Boron Profiles Research Articles

Artificial intelligence approach to analyze SIMS profiles of11B,31P and75As in n- and p-type silicon substrates: experimental investigation

AbstractIn this work, we report an effective approach based on an artificial intelligence technique to investigate the secondary ions mass spectroscopy (SIMS) profiles of boron, phosphorus and arsenic ions. Those dopant ions were implanted into n- and p-type (100) Silicon substrate using the ion implantation technique with energy of 100 and 180 keV. Annealing treatment was conducted at various temperatures ranging from 900 to 1030 °C for 30 min. The doping profile parameters such as the activation energy, diffusion coefficient, junction depth, implant dose, projected range and standard deviation were determined using particle swarm optimization (PSO) algorithm. The efficiency of this strategy was experimentally verified by the fitting between both real measured SIMS profile and predicted ones. In addition, a set of simulated doping profiles was generated for different annealing time to prove the ability of this approach to accurately estimate the above parameters even when changing the experimental conditions.

Light impurities: equilibrium, transport and density profiles in tokamak and stellarator plasmas

The density profiles of light impurities observed in recent decades in a relatively wide variety of experiments on tokamaks and stellarators are analyzed and modeled based on the concept of self-consistent equilibrium and transport of impurity charge states (Shurygin 2020 Nuclear Fusion 60 046001). The emphasis is on the formation of charge-radial equilibrium and its invariant properties affecting transport and density profile. The impurity invariant equilibrium arises due to random compatible charge-radial variations, linking the impurity motion into a general ergodic (Markovian) process governed by a matrix of final probabilities. More than 60 profiles of helium, boron and carbon with central accumulation, flat and hollow were accurately reproduced by invariant dimensionless transport functions. It is shown that the leading processes determining the formation of impurity invariant density profiles in stationary plasma are the processes of ionization-recombination, and not the transport of particles. Successive variations in the hollow density profiles of helium, boron, and carbon observed in experiments can be described as successive invariant profile changes in the recombination rate profiles. The invariant particle diffusive-convective profiles can be calculated directly from the impurity density profiles. A general empirical formula for equilibrium constant of light impurities was proposed.

Study of the Acceptor Removal Effect of LGAD

This article presents a detailed investigation of the influence of carbon co-implantation on the radiation hardness of the low gain avalanche detectors (LGADs). The implantation and thermal annealing of carbon during LGAD fabrication could improve the device’s radiation hardness. As an attempt to explain the mechanism of the implanted carbon to suppress acceptor removal induced by neutron irradiation, the acceptor removal coefficients ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$c$ </tex-math></inline-formula> factors) of LGADs are modeled based on secondary ion mass spectrometry (SIMS), which is used to study carbon and boron distributions in critical regions of LGADs. The model is in good agreement with the radiation hardness measurement of both sensors fabricated by the Institute of High Energy Physics (IHEP) and by others, revealing the reliability of the model in predicting the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$c$ </tex-math></inline-formula> factor without irradiating the sensors but with only density profiles of carbon and boron. This model is pivotal to the design of the next version of IHEP LGAD aiming at reaching better anti-radiation performance.

On the dissolution of a borosilicate glass with the use of isotopic tracing – Insights into the mechanism for the long-term dissolution rate

An understanding of the mechanisms responsible for controlling the long-term corrosion rate of nuclear waste glass is paramount if reliable glass dissolution models are to be used to calculate the controlled release of radionuclides from nuclear waste glass under geologic disposal conditions. Understanding the mechanism that controls silicate glass dissolution rates is also important for natural glasses to understand the role from the dissolution of these glasses has on the composition of natural aquatic systems. Two general mechanisms appear to be responsible for the elemental release from glass to the surrounding biosphere – ion exchange (release principally of alkalis) and matrix dissolution (release of the structural components of the glass). Key unknowns related to these mechanisms are the impact of surface layers on the altered glass and how these layers participate in corrosion. To better understand the impact of these layers on the long-term glass corrosion rate, we made two glasses of the same elemental composition, but with selected elements enriched in specific isotopes for B (11B), Li (6Li), and Si (29Si). We reacted these glasses for 1 y then the solutions from each were exchanged and the chemistry of the solutions and the solids were followed for another 2 y (a total of 3 y). This allowed us to follow changes in the glasses with respect to these elements and how these elements were transported through the alteration layers with time and, for at least one element, into the glass and to deconvolute some competing kinetic steps, such as matrix dissolution and ion exchange. Results from these experiments demonstrate that the release behavior of different elements is strongly dependent on their structural role in the glass (e.g. network formers and modifiers), but, more importantly, the role of water transport and subsequent ion exchange has in the long-term dissolution of the glass studied here. In this article, we highlight the behavior of four elements: lithium, sodium, silicon, and boron. Lithium and sodium, network modifying elements, have similar chemistries. The behavior of Li could be tracked in more detail by following both 6Li and 7Li; Li penetrates through the gel layer in both directions without hinderance and is released from the glass deeper than Na. Silicon, a network forming element, reacts with the silica-rich alteration layer. Boron, a network forming element, does not accumulate in the gel or the pristine glass and has a very sharp elemental profile between the pristine glass and alteration layer. Boron, lithium, and sodium elemental profiles suggest that there is little if any transport control within the alteration layer. These results are similar to those found for basalt glass. However, the correlation between the Li and Na profiles and that of a water species suggest that the limiting release is not controlled by the formation of the gel but rather is a steady state between the diffusion of a water species and matrix dissolution that results in a low release rate for alkali and this provides a steady driving force for the long-term dissolution of glass.

~23% rear side poly-Si/SiO2 passivated silicon solar cell with optimized ion-implanted boron emitter and screen-printed contacts

We report on the understanding and optimization of ion-implanted boron emitters in combination with screen-printed contacts to produce very low recombination current density and high-efficiency cells with rear poly-Si/SiO2 passivated contact. Due to high bulk lifetime in n-base Si and very low recombination in the rear-side n+ passivated contact, recombination in the emitter limits the efficiency potential of manufacturable single-side passivated contact cells. Emitter recombination is governed by recombination under metal contacts (J0e,metal) and in the passivated regions in between (J0e,pass). Emitter profile engineering and dielectric passivation can lower the J0e,pass while paste chemistry and firing conditions can reduce J0e,metal by altering the extent of screen-printing induced emitter surface etching and the percentage of unetched dielectric islands under the metal contacts. We optimized implanted boron profiles, surface concentration and passivation, and junction depth in the sheet resistance range of 48-200 Ω/□ and achieved very low J0e,pass (<15 fA/cm2) for textured boron emitters with Rsheet≥140 Ω/□. Additionally, screen-printing paste and firing optimization reduced J0e,metal from 1172 to 707 fA/cm2 on 170 Ω/□ boron emitter by virtually eliminating emitter surface etching and creating distributed local contacts with unetched dielectric islands (~40% area coverage) underneath the grid lines. This resulted in very low total metallized J0e of 30 fA/cm2 with 3% metal coverage. Our device modeling showed the optimum boron sheet resistance is in the range of 120-170 Ω/□. The simulated results were validated by fabricating fully screen-printed 100 cm2 22.9% efficient bifacial cell with n+ poly-Si/SiO2 passivated rear contact.

Differential nonlinear photocarrier radiometry for characterizing ultra-low energy boron implantation in silicon

The measuring of the depth profile and electrical activity of implantation impurity in the top nanometer range of silicon encounters various difficulties and limitations, though it is known to be critical in fabrication of silicon complementary metal–oxide–semiconductor (CMOS) devices. In the present work, SRIM program and photocarrier radiometry (PCR) are employed to monitor the boron implantation in industrial-grade silicon in an ultra-low implantation energy range from 0.5 keV to 5 keV. The differential PCR technique, which is improved by greatly shortening the measurement time through the simplification of reference sample, is used to investigate the effects of implantation energy on the frequency behavior of the PCR signal for ultra-shallow junction. The transport parameters and thickness of shallow junction, extracted via multi-parameter fitting the dependence of differential PCR signal on modulation frequency to the corresponding theoretical model, well explain the energy dependence of PCR signal and further quantitatively characterize the recovery degree of structure damage induced by ion implantation and the electrical activation degree of impurities. The monitoring of nm-level thickness and electronic properties exhibits high sensitivity and apparent monotonicity over the industrially relevant implantation energy range. The depth profiles of implantation boron in silicon with the typical electrical damage threshold (Y ED) of 5.3 × 1015 cm−3 are evaluated by the SRIM program, and the determined thickness values are consistent well with those extracted by the differential PCR. It is demonstrated that the SRIM and the PCR are both effective tools to characterize ultra-low energy ion implantation in silicon.

Defect Distribution in Doped Silicon Nanostructures Characterized By Means of Scanning Spreading Resistance Microscopy

Scanning Spreading Resistance Microscopy (SSRM) is a well-known technique for electrical characterization of dopant distributions in semiconductors. The resistance between a conductive atomic force microscope (AFM) tip and a large area contact on a semiconductor sample gives direct hint of sample resistivity underneath the tip. The sample surface has to be polished to achieve a smooth surface which is crucial for a low ohmic electrical contact between tip and sample. In theory, the formula of spreading resistance Rspr = ρ/4a with tip radius a connects SSRM raw data to resistivity data which can be transformed to concentration data of corresponding dopants. In experiment, additional series resistances and electrical defects have an impact on the SSRM analysis so that the formula does not hold any more. A SSRM scan on a calibration sample with regions of different well-known dopant concentrations enables an empirical relationship between R and ρ. This relationship is only valid for the specific defect distribution and tip-sample contact of the calibration sample. Both the defect distribution and the tip sample contact, respectively, depend strongly on sample preparation. Reliable calibration of unknown dopant distributions in semiconductor samples is only possible in the case of a perfectly reproducible sample preparation which is however hard to attain. Therefore, an accurate quantification of SSRM data remains difficult.One first step towards SSRM quantification requires an improved understanding and control of electrical defects on the sample surface which affect the SSRM measurement. In this work, we apply SSRM on well characterized n- and p-type dopant profiles in silicon bulk- and nanostructures. The deviation of the experimental SSRM data from simulated spreading resistance profiles provides direct information on type, quantity and origin of electrical defects in the sample.Our analysis of bulk samples reveals two type of preparation induced defects: n-type surface defects and hydrogen traps which deactivate boron atoms. The number of surface defects is proportional to the surface roughness. An improved sample preparation with additional polishing steps reduces the impact of this defect on the SSRM analysis. Hydrogen traps are driven into the sample during water based chemical mechanical polishing steps. An annealing of the sample at 250°C for 20 minutes reactivates most of the boron atoms.A third type of defect was noticed in nanostructured samples. Silicon nano pillars with diameters between 500 and 600 nm are manufactured in a top-down approach out of a silicon wafer with a 600 nm deep boron diffusion profile. Figure 1 shows the SSRM data of the bulk sample (a), the cross-sectional prepared nano pillar (b), and the depth profiles of SSRM analysis (c). The SSRM signal at the top of the pillar is dominated by the boron profile (b). The side walls are covered with gold as second contact for SSRM analysis. Obviously, the SSRM depth profile at the shell region (#2, circles) of the pillar is deeper than at the core (#3, triangles) and in the bulk sample (#1, squares) (c). The dopant distribution itself cannot vary across the pillar as the nanofabrication is done by dry-etching at cryogenic temperatures. We explain the variance in SSRM signal by acceptor defect states at the pillar shell which increase the number of p-type charge carriers in the shell region.COMSOL simulations of the SSRM analysis, including the impact of defects on the resistance profile, is used to quantify the defect distributions. The calculated resistance profiles accurately describe the experimental data (black dotted lines in (c)) and support our assumption on the distribution of electrical defects in silicon nanostructures. Figure 1

Effect of Deposition Conditions on Oxide Parameters of Silicon

In this study, the effect of deposition conditions and the temperature thermal treatment on the oxide parameters of two structures of silicon layers were investigated. The study present the evolution of boron profiles following a dry thermal oxidation in poly-Si/SiO2/c-Si films deposited at 520°C and 605°C temperatures and thermally oxidized in dry oxygen at respectively temperature 840°C, 945°C and 1050°C for tr=1h33’duration. The results show that the deposition conditions and the temperature treatment make a very important impact on the obtained films, which affect the redistribution and localization of dopants. It has been observed that the obtained value of the linear and the parabolic rate constant, the diffusion coefficient and the oxidation thickness are higher in the films deposited at Td = 520°C than those deposited at Td = 605°C. Also, the X-ray diffraction is strongly affected by the oxide thickness deposited between poly-silicon layers and crystalline substrates.

NEUTRON DEPTH PROFILE CALCULATIONS USING ARTIFICIAL NEURAL NETWORKS

Neutron depth profiling (NDP) is a non-destructive technique used for identifying the concentration of impurity isotopes below the sample surface. NDP is carried out by detection of the emitted charged particles resulting from bombarding the sample with neutrons. NDP specifies the isotopic concentration versus the sample depth for a few micrometers below the surface. The sample is bombarded inside a research reactor using a thermal neutron beam. Charged particles like alpha particles or protons are produced from the neutron induced reactions in the sample. Each neutron isotopic interaction produces a certain Q, indicating a specific kinetic energy for the emitted charged particle. As the charged particle travels through the sample to eject the surface, it loses energy to atoms (electrons) on its path. The charged particle energy loss holds information regarding the number of atoms by which the emitted particle passed, thus indicating its original depth. The purpose of this work is to check the capability of Artificial Neural Networks (ANNs) in predicting the boron concentration profile across a boro-silicate sample of thickness 3.5 μm divided into 10 layers. Each layer included different boron concentration than the other. Also, the boron concentration had the values {0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1}. Training, validation, and test data were generated synthetically using MCNP6 in which the boron concentrations varied in the layer number from one sample to another. MCNP6 model consisted of a silicon barrier detector, boro-silicate sample, chamber body and an idealized thermal neutron source. The detector, sample, and the source were located in a voided chamber. The samples were irradiated with a 0.025 eV monoenergetic thermal neutron beam from a monodirectional disk source. To cover the whole area of the samples, the thermal neutron beam had a radius of 3 cm. The silicon detector active volume was modelled as a 100 μm thick and 3 cm radius facing the sample directly. The sample, beam, and the detector were placed on the same axis. Ten ANN regression models were developed, one for each layer boron concentration prediction where the input for each model was the alpha spectrum read by the detector, while the output was the boron concentration for each layer. Results showed regression values higher than 0.94 for all of the developed models. ANNs proved its capability of predicting the boron profile form the alpha spectrum read by the detector regarding neutron depth profiling in a boro-silicate samples.

Effect of Deposition Conditions on Oxide Parameters of Silicon

In this study, the effect of deposition conditions and the temperature thermal treatment on the oxide parameters of two structures of silicon layers were investigated. The study present the evolution of in situ boron profiles following a dry thermal oxidation in poly-Si/SiO2/c-Si films deposited at 520°C and 605°C temperatures and thermally oxidized in dry oxygen at respectively temperature 840°C, 945°C and 1050°C for duration tr=1h33’. The results show that the deposition conditions and the temperature treatment make a very important impact on the obtained films, which affect the redistribution and localization of dopants. It has been observed that the obtained value of the linear and the parabolic rate constant, the diffusion coefficient and the oxidation thickness are higher in the films deposited at Td = 520°C than those deposited at Td = 605°C. Also, the X-ray diffraction is strongly affected by the oxide thickness deposited between poly-silicon layers and crystalline substrates.

Characterization of the boron profile and coordination in altered glass layers by EEL spectroscopy

Electron energy-loss spectroscopy was used to characterize the boron profile and its coordination (BIII and BIV), along the complex alteration layer of glass samples altered for 511 days at 50 °C in solution containing FeCl2, MgCl2 and/or CaCl2. To reach this goal, the impact of both TEM operating conditions and sample preparation on the determination of the boron coordination was first studied using mineralogical and pristine glasses reference samples. Then, the boron concentration profiles were characterized in the glass alteration layer. These profiles were found to be S-shaped with a thickness around forty nanometers. The proportion of BIII was found to decrease with the boron total concentration (from the pristine glass to the gel layer), which suggests a higher bonding strength for BIV bonds than that of BIII bonds under the alteration conditions. These findings are of tremendous interest to advance further in the understanding of glass alteration mechanisms.

Monolithically Integrated Diffused Silicon Two-Zone Heaters for Silicon-Pyrex Glass Microreactors for Production of Nanoparticles: Heat Exchange Aspects.

We present the design, simulation, fabrication and characterization of monolithically integrated high resistivity p-type boron-diffused silicon two-zone heaters in a model high temperature microreactor intended for nanoparticle fabrication. We used a finite element method for simulations of the heaters’ operation and performance. Our experimental model reactor structure consisted of a silicon wafer anodically bonded to a Pyrex glass wafer with an isotropically etched serpentine microchannels network. We fabricated two separate spiral heaters with different temperatures, mutually thermally isolated by barrier apertures etched throughout the silicon wafer. The heaters were characterized by electric measurements and by infrared thermal vision. The obtained results show that our proposed procedure for the heater fabrication is robust, stable and controllable, with a decreased sensitivity to random variations of fabrication process parameters. Compared to metallic or polysilicon heaters typically integrated into microreactors, our approach offers improved control over heater characteristics through adjustment of the Boron doping level and profile. Our microreactor is intended to produce titanium dioxide nanoparticles, but it could be also used to fabricate nanoparticles in different materials as well, with various parameters and geometries. Our method can be generally applied to other high-temperature microsystems.

SIMULATION OF BORON DIFFUSION IN THE NEAR-SURFACE REGION OF SILICON SUBSTRATE

The mechanism of boron-enhanced diffusion from a thin boron layer deposited on the surface in the case of silicon crystal doping is proposed and investigated. It was supposed that lattice contraction occurs in the vicinity of the surface due to the difference between the atomic radii of boron and silicon. This lattice contraction provides a stress-mediated diffusion of silicon self-interstitials from the near-surface region to the bulk of a semiconductor. Due to the stress-mediated diffusion, the near-surface region is depleted of silicon self-interstitials, and simultaneous oversaturation of this species occurs in the bulk. In this way, a strong nonuniform distribution of silicon self-interstitials in the vicinity of the surface is formed without regard to the large migration length of this species. The oversaturation of the bulk of a semiconductor with nonequilibrium self-interstitials allows one to explain the boron-enhanced diffusion of impurity atoms. The strong nonuniform distribution of these point defects also results in a specific form of boron concentration profile in the vicinity of the surface. Good agreement of the calculated boron profile with the experimental data for the entire doped region was obtained within the limit of the proposed model.

Light impurity transport in tokamaks: on the impact of neutral beam fast ions

Previous studies (e.g. (Kappatou 2019 Nucl. Fusion 59 056014)) have shown that discrepancies exist between experimental and modelled light impurity peaking in specific regimes. In particular, in NBI heated plasmas, the strong hollowness of boron profiles are not captured by the modelling. In this context, a dedicated ASDEX Upgrade discharge, including boron and helium density measurements, is studied where such discrepancies appear. Emphasis is given to the impact of fast ions on the turbulent and neoclassical impurity transport computed with the codes GKW and NEO, respectively. It is shown that fast ions increase the turbulent outward impurity convection via an increase of both thermo- and roto-diffusion. This increase is correlated with the stabilisation of the ion temperature gradient driven mode (ITG). Additionally, the ratio of the turbulent impurity diffusion over the ion heat diffusion is reduced with fast ions, which in turn, increases the neoclassical contributions to the impurity peaking. Finally, neoclassical convection is also enhanced through changes in the ion density gradient due to the modification of the quasi-neutrality condition in the presence of peaked fast ion profiles. The combination of these three mechanisms induced by the fast ion population has a significant impact on the development of hollow boron profiles, up to experimental levels.

Double-sided TOPCon solar cells on textured wafer with ALD SiOx layer

Double-sided, front and rear, tunnel oxide passivated contact (TOPCon) of crystalline silicon (c-Si) solar cells on textured wafer is presented. The double-sided TOPCon structure is composed of (p) poly-Si/SiOx/(n) c-Si/SiOx/(n) poly-Si, where the silicon oxide (SiOx) layer is formed by atomic layer deposition (ALD). With a 0.6 ± 0.1 nm-thick SiOx layer, an 18.8 %-efficiency solar cell is fabricated, where an excellent short circuit current above 39 mA/cm2 is confirmed for a front grid structure. The solar cell performance is improved by optimizing the boron and hydrogen diffusion profiles near the p-side SiOx/c-Si interface.

Automated data processing of neutron depth profiling spectra using an Artificial Neural Network

This work examines the possibility of using an Artificial Neural Network (ANN) to interpret Neutron Depth Profiling (NDP) spectra. AMonte Carlo of N-Particle (MCNP6) radiation transport model was used to simulate the alpha energy spectrum of NIST standard SRM 2137 during a 10B(n, α)7Li NDP measurement. Simulations of 300 randomly generated specimens were also performed and used to train an Artificial Neural Network (ANN). The depth profile of boron in the SRM2137 NIST standard was obtained by processing the MCNP pulse height light tally with the trained ANN. This was compared to the results of traditional analysis using stopping tables. The traditional analysis and ANN results both agree well with the reference SRM 2137 boron profile.

Analysis of boron profiles as function of nitrogen content in silicon

In this paper, the Secondary Ion Mass Spectroscopy (SIMS) technique is used to study the experimental depth concentration profiles of boron, nitrogen, and other expected atoms in amorphous nitrogen doped silicon (NiDoS) layers deposited at Td = 460 °C by low-pressure chemical vapor deposition (LPCVD) process from disilane. It has been observed that the reduction of implanted boron penetration is important when the film deposition temperature is low and the nitrogen in-situ doping step is initially improved. And, the simulation results with the experientially measured projected range values using SIMS are in good agreement.

Diffusion of Phosphorus and Boron from Atomic Layer Deposition Oxides into Silicon

Oxides containing group III or group V elements (B2O3/Sb2O5 and P2O5/Sb2O5) are grown by plasma‐assisted atomic layer deposition (ALD) on single‐crystalline silicon and serve as dopant sources for conformal and shallow doping. Transport phenomena in ALD‐oxide–Si structures during rapid thermal annealing (RTA) are investigated subsequently by X‐ray photoelectron spectroscopy (XPS), transmission electron microscopy (TEM), and secondary ion mass spectrometry (SIMS). The XPS and TEM analyses of the annealed ALD‐oxide–Si structures demonstrate that the ALD oxide converts to a silicon oxide and partially evaporates during annealing. In addition, dopant‐containing, spherical, and partially crystalline particles form in the oxide, and Si‐P precipitates at the oxide–Si interface. After diffusion annealing at 1000 °C, the SIMS analyses reveal phosphorus and boron concentration profiles in the silicon substrate with maximum concentrations exceeding their solid solubility limits by roughly one order of magnitude. Experimental doping profiles of phosphorus and boron in silicon are compared with simulation results, considering a slight injection of self‐interstitials and dynamical defect clustering.

Kinetics of Formation of Fe2B Layers on AISI S1 Steel

In the present work, the AISI S1 steel was pack-borided in the temperature range 1123-1273 K for 2- 8 h to form a compact layer of Fe2B at the material surface. A recent kinetic approach, based on the integral method, was proposed to estimate the boron diffusion coefficients in the Fe2B layers formed on AISI S1 steel in the temperature range 1123-1273 K. In this model, the boron profile concentration in the Fe2B layer is described by a polynomial form based on the Goodman’s method. As a main result, the value of activation energy for boron diffusion in AISI S1 steel was estimated as 199.15 kJmol-1 by the integral method and compared with the values available in the literature. Three extra boriding conditions were used to extend the validity of the kinetic model based on the integral method as well as other diffusion models. An experimental validation was made by comparing the values of Fe2B layers’ thicknesses with those predicted by different diffusion models. Finally, an iso-thickness diagram was proposed for describing the evolution of Fe2B layer thickness as a function of boriding parameters.

The Physiological Role of Boron on Health.

Boron is an essential mineral that plays an important role in several biological processes. Boron is required for growth of plants, animals, and humans. There are increasing evidences of this nutrient showing a variety of pleiotropic effects, ranging from anti-inflammatory and antioxidant effects to the modulation of different body systems. In the past few years, the trials showed disease-related polymorphisms of boron in different species, which has drawn attention of scientists to the significance of boron to health. Low boron profile has been related with poor immune function, increased risk of mortality, osteoporosis, and cognitive deterioration. High boron status revealed injury to cell and toxicity in different animals and humans. Some studies have shown some benefits of higher boron status, but findings have been generally mixed, which perhaps accentuates the fact that dietary intake will benefit only if supplemental amount is appropriate. The health benefits of boron are numerous in animals and humans; for instance, it affects the growth at safe intake. Central nervous system shows improvement and immune organs exhibit enhanced immunity with boron supplementation. Hepatic metabolism also shows positive changes in response to dietary boron intake. Furthermore, animals and human fed diets supplemented with boron reveal improved bone density and other benefits including embryonic development, wound healing, and cancer therapy. It has also been reported that boron affects the metabolism of several enzymes and minerals. In the background of these health benefits, low or high boron status is giving cause for concern. Additionally, researches are needed to further elucidate the mechanisms of boron effects, and determine the requirements in different species.