About

Narayana Aluru is a professor involved in research related to Quantum Computing, as indicated by the group's work on this topic. The group's research includes developing frameworks that integrate quantum-classical methods, such as the hybrid quantum-classical framework combining Multiconfigurational Self-Consistent Field (MCSCF) with the Variational Quantum Eigensolver (VQE). This framework is used to compute binding energies of transition metals on graphene analogues, demonstrating a focus on computational chemistry and quantum simulation. The group also explores various nanotechnology and nanomaterials topics, including nanofluidics, nanobiotechnology, nanomaterials/NEMS, soft matter, and MEMS, with applications spanning from biological channels and sequencing to energy storage, sensing, and multiscale analysis. The research emphasizes multiscale analysis, force fields, machine learning, and uncertainty quantification, reflecting a broad engagement with advanced computational and experimental techniques in nanoscience and quantum computing.

Research topics

• Chemistry
• Nanotechnology
• Materials science
• Artificial Intelligence
• Physical chemistry
• Computer Science
• Optoelectronics
• Physics
• Metallurgy
• Biochemistry
• Molecular biology
• Chromatography
• Thermodynamics
• Chemical engineering
• Biology
• Composite material
• Computer vision
• Computer hardware

Selected publications

• Fluids and Electrolytes under Confinement in Single-Digit Nanopores

  Chemical Reviews · 2023 · 188 citations

  1st authorCorresponding
  • Chemistry
  • Nanotechnology
  • Physical chemistry

  Confined fluids and electrolyte solutions in nanopores exhibit rich and surprising physics and chemistry that impact the mass transport and energy efficiency in many important natural systems and industrial applications. Existing theories often fail to predict the exotic effects observed in the narrowest of such pores, called single-digit nanopores (SDNs), which have diameters or conduit widths of less than 10 nm, and have only recently become accessible for experimental measurements. What SDNs reveal has been surprising, including a rapidly increasing number of examples such as extraordinarily fast water transport, distorted fluid-phase boundaries, strong ion-correlation and quantum effects, and dielectric anomalies that are not observed in larger pores. Exploiting these effects presents myriad opportunities in both basic and applied research that stand to impact a host of new technologies at the water-energy nexus, from new membranes for precise separations and water purification to new gas permeable materials for water electrolyzers and energy-storage devices. SDNs also present unique opportunities to achieve ultrasensitive and selective chemical sensing at the single-ion and single-molecule limit. In this review article, we summarize the progress on nanofluidics of SDNs, with a focus on the confinement effects that arise in these extremely narrow nanopores. The recent development of precision model systems, transformative experimental tools, and multiscale theories that have played enabling roles in advancing this frontier are reviewed. We also identify new knowledge gaps in our understanding of nanofluidic transport and provide an outlook for the future challenges and opportunities at this rapidly advancing frontier.

  PublisherOA PDFDOI

• Ultrasensitive Detection of Dopamine, IL‐6 and SARS‐CoV‐2 Proteins on Crumpled Graphene FET Biosensor

  Advanced Materials Technologies · 2021 · 98 citations

  • Nanotechnology
  • Materials science
  • Optoelectronics

  Universal platforms for biomolecular analysis using label-free sensing modalities can address important diagnostic challenges. Electrical field effect-sensors are an important class of devices that can enable point-of-care sensing by probing the charge in the biological entities. Use of crumpled graphene for this application is especially promising. It is previously reported that the limit of detection (LoD) on electrical field effect-based sensors using DNA molecules on the crumpled graphene FET (field-effect transistor) platform. Here, the crumpled graphene FET-based biosensing of important biomarkers including small molecules and proteins is reported. The performance of devices is systematically evaluated and optimized by studying the effect of the crumpling ratio on electrical double layer (EDL) formation and bandgap opening on the graphene. It is also shown that a small and electroneutral molecule dopamine can be captured by an aptamer and its conformation change induced electrical signal changes. Three kinds of proteins were captured with specific antibodies including interleukin-6 (IL-6) and two viral proteins. All tested biomarkers are detectable with the highest sensitivity reported on the electrical platform. Significantly, two COVID-19 related proteins, nucleocapsid (N-) and spike (S-) proteins antigens are successfully detected with extremely low LoDs. This electrical antigen tests can contribute to the challenge of rapid, point-of-care diagnostics.

  DOI

• Toward Durable Protonic Ceramic Cells: Hydration-Induced Chemical Expansion Correlates with Symmetry in the Y-Doped BaZrO₃–BaCeO₃ Solid Solution

  The Journal of Physical Chemistry C · 2021 · 40 citations

  • Materials science
  • Chemical engineering
  • Thermodynamics

  Electrolytes and electrodes in protonic ceramic electrolysis/fuel cells (PCECs/PCFCs) can exhibit significant chemical strains upon incorporating H2O into the lattice. To increase PCEC/PCFC durability, oxides with lower hydration coefficients of chemical expansion (CCEs) are desired. We hypothesized that lowering symmetry in perovskite-structured proton conductors would lower their CCEs and thus systematically varied the tolerance factor through B-site substitution in the prototypical BaCe0.9–xZrxY0.1O3−δ (0 ≤ x ≤ 0.9) solid solution. X-ray diffraction (XRD) confirmed that symmetry decreased with decreasing Zr content. CCEs were measured by isothermal XRD, dilatometry, and thermogravimetric analysis (TGA) in varied pH2O over 430–630 °C. With decreasing Zr content, the isothermal H2O uptake was greater, but the corresponding chemical strains were smaller; therefore, CCEs monotonically decreased. Density functional theory simulations on end-member BaCe1–yYyO3−δ and BaZr1–yYyO3−δ compositions showed the same trend. Lower CCEs in this solid solution correlate to decreasing symmetry, increasing unit cell volume, increasing oxygen vacancy radius, decreasing bulk modulus, and inter- vs intraoctahedral hydrogen bonding. Microstructural constraints may also contribute to lower macroscopic CCEs in lower-symmetry bulk ceramics based on the observed anisotropic chemical expansion and enhanced strains in powder vs bulk BaCe0.9Y0.1O3−δ. The results inform design principles for the rational tailoring of CCEs and materials choice for chemomechanically durable devices.

  PublisherDOI

• Ultrasensitive detection of nucleic acids using deformed graphene channel field effect biosensors

  Nature Communications · 2020 · 416 citations

  • Nanotechnology
  • Materials science
  • Optoelectronics

  Field-effect transistor (FET)-based biosensors allow label-free detection of biomolecules by measuring their intrinsic charges. The detection limit of these sensors is determined by the Debye screening of the charges from counter ions in solutions. Here, we use FETs with a deformed monolayer graphene channel for the detection of nucleic acids. These devices with even millimeter scale channels show an ultra-high sensitivity detection in buffer and human serum sample down to 600 zM and 20 aM, respectively, which are ∼18 and ∼600 nucleic acid molecules. Computational simulations reveal that the nanoscale deformations can form 'electrical hot spots' in the sensing channel which reduce the charge screening at the concave regions. Moreover, the deformed graphene could exhibit a band-gap, allowing an exponential change in the source-drain current from small numbers of charges. Collectively, these phenomena allow for ultrasensitive electronic biomolecular detection in millimeter scale structures.

  DOI

• Curved neuromorphic image sensor array using a MoS2-organic heterostructure inspired by the human visual recognition system

  Nature Communications · 2020 · 330 citations

  • Computer Science
  • Artificial Intelligence
  • Computer Science

  -organic vertical stack. The curved neuromorphic image sensor array integrated with a plano-convex lens derives a pre-processed image from a set of noisy optical inputs without redundant data storage, processing, and communications as well as without complex optics. The proposed imaging device can substantially improve efficiency of the image acquisition and recognition process, a step forward to the next generation machine vision.

  DOI

Recent grants

• PIRE: Integrated Computational Materials Engineering for Active Materials and Interfaces in Chemical Fuel Production

  NSF · $4.3M · 2015–2021

• Transport and Interfacial Phenomena in Boron Nitride Nanotubes

  NSF · $300k · 2009–2013

• AF:Small:Coarse-Grained Algorithms for Soft Matter

  NSF · $450k · 2009–2013

• Continuum Theories Combined with Atomistic Information for Electrolyte Transport in Nanometer Channels

  NSF · $170k · 2006–2010

• Complex Nonlinear Dynamics in Electrostatic Microelectromechanical Systems (MEMS)

  NSF · $240k · 2006–2010

Frequent coauthors

• Eric Jakobsson

  96 shared

• U. Ravaioli

  82 shared

• Xiang Zhu

  81 shared

• Benoît Roux

  University of Chicago

  81 shared

• H. L. Scott

  81 shared

• Gerhard Klimeck

  Purdue University West Lafayette

  81 shared

• Susan B. Rempe

  Sandia National Laboratories

  81 shared

• Steven J. Plimpton

  Temple University

  81 shared

Education

• Other

  Birla Institute of Technology and Science (BITS), Pilani, India

  1989

• M.S.

  Rensselaer Polytechnic Institute, Troy, NY

  1991

• Ph.D.

  Stanford University, Stanford, CA

  1995

Similar researchers at University of Texas at Austin

• Carlos Caldash-218
• Thomas J. Hughesh-154
• George Georgiouh-107
• Keith Johnstonh-106
• Jeffrey Andrewsh-104