved contains high concentrations of nitrate, that once released, create an environment that may be conducive to pitting corrosion and/or stress corrosion cracking (SCC) of carbon steel. The salt dissolution process also liberates interstitial liquid trapped between the salt crystals. This liquid is initially high in nitrite and hydroxide concentration. High pH and greater ratios of nitrite to nitrate act as inhibitors to minimize corrosion of carbon steel in high nitrate environments. However, as dissolution proceeds, the concentration of nitrate will increase, while the hydroxide and nitrite concentration of the interstitial liquid will deplete and become insufficient to prevent the onset of corrosion attack. Tank blending and addition of inhibitors are used to ensure adequate concentrations of hydroxide and nitrite. However, this is not desirable during salt dissolution as it can reduce process efficiency and increase the amount of waste that needs processing. It has been proposed that these corrosion control limits be revisited to evaluate the corrosion susceptibility of carbon steel in environments that more closely resemble current operating conditions at SRS. An experimental matrix was designed to evaluate the use of the pitting factor for supernate chemistries characteristic to SRS, particularly during the salt dissolution process. Two electrochemical methods were identified to determine the susceptibility of A537 and A285 low-carbon steels to pitting corrosion with this chemistry envelope at temperatures up to 75 °C. The predominant electrochemical test method was Cyclic Potentiodynamic Polarization (CPP) studies. Through CPP, the pitting factor was used, based on Hanford Site corrosion studies, to accurately identify pitting susceptibility within the compositional range studied with some conservatism. Additionally, sulfate was determined to have no statistically significant influence, at concentrations up to 0.6 M, on pitting behavior in more concentrated solutions where other aggressive species govern pitting susceptibility. Where CPP was inconclusive, Modified ASTM G192 was successfully used to evaluate pitting susceptibility conditions and allowed for a pass/fail result to be determined. In all cases, the pitting factor was determined to be applicable to the simulants tested, with this metric accurately predicting incidences in which pitting occurred. Based upon the findings in this work, a pitting factor of 1.2 is being proposed to build in a safety factor and remain consistent with the Hanford Site approach. Additionally, a minimum pH limit of 12 is proposed to ensure carbon steel passivity and localized corrosion the primary degradation mechanism. Susceptibility to SCC was evaluated using a reduced matrix of tests at 75 °C. No failures due SCC were observed at open circuit. In addition, tests polarized anodically by 200 mV only resulted in failures for trials with pitting factors less than 0.86. However, a test with a passing condition based upon the pitting factor metric (pitting factor = 1.40) did exhibit a failure with an applied potential of +300 mV vs. OCP. This result is contrary to the prediction based upon the pitting factor, however, a polarization of 300 mV, or even 200 mV, from open circuit is substantial. The relationship between these testing parameters and service environment/conditions and the desired level of conservatism in the metric should be further evaluated in the determination of the significance of this result. While the pitting factor accurately predicted susceptibility to SCC at temperatures up to 75 °C and with positive overpotentials up to 200 mV, the relatively small sample matrix and failure of a passing pitting factor with a 300 mV polarization resulted in an inconclusive determination of whether the pitting factor may be used for predicting susceptibility to SCC at temperatures between 50 °C and 75 °C. As such, additional testing is recommended to evaluate the validity of the pitting factor for SCC susceptibility prediction at temperatures between 50 °C and 75 °C.
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
Slow Strain Rate Testing of A537 Tank Wall Material
At Savannah River Site (SRS), High-Level Waste is stored in below-grade carbon steel tanks. This waste in part consists of sludge, salt cake, and/or supernate. Preparation of this waste for future processing involves dissolution of the salt cake layer. The salt dissolution process can create conditions that leave the carbon steel tanks susceptible to localized corrosion. The salt to be dissolved contains high concentrations of nitrate, that once released, create an environment that may be conducive to pitting corrosion and/or stress corrosion cracking (SCC) of carbon steel. The salt dissolution process also liberates interstitial liquid trapped between the salt crystals. This liquid is initially high in nitrite and hydroxide concentration. High pH and greater ratios of nitrite to nitrate act as inhibitors to minimize corrosion of carbon steel in high nitrate environments. However, as dissolution proceeds, the concentration of nitrate will increase, while the hydroxide and nitrite concentration of the interstitial liquid will deplete and become insufficient to prevent the onset of corrosion attack. Tank blending and the addition of inhibitors are used to ensure adequate concentrations of hydroxide and nitrite. However, this is not desirable during salt dissolution as it can reduce process efficiency and increase the amount of waste that needs processing. This testing program was designed to examine the risk of SCC associated with utilizing the pitting factor (PF) and nitrite/nitrate (NO 2 - /NO 3 - ) ratio limits for handling dissolved salt solutions at an elevated temperature in the carbon steel waste tanks. The previously identified limits are a PF of 1.2 and an NO 2 - /NO 3 - ratio of 0.15. The results indicate that as long as the NO 2 - /NO 3 - ratio exceeds 0.1 and the PF is above approximately 0.8, there is a discernible safety margin between the open circuit potential (OCP) and the critical cracking potential (CCP) observed during applied potential testing. However, this margin, defined by the difference between the OCP and CCP, is relatively narrow, ranging from 0.1 to 0.25 volts. This small margin raises concerns about potential shifts in OCP during waste retrieval operations, which could inadvertently increase the risk of SCC if the OCP approaches or exceeds the CCP. These results confirm that dissolved salt solutions provide a potent chemistry that, under certain conditions, makes carbon steel susceptible to SCC. The next question to consider is the influence these results have on decisions for storage and retrieval of waste from the tanks. For Type III/IIIA waste tanks, the risk of SCC remains very low. First, and most importantly, the post-weld stress relief of the tanks has reduced the residual stress near the welds. Thus, without the stress component, SCC risk is minimized. The material of construction (A537 Carbon steel) for the Type III/IIIA tanks is superior to the steel in its resistance to SCC than the steel that was utilized for the Type I, II, and IV tanks (A285 carbon steel). From a chemistry control standpoint for a Type III/IIIA tank directly involved with handling dissolved salt solutions, the PF and NO 2 - /NO 3 - ratio limits may be utilized wherein chemistry control provides an extra layer of defense against SCC. Chemistry control for a Type III/IIIA tank minimizes the risk for a tank that may receive the dissolved salt solution, particularly if that tank is a Type I, II, or IV waste tank. On the other hand, if the dissolved salt solution is handled by a Type I, II, or IV waste tank the risk of SCC is real. The potent chemistry, absence of stress relief, and inferior material result in a condition that is conducive to cracking. Efforts should be made to either avoid transferring waste that may not meet the PF and NO 2 - /NO 3 - ratio criteria to one of these tanks or if it is unavoidable, take measures to minimize the consequences of a leak. As shown by these tests, even if the PF and NO 2 - /NO 3 - ratio criteria are met, there is a risk that the tank potential may be disturbed in the positive direction and the risk of SCC increase.
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
Refinement of Salt Dissolution Inhibitor Requirements (Interim Report)
At Savannah River Site, High-Level Waste is stored in below-grade carbon steel tanks. This waste in part consists of sludge, salt cake, and/or supernate. Preparation of this waste for future processing involves dissolution of the salt cake layer. The salt dissolution process can create conditions that leave the carbon steel tanks susceptible to localized corrosion. The salt to be dissolved contains high concentrations of nitrate, that once released, create an environment that may be conducive to pitting corrosion or stress corrosion cracking (SCC) of carbon steel. The salt dissolution process also liberates interstitial liquid trapped between the salt crystals. This liquid is initially high in nitrite and hydroxide concentration. High pH and greater ratios of nitrite to nitrate act as inhibitors to minimize corrosion of carbon steel in high nitrate environments. However, as dissolution proceeds, the concentration of nitrate increases while the hydroxide and nitrite concentration of the interstitial liquid depletes and becomes insufficient to prevent the onset of corrosion attack. While tank blending and the addition of inhibitors are used to ensure adequate concentrations of hydroxide and nitrite during normal operation, this is not desirable during salt dissolution as it can reduce process efficiency and increase the amount of waste that needs processed.
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
Degradation mechanism of blended cement pastes in sulfate-bearing environments under applied electric fields: Sulfate attack vs. decalcification
Applied electric fields, the reason behind stray currents, accelerate the ingress of sulfate into cementitious materials. To identify mitigation approaches, this study investigates the effects of slag and fly ash on sodium sulfate attacks of cement pastes under a constant electric current. The mineralogical alterations induced by the attacks were analyzed using X-ray diffractometry, thermogravimetric analysis, scanning electron microscopy, and thermodynamic modeling. The dissolution of aluminates in the slag and fly ash induced a monosulfate-rich area (>~20 mm from the cathode surface) to form next to the ettringite-rich area on the sample surface (<~20 mm). This effect reduced the availability of SO 4 2– in the pore solution, thereby hindering the penetration of sulfate. Meanwhile, the consumption of portlandite by the pozzolanic reaction lowered the decalcification resistance of the materials. This produced a wide area that endured the decomposition of portlandite and carbonate-AFm. Altogether, blending 30% fly ash did not improve the resistance of the material to either sulfate attacks or decalcification; blending 50% slag can effectively mitigate sulfate ingress, though decalcification may become a governing mechanism in the degradation process.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Bio-Oil Impact on Water Diffusion and Durability of Bitumen: Influence of Aging and Salinity
Bio-oils derived from inexpensive biomass offer environmentally friendly options for modifying bitumen for improved durability or rejuvenating aged material, although their impact on bitumen moisture resistance can be mixed. A better understanding of water diffusion into bitumen and its interactions with bio-oil compounds would aid the development of effective bio-oils. In this study, the effect of water exposure on bio-oil-modified bitumen blends was examined by de-wetting contact angle measurements and differential FTIR spectroscopy. The bio-oils improved the anti-stripping behavior of the bitumen but also increased water absorption which could weaken cohesive strength. Short-term thermal aging increased water diffusion for all bitumen blends including the control, probably due to the presence of more oxidized compounds. Negative peaks of alkanes and polar groups in the differential FTIR data suggest the co-diffusion of surfactant molecules towards the bitumen-water interface. Basic pH increased de-wetting of some bitumen blends from silica, possibly by attacking the silica surface itself. The presence of salt in solution altered the bitumen surface composition through the formation of salt complexes with bitumen or bio-oil compounds. In particular, the formation of calcium-carboxylate complexes appeared to greatly improve anti-stripping effects of bio-oils. Water diffusion into most of the bitumen blends was insensitive to pH or salt concentration except for a few notable outliers. Identifying the compounds responsible for increasing or decreasing water diffusion in these outlier cases would be valuable developing future bio-oil formations that avoid or promote those compounds.
Hung, Albert M.↗
A Mathematical Framework for Representing Cyber-Physical System Interdependencies and Resilience
U.S. critical infrastructure is increasingly composed of integrated cyber-physical systems (CPS) whose components are operationally interdependent. These interdependencies can create additional vulnerabilities beyond those that are typically evaluated through independent physical and cyber risk assessments. These additional vulnerabilities, previously undetected at the sub-system and/or component level, could cause cascading effects across both the physical and cyber domains that could lead to infrastructure disruption or failure. This paper will review an initial mathematical framework developed to help understand the dynamics of these interfacing physical and cyber components at a holistic system level. The resulting framework also provides a method for modeling and assessing the resilience of CPS in complex and adaptive systems. It frames the system in terms of mission performance and the potential effects to performance caused by attacks that are cyber, physical, or blended in nature. The framework utilizes a systems-based, state-space modeling approach to reason about risk, resilience, and interdependencies in CPS. Probabilities are applied to each CPS component regarding a threat (both man-made and natural) and the likelihood of that particular component being impacted, along with indirect impact to other interdependent components. These component-level impacts from threats then translate into mission-level impact and systemic state change.
Brigantic, Robert T.↗
Efficiency of natural pozzolans, ground glasses and coal bottom ashes in mitigating sulfate attack and alkali-silica reaction
The use of pozzolans to partially replace Portland cement in concrete has generally demonstrated beneficial impacts on the durability characteristics of concrete for decades. In this paper a diverse range of pozzolans including natural pozzolans, ground glasses and industrial by-products such as coal ash (fly ash and bottom ash) and silica fume were investigated for their synergistic potential in binary or ternary blends with Portland cement in improving resistance to chemical sulfate attack and alkali-silica reaction (ASR). It is generally considered that pozzolans improve most of the durability issues encountered in concrete, including reducing the risk of sulfate attack or ASR. But this is not always the case. For example, it was found that ground glasses were very efficient in improving sulfate resistance, but their ability to mitigate expansion due to ASR was dictated by the equivalent alkalis content (Na{sub 2}O{sub e}) of the glass and high-alkali soda glass was generally not effective in this role. On the other hand, metakaolin, a highly reactive pozzolan, was highly effective in reducing ASR expansion, but may actually increase the damage due to sulfate attack when used at moderate replacement levels. Most pozzolans, such as low-CaO coal fly ash and ground coal bottom ash, silica fume, and pumice, were effective in controlling expansion due to both ASR and sulfate attack. The results demonstrated that the extent of the positive impact of using natural pozzolans on both properties was variable. The pozzolanic reactivity of materials alone was an unreliable indicator to assess the ability of the pozzolan to suppress expansion due to sulfate attack or ASR.
36 MATERIALS SCIENCE↗
Modelling of the sulfuric acid attack on different types of cementitious materials
A chemical-reactive transport model is used to simulate the sulfuric acid attack of cement pastes based on ordinary Portland cement (CEM I), blended Portland cements (CEM III, CEM IV, and CEM V), and calcium aluminate cement (CAC). This model accounts for the dissolution of cement hydrates (portlandite, C-S-H, hydrogarnet), and the precipitation of deterioration products (ettringite and gypsum). Moreover, diffusion of the aqueous species in the pore space of the material is considered. With this model, the hydrate contents, the porosity, and the deterioration phase contents throughout a sulfuric acid attack are determined. Two indicators are defined to predict the service life of the cementitious materials: the deterioration depth and the dissolved calcium content. These two indicators show that calcium aluminate cement has a better resistance to sulfuric acid attack than that of Portland cements. This better resistance is mainly due to the partial dissolution of CAC hydrate as opposed to the total dissolutions of CH and C-S-H.
36 MATERIALS SCIENCE↗
Securing Smart Manufacturing: Detection of Cyber-Physical Attacks in CNC-Based Systems
As Industry 4.0 advances, the integration of computer numerical control (CNC) machines and advanced manufacturing technologies is transforming production into smart manufacturing systems that blend physical and digital processes as cyber-physical systems. However, this increased cyber-physical connectivity exposes manufacturing systems to cyber threats that can cause severe operational and financial disruptions. This paper presents a comparative study on cyber attacks and anomaly detection techniques in manufacturing, focusing on network traffic from CNC machines. The data extracted from network packets includes machine commands and control signals exchanged between the machine's interface and control system, crucial for maintaining operational integrity. We explore two types of cyber attacks, design modification and command injection, which pose substantial risks to CNC machine productivity and system integrity. Our investigation involves experiments on a real CNC system, highlighting the urgent need for effective detection mechanisms. To address these threats, we evaluate three anomaly detection methods: dynamic time warping (DTW), rolling average, and a deep learning, long short-term memory (LSTM) time-series-based autoencoder. Each is assessed for its effectiveness in identifying anomalous behaviors caused by the attacks. Our findings demonstrate the unique strengths and limitations of each detection technique, providing a deeper understanding of their applicability in realworld manufacturing environments. The comparative analysis indicates that while certain methods are highly effective against specific attack types, others offer broader applicability across different attacks. This study contributes to the accurate detection of anomalies in CNC machining processes, thereby enhancing the reliability and security of smart manufacturing systems against diverse cyber threats.
Williams, Bethanie [Tennessee Technological Univer↗
Self-re-adhering alkali-activated cement composite and its ability to mitigate corrosion of carbon steel in 300 °C hydrothermal environment
Cement-steel interface is a weak point of cement sheath integrity under the environments of high-temperature geothermal wells. This paper presents carbon steel (CS) adherence behaviors of 300 °C-autoclaved alkali-activated Calcium-Aluminate-Cement (CAC)/fly ash F (FAF) (Thermal Shock Resistant Cement, TSRC), granulated blast furnace slag (GBFS)/SiO 2 , and Ordinary Portland Cement (OPC)/SiO 2 blends. The composites’ ability to preserve the bond under the conditions of thermal shock (TS) and strong acid attack (pH 0.6 H 2 SO 4 /brine at 90 °C) as well as their ability to recover the damaged bond and provide steel corrosion protection after additional short-time 5-day curing at 300 °C were evaluated. GBFS/SiO 2 sheath underwent catastrophic failure in the first TS cycle; OPC/SiO 2 lost 78 % and TSRC 51 % of the bond strength in 6 cycles. Only TSRC-CS bond survived 30 days of strong acid exposure; OPC/SiO 2 bond failed after 18 days and GBFS/SiO 2 after 20 days. Addition of micro-glass fibers (MGF) to TSRC further improved its bond strength and CS corrosion protection. Samples of TSRC-CS cured for 30 days at 300 °C before the bond damage recovered 49 % of the damaged bond strength after additional short-time curing. The CS protected by the re-adhered TSRC showed low corrosion rate of 0.13 mm/year (TSRC-MGF), 0.2 mm/year (TSRC) vs. 0.64 mm/year for OPC/SiO 2 protected CS.
15 GEOTHERMAL ENERGY↗
Watching for light: An enterprise roadmap for trustworthy laser threat warning (LTW) to protect national assets
Comprehensive space force protection must include effective and trustworthy laser threat warning (LTW). Effective LTW will detect and characterize threats to space assets and thus enhance space deterrence. LTW must be trustworthy: able to categorize threats and non-threats by being both sensitive to true events and resistant to false alarms. Outside of the laboratory, the statistics and even the roles of lasers become unclear. In the chain of events leading to an attack, the laser may be the last link to be understood. Human situational awareness and informal reasoning must blend statistics with circumstantial evidence to visualize these chains before they are clear. This paper sets out an industrial model for an enterprise that will routinely produce trustworthy LTW. By incorporating psychology and economics, this enterprise can overcome the difficulties and perils of cooperation in networked defense and intelligence. This roadmap suggests how the enterprise can incentivize distracted actors with different goals to share what they know and coordinate what they do.
45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
Semantic Stealth: Crafting Covert Adversarial Patches for Sentiment Classifiers Using Large Language Models
Deep learning models have been shown to be vulnerable to adversarial attacks, in which perturbations to their inputs cause the model to produce incorrect predictions. As opposed to adversarial attacks in computer vision, where small changes introduced to pixel values can drastically alter a model's output while remaining imperceptible to humans, text-based attacks are difficult to conceal due to the discrete nature of tokens. Consequently, unconstrained gradient-based attacks often produce adversarial examples that lack semantic meaning, rendering them detectable through visual inspection or perplexity filters. In contrast to methods that rely on gradient-based optimization in the embedding space, we propose an approach that leverages a Large Language Model's ability to generate grammatically correct and semantically meaningful text to craft adversarial patches that seamlessly blend in with the original input text. These patches can be used to alter the behavior of a target model, such as a text classifier. Since our approach does not rely on gradient backpropagation, it only requires access to the target model's confidence scores, making it a grey-box attack. We demonstrate the feasibility of our approach using open-source LLMs, including Intel's Neural Chat, Llama2, and Mistral-Instruct, to generate adversarial patches capable of altering the predictions of a distilBERT model fine-tuned on the IMDB reviews dataset for sentiment classification.
Roa Carvajal, Maria↗
Resilient Communication Scheme for Distributed Decision of Interconnecting Networks of Microgrids
Networking of microgrids can provide the operational flexibility needed for the increasing number of DERs deployed at the distribution level and supporting end-use demand when there is loss of the bulk power system. But, networked microgrids are vulnerable to cyber-physical attacks and faults due to the complex interconnections. As such, it is necessary To design resilient control systems to support the operations of networked microgrids in responses to cyber-physical attacks and faults. This paper introduces a resilient communication scheme for interconnecting multiple microgrids to support critical demand, in which the interconnection decision can be made distributedly by each microgrid controller even in the presence of cyberattacks to some communication links or microgrid controllers. This scheme blends a randomized peer-to-peer communication network for exchanging information among controllers and resilient consensus algorithms for achieving reliable interconnection agreement. The network of 6 microgrids divided from a modified 123-node test distribution feeder is used to demonstrate the effectiveness of the proposed resilient communication scheme.
Vu, Thanh Long↗
Real-time Intrusion Detection for High-bandwidth Research Networks using Unsupervised Deep Learning
Nowadays, data generated by large-scale scientific experiments are on the scale of petabytes per month. These data are transferred through dedicated high-bandwidth networks across distributed collaboration sites for processing, storage, and analysis. Like general purpose networks, research networks experience attacks. However, monitoring traffic in such high-bandwidth network environments is challenging with conventional deep packet inspection (DPI)- based network intrusion detection systems (NIDS). Recently, machine learning (ML) algorithms have shown potential in detecting anomalous patterns with better generalizability and faster speed. Compared to the general purpose networks, traffic movement in research network is less volatile and more likely to benefit from the ML-based anomaly analysis. We present ThunderSecure, an efficient AI-powered system for detecting anomalies in 100G research networks. ThunderSecure implements a high-throughput packet processing infrastructure using multi-cores and GPUs. It takes time-series statistics from a variety of network measurements and uses 2D Convolutional Neural Network (CNN) to explore both spatial and temporal dependencies in network data stream. Patterns of science data traffic are learned with a one-class neural network, which blends an Adversarial Autoencoder (AAE) with Gaussian mixture density estimation. Testing traffic flows exhibiting significant deviations from the learned baseline of normality are marked as anomalies. We trained ThunderSecure on hundreds of billions of science data packets recorded from a 100G research network at Fermi National Accelerator Laboratory. The detection performance was evaluated on traffic captured from the same research network days and weeks after the training with different types of attack flows injected. To the best of our knowledge, this is the first ML work in the area of network anomaly detection that has been validated on such extreme scale datasets. Results show that ThunderSecure can recognize science data traffic that are captured long after the training and make nearly certain detection on those with anomalous flows injected, even in the case when the anomaly-to-normal mixing ratio is 0.1%.
Gong, Qian↗
Capacity Fade and Its Mitigation in Li-Ion Cells with Silicon-Graphite Electrodes
In this study we scrutinize the causes for capacity fade in lithium-ion cells containing silicongraphite (Si-Gr) blends in the negative electrode and examine approaches for minimizing this fade. The causal mechanisms are inferred from data obtained by electrochemistry, microscopy, spectroscopy and thermogravimetry techniques. The presence of SiOxFy signals in the Si-Gr electrode, LixPOyFz compounds in the electrolyte, and SiO2 species on the NCM523 positive electrode, highlight the crucial role of hydrolytically generated HF, which accelerates the degradation of Si particles. The hydrolysis could result from residual moisture in the current electrode fabrication process, which uses aqueous binders. Water can also be released when silanol groups on the Si nanoparticles react with HF to form Si-F compounds. We note that the primary cause of capacity fade in the full cells is the loss of solid electrolyte interphase (SEI) integrity resulting from volume changes in Si particles during electrochemical cycling. Adding fluoroethylene carbonate (FEC) to the conventional electrolyte slows capacity fade through the formation of a cross linked polymer with elastomeric properties. Further gains in cell longevity are possible by excluding water during electrode fabrication, using hydrolytically stable lithium salts, and adopting electrolyte systems that provide more elasticity to the SEI layers.
fluoroethylene carbonate↗
Reinventing CEMENT: Carbonation-Enabled Mineralization to Engender Novel Technology
Cement is the most important building material used in civil infrastructure but it is extremely energy intensive to produce. We developed novel ways to make cements at low temperatures by mimicking the chemistry of the calcium silicate mineral pseudowollastonite. Pseudowollastonite is interesting because when it is exposed to hot (90-150oC), alkaline conditions with CO2 and water it reacts to form mineral phases that are much stronger than commercial cements. The resulting phases are also much more resistant to acid attack and have lower permeability, which will make them last longer. Many of the mineral phases in our cements are similar to those that exist in ancient Roman cements that have lasted thousands of years. Our objective was to understand how waste materials from industrial processes (such as power production, municipal solid waste treatment, or power plants) can be used to replicate the conditions that give pseudowollastonite cement its remarkable properties. We worked to optimize our formulations and incorporate the cements into concrete blends that the industry can test and consider using in different applications. Our cements could be used in pre-cast cement structural elements, which makes up nearly 20% of the total cement market and is growing rapidly. This work supports ARPA-E program objectives to significantly improve the industrial efficiency of materials production.
36 MATERIALS SCIENCE↗