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Cyber-Informed Engineering is a framework which allows engineers to build resiliency to the impacts of cyber attack into engineered systems starting in the early design phases. This article introduces the framework and provides a description of some of its principles and resources for learning more.
Validation is an important step in any systems engineering process to ensure the correct system was made to fulfill stakeholders’ needs, goals, and expectations. In the context of Cyber-Informed Engineering (CIE), validation ensures cyber impact is reduced through implemented design choices and CIE requirements. This document details a process in validating CIE-based design choices relative to their effectiveness at mitigating high consequence events. The document includes a case study to illustrate the CIE validation process. The case study explores the implementation of CIE validation within the engineering lifecycle of a chemical mixing plant.
Cyber-Informed Engineering (CIE) integrates engineering principles into the design, development, and operation of cyber-physical systems (CPS) to mitigate or eliminate the impact of cyber-enabled attacks. In July 2024, Idaho National Laboratory (INL) engaged MITRE researchers to investigate methods for systematically measuring the benefits of CIE implementation. This included evaluating the success and outcomes of CIE, identifying and quantifying the value of early adoption, and determining the business justification for its implementation, especially in existing infrastructure. MITRE reviewed existing methods in engineering and cybersecurity to understand how organizations prioritize security investments, considering their strengths, weaknesses, and relevance to CIE stakeholders. Based on this analysis, MITRE proposed potential approaches for quantifying CIE benefits and provided recommendations for INL's consideration.
This study presents experimental and numerical examination of directly injected (DI) propane and iso-octane, surrogates for liquified petroleum gas (LPG) and gasoline, respectively, at various engine like conditions with the overall objective to establish the baseline with regards to fuel delivery required for future high efficiency DI-LPG fueled heavy-duty engines. Sprays for both iso-octane and propane were characterized and the results from the optical diagnostic techniques including high-speed Schlieren and planar Mie scattering imaging were applied to differentiate the liquid-phase regions and the bulk spray phenomenon from single plume behaviors. The experimental results, coupled with high-fidelity internal nozzle-flow simulations were then used to define best practices in CFD Lagrangian spray models. Optical imaging revealed that unlike iso-octane, propane’s spray propagation was fed by its flash boiling, spray collapse, and high degree of vaporization, resulting in a direct proportionality of propane’s penetration length to temperature. These unique features of propane and its variation from iso-octane’s spray pattern, contributed to its classification as an unconventional spray. Appropriate corrections to the injection and breakup models were developed to reproduce the under-expanded jet dynamics and to mimic the flash boiling-driven spray development observed with propane sprays. The simulation results were found to be sensitive to cone and inclusion angles of the blob injector. The current work represents a first assessment of the capability of the commonly available models for engine-spray simulations and highlights the fact that, despite the reasonable agreement obtained in the fuel vapor morphology, the representation of the liquid phase lacks accuracy and requires further model development.
As nuclear reactors transition from analog to digital technology, the benefits of enhanced operational capabilities and improved efficiencies are potentially offset by cyber risks. Cyber-Informed Engineering (CIE) is an approach that can be used by engineers and staff to characterize and reduce new cyber risks in digital instrumentation and control systems. CIE provides guidance that can be applied throughout the entire systems engineering lifecycle, from conceptual design to decommissioning. In addition to outlining the use of CIE in nuclear reactor applications, this chapter provides a brief primer on nuclear reactor instrumentation and control and the associated cyber risks in existing light water reactors as well as the digital technology that will likely be used in future reactor designs and applications.
The Cyber-Informed Engineering (CIE) Curriculum Guide provides a framework, guidance, and resources for incorporating CIE into university-level engineering programs and related educational activities. A key goal of this guide is to help institutions deliver CIE focused education to produce future engineers and technicians who meet the nation’s infrastructure needs. To accommodate a broad range of educational goals and approaches, this guide outlines several practical integration strategies, links to resources that can accelerate CIE adoption, and offers perspectives from partner academic institutions on the various implementation strategies.
ABSTRACT Separating crude oil from water remains one of the most stubborn challenges in environmental remediation, especially for surfactant‐stabilized emulsions that resist conventional demulsification methods. Here, we report a scalable strategy for achieving near‐zero‐discharge separation of crude oil emulsions using a single superhydrophilic membrane. By applying low‐temperature atomic layer deposition (ALD) of various metal oxides onto activated polyvinylidene fluoride (PVDF) membranes, we create atomically precise surface‐engineered (SE) membranes that maintain an exceptionally strong hydration layer at the membrane‐feed interface, even at high oil loadings. Among the various metal oxides, TiO 2 ‐modified SE membranes exhibit superior interfacial water stability, enabling sustained dewatering of complex crude oil‐water emulsions with >98% separation efficiency and >97% water recovery, compared to only 24.6% water recovery for the pristine membrane. This separation performance surpasses conventional hydrophilic membranes and is comparable to complex Janus channel membrane systems, demonstrating near‐complete emulsion separation using a single membrane. This low‐temperature membrane surface engineering process with atomic‐level precision and potential for scalability via roll‐to‐roll fabrication is promising for industrial‐scale, energy‐efficient water treatment and oil spill remediation applications.
Abstract Lowering the operating temperature (ideally below 400 °C) for solid oxide fuel cell (SOFC) technology deployment has been an important transition that introduces the benefit of reduced operational costs and system durability. However, the key technical issue limiting the transition is the sluggish cathodic performance, namely the oxygen reduction reaction (ORR) rate of the conventional sponge‐like cathode dramatically drops as the temperature reduces. In this paper, 3D engineering of a cathode is conducted on a protonic ceramic fuel cell to obtain an enhanced ORR between 400 and 600 °C. Compared with a cell using a conventional sponge‐like cathode, 3D engineering improves the cathode ORR by 41% at 400 °C with a peak power density of 0.410 W cm −2 . A phase field simulation is applied to assist the engineering by understanding the competition between the cathode mass and charge transfer with different cathode porosities. The results show that structural engineering of existing well‐developed cathodes is a simple and effective method to promote cathode ORR for low temperature SOFC by regulating the mass and charge transfer.
In nature, biological compartments such as cells rely on dynamically controlled permeability for matter exchange and complex cellular activities. Likewise, the ability to engineer compartment permeability is crucial for in vitro systems to gain sustainability, robustness, and complexity. However, rendering in vitro compartments such a capability is challenging. Here, a facile strategy is presented to build permeability-configurable compartments, and marked advantages of such compartmentalization are shown in reconstituting sustained synthetic biology systems in vitro. Through microfluidics, the strategy produces micrometer-sized layered microgels whose shell layer serves as a sieving structure for biomolecules and particles. In this configuration, the transport of DNAs, proteins, and bacteriophages across the compartments can be controlled an guided by a physical model. Through permeability engineering, a compartmentalized cell-free protein synthesis system sustains multicycle protein production; ≈100 000 compartments are repeatedly used in a five-cycle synthesis, featuring a yield of 2.2 mg mL -1 . Further, the engineered bacteria-enclosing compartments possess near-perfect phage resistance and enhanced environmental fitness. In a complex river silt environment, compartmentalized whole-cell biosensors show maintained activity throughout the 32 h pollutant monitoring. It is anticipated that permeability-engineered compartmentalization should pave the way for practical synthetic biology applications such as green bioproduction, environmental sensing, and bacteria-based therapeutics.
Abstract Photoenzymes are biological catalysts that use light to convert starting materials into products. These catalysts require photon absorption for each turnover, making quantum efficiency an important optimization parameter. Flavin‐dependent “ene”‐reductases (EREDs) display latent photoenzymatic activity for synthetically valuable hydroalkylations; however, protein engineering has not been used to optimize this non‐natural function. We describe a protein engineering platform for the high throughput optimization of photoenzymes. A single round of engineering results in improved catalytic function toward the synthesis of γ, δ, ϵ‐lactams, and acyclic amides. Mechanistic studies show that key mutations can alter the enzyme's excited state dynamics, enhance its photon efficiency, and ultimately increase catalyst performance. Transient absorption spectroscopy reveals that engineered variants display dramatically decreased radical lifetimes, indicating an evolution toward a concerted mechanism.
Abstract Cellulosic n ‐butanol from renewable lignocellulosic biomass has gained increased interest. Previously, we have engineered Clostridium cellulovorans , a cellulolytic acidogen, to overexpress the bifunctional butyraldehyde/butanol dehydrogenase gene adh E2 from C. acetobutylicum for n ‐butanol production from crystalline cellulose. However, butanol production by this engineered strain had a relatively low yield of approximately 0.22 g/g cellulose due to the coproduction of ethanol and acids. We hypothesized that strengthening the carbon flux through the central butyryl‐CoA biosynthesis pathway and increasing intracellular NADH availability in C. cellulovorans adh E2 would enhance n ‐butanol production. In this study, thiolase ( thl A CA ) from C. acetobutylicum and 3‐hydroxybutyryl‐CoA dehydrogenase ( hbd CT ) from C. tyrobutyricum were overexpressed in C. cellulovorans adh E2 to increase the flux from acetyl‐CoA to butyryl‐CoA. In addition, ferredoxin‐NAD(P) + oxidoreductase ( fnr ), which can regenerate the intracellular NAD(P)H and thus increase butanol biosynthesis, was also overexpressed. Metabolic flux analyses showed that mutants overexpressing these genes had a significantly increased carbon flux toward butyryl‐CoA, which resulted in increased production of butyrate and butanol. The addition of methyl viologen as an electron carrier in batch fermentation further directed more carbon flux towards n ‐butanol biosynthesis due to increased reducing equivalent or NADH. The engineered strain C. cellulovorans adh E2‐ fnr CA ‐ thl A CA ‐ hbd CT produced n ‐butanol from cellulose at a 50% higher yield (0.34 g/g), the highest ever obtained in batch fermentation by any known bacterial strain. The engineered C. cellulovorans is thus a promising host for n ‐butanol production from cellulosic biomass in consolidated bioprocessing.
Integrating multidisciplinary research in plant genetic engineering and renewable deep eutectic solvents (DESs) can facilitate a sustainable and economic biorefinery. In this work, we leveraged a plant genetic engineering approach to specifically incorporate C6C1 monomers into the lignin structure. By expressing the bacterial ubiC gene in sorghum, p-hydroxybenzoic acid (PB)-rich lignin was incorporated into the plant cell wall while this monomer was completely absent in the lignin of the wild-type (WT) biomass. A DES was synthesized with choline chloride (ChCl) and PB and applied to the pretreatment of the PB-rich mutant biomass for a sustainable biorefinery. The release of fermentable sugars was significantly enhanced (~190 % increase) compared to untreated biomass by the DES pretreatment. In particular, the glucose released from the pretreated mutant biomass was up to 12 % higher than that from the pretreated WT biomass. Lignin was effectively removed from the biomass with the preservation of more than half of the β-Ο-4 linkages without condensed aromatic structures. Hydrogenolysis of the fractionated lignin was conducted to demonstrate the potential of phenolic compound production. In addition, a simple hydrothermal treatment could selectively extract PB from the same engineered lignin, showing a possible circular biorefinery. These results suggest that the combination of PB-based DES and engineered PB-rich biomass is a promising strategy to achieve a sustainable closed-loop biorefinery.
Designing efficient materials is crucial to meeting specific requirements in various electrochemical energy applications. Mono-/bimetallic doped and heterostructure engineering have attracted considerable research interest due to their unique functionalities and potential for electrochemical energy conversion and storage. However, addressing material imperfections such as low conductivity and poor active sites requires a strategic approach to design. This review explores the latest advancements in materials modified by mono-/bimetallic doped and heterojunction strategies for electrochemical energy applications. It can be subdivided into three key points: (i) the regulatory mechanisms of metal doping and heterostructure engineering for materials; (ii) the preparation methods of materials with various engineering strategies; and (iii) the synergistic effects of two engineering approaches, further highlighting their applications in supercapacitors, alkaline ion batteries, and electrocatalysis. Finally, the review concludes with perspectives and recommendations for further research to advance these technologies.
Abstract Geometric engineering is a collection of tools developed to establish dictionaries between local singularities in string theory and (supersymmetric) quantum fields. Extended operators and defects, as well as their higher quantum numbers captured by topological symmetries, can be encoded within geometric engineering dictionaries. In this paper we revisit and clarify aspects of these techniques, with special emphasis on ’t Hooft anomalies, interpreted from the SymTFT perspective as obstructions to the existence of Neumann boundary conditions. These obstructions to gauging higher symmetries are captured via higher link correlators for the SymTFT on spheres. In this work, we give the geometric engineering counterpart of this construction in terms of higher links of topological membranes. We provide a consistency check in the context of 5D SCFTs with anomalous 1-form symmetries, where we give two independent derivations of the anomaly in terms of higher links, one purely field theoretical and the other purely geometrical. Along the way, we also recover the construction of non-invertible duality defects in 4D$$ \mathcal{N} $$ N = 4 SYM from a geometric engineering perspective.
In recent years, as engine control strategies have grown increasingly sophisticated in a continued drive for increasing efficiency and reducing emissions, engine operation has been pushed into regimes that are limited by combustion instabilities. These instabilities produce undesirable abnormal combustion events, which pose barriers to further improvement in engine efficiency. Many of the phenomena involved are difficult to model or control using traditional, purely physics-based models and reactive control approaches. Artificial intelligence (AI) techniques offer some promise for achieving more effective combustion stability control, especially when appropriately applied within a physics-informed framework. This chapter illustrates the current state-of-the-art in applying AI to combustion stability control and examines three case studies with application to the dilute stability limit in spark-ignition engines to illustrate the utility and limitations of AI in these applications.
Bioconversion of lignocellulosic biomass offers a promising alternative to petroleum-based chemical production. However, inefficient xylose utilization and toxic compounds in cellulosic hydrolysate limit microbial fermentation, as the hydrolysate contains substantial amounts of xylose in addition to glucose. To address these challenges, we engineered Issatchenkia orientalis to produce 3-hydroxypropionic acid (3-HP) directly from sorghum hydrolysate under low-pH conditions. A heterologous xylose utilization pathway consisting of XYL1, XYL2, and XYL3 from Scheffersomyces stipitis was introduced into an engineered 3-HP producing strain, enabling efficient conversion of xylose to 3-HP. The engineered strain produced 46.8 g/L 3-HP from sorghum hydrolysate without nutrient supplementation. To eliminate the lag phase under low-pH conditions, fermentation was conducted at pH 6.0 for the first three days, after which pH control was discontinued and in situ 3-HP accumulation buffered the culture. This partial pH control strategy increased 3-HP productivity by 55% from 0.20 to 0.31 g/L∙h, while maintaining low-pH conditions. Introducing an additional copy of XYL2 further increased 3-HP titer to 53.5 g/L and the yield by 33%, from 0.30 to 0.40 g/g sugars, with pH reaching 4.5 at the end of fermentation. This represents one of the highest reported 3-HP titers and yields from cellulosic hydrolysate without additional nutrient supplementation. This work demonstrates a nutrient-independent and low-pH bioprocess for upgrading lignocellulosic hydrolysate into 3-HP, highlighting the industrial potential of engineered xylose-utilizing I. orientalis for sustainable production of platform chemicals from renewable feedstocks.
Optimization of metabolically engineered organisms requires good understanding of producing balanced level of pathway proteins. Targeted proteomics via selected-reaction monitoring (SRM) has been increasingly used in metabolic engineering studies to detect and quantify sets of proteins with high selectivity, multiplexity, and reproducibility. In combination with metabolomics and other omics tools, targeted proteomics has helped optimize the production of many bio-based chemicals in various metabolic engineering cell factories. In this review, we present recent applications of targeted proteomics in metabolic engineering studies and highlight several successful cases of targeted proteomics in boosting production of commodity and high value chemicals. Additionally, we also discuss challenges and limitations of current targeted proteomics and map opportunities for future research.
Hydrogen is considered as one of the most promising options to achieve effective decarbonization of the energy and transportation sectors. As such, it has recently been receiving increasing attention because of its promising potential as an energy carrier for advanced energy and propulsion systems. With a focus on internal combustion engines, direct injection (DI) of gaseous hydrogen during the compression stroke offers great potential for high engine efficiency and specific power while reducing the risk of backfiring and pre-ignition issues. Therefore, many experimental and numerical efforts have recently been dedicated to understanding the physical and chemical behaviors of hydrogen in engine during mixing and combustion. This study focuses on computational fluid dynamics (CFD) modeling of the hydrogen DI process in a hydrogen optical research engine. Under the conditions studied, gaseous hydrogen is injected into the combustion chamber via a centrally located single-hole injector at a pressure of 100 bar. Two configurations, namely low-and high-tumble, are investigated to understand the impact of different in-cylinder flow patterns on the fuel-air mixture preparation. Simulations are carried out using the commercial CFD software CONVERGE. Here, the in-cylinder turbulence is modeled with an unsteady Reynolds-averaged Navier-Stokes (URANS) formulation closed by the renormalization group (RNG) k-ε model. Several numerical methods and model constants, including but not limited to turbulent Schmidt number, are evaluated. The numerical results are systematically compared against experimental measurements of velocity and hydrogen concentration fields on the vertical center plane to assess the performance of the CFD model, unveil the physics of hydrogen mixing, and establish best practices for modeling hydrogen DI under relatively high injection pressure conditions.